Identification of potential crucial genes associated with steroid-induced necrosis of femoral head based on gene expression profile.

PubMed

Lin, Zhe; Lin, Yongsheng

2017-09-05

The aim of this study was to explore potential crucial genes associated with the steroid-induced necrosis of femoral head (SINFH) and to provide valid biological information for further investigation of SINFH. Gene expression profile of GSE26316, generated from 3 SINFH rat samples and 3 normal rat samples were downloaded from Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were identified using LIMMA package. After functional enrichment analyses of DEGs, protein-protein interaction (PPI) network and sub-PPI network analyses were conducted based on the STRING database and cytoscape. In total, 59 up-regulated DEGs and 156 downregulated DEGs were identified. The up-regulated DEGs were mainly involved in functions about immunity (e.g. Fcer1A and Il7R), and the downregulated DEGs were mainly enriched in muscle system process (e.g. Tnni2, Mylpf and Myl1). The PPI network of DEGs consisted of 123 nodes and 300 interactions. Tnni2, Mylpf, and Myl1 were the top 3 outstanding genes based on both subgraph centrality and degree centrality evaluation. These three genes interacted with each other in the network. Furthermore, the significant network module was composed of 22 downregulated genes (e.g. Tnni2, Mylpf and Myl1). These genes were mainly enriched in functions like muscle system process. The DEGs related to the regulation of immune system process (e.g. Fcer1A and Il7R), and DEGs correlated with muscle system process (e.g. Tnni2, Mylpf and Myl1) may be closely associated with the progress of SINFH, which is still needed to be confirmed by experiments. Copyright © 2017 Elsevier B.V. All rights reserved.

Identification of CRASH, a gene deregulated in gynecological tumors.

PubMed

Evtimova, Vesna; Zeillinger, Robert; Kaul, Sepp; Weidle, Ulrich H

2004-01-01

We have identified CRASH, a human asparaginase-like protein which is composed of 308 amino acids and exhibits 32% homology to human aspartylglucosaminadase at the amino acid level. Database analysis revealed that the gene corresponding to CRASH is composed of 7 exons and 6 introns. Steady-state level of CRASH mRNA was found to be increased in 5 cell lines derived from metastatic lesions compared with 2 cell lines derived from primary mammary carcinoma and HMEC (human mammary epithelial cells). We found that the mRNA level of CRASH correlates with the metastatic propensity of several isogenic human colon cancer and pancreatic carcinoma cell lines. CRASH corresponds to a recently identified sperm autoantigen and furthermore we have demonstrated inducibility of CRASH mRNA by androgen and progesterone. Investigation of several types of human cancers and their corresponding normal tissues revealed high levels of CRASH mRNA in uterine, mammary and ovarian tumors compared with the corresponding normal tissues. CRASH mRNA expression was analysed in breast cancer samples with disclosed clinico-pathological features and corresponding normal tissues. The levels of CRASH mRNA were significantly up-regulated in tumors compared with normal breast tissues and correlate with lack of estrogen receptor expression of the tumors.

Identification of potential crucial genes and construction of microRNA-mRNA negative regulatory networks in osteosarcoma.

PubMed

Pan, Yue; Lu, Lingyun; Chen, Junquan; Zhong, Yong; Dai, Zhehao

2018-01-01

This study aimed to identify potential crucial genes and construction of microRNA-mRNA negative regulatory networks in osteosarcoma by comprehensive bioinformatics analysis. Data of gene expression profiles (GSE28424) and miRNA expression profiles (GSE28423) were downloaded from GEO database. The differentially expressed genes (DEGs) and miRNAs (DEMIs) were obtained by R Bioconductor packages. Functional and enrichment analyses of selected genes were performed using DAVID database. Protein-protein interaction (PPI) network was constructed by STRING and visualized in Cytoscape. The relationships among the DEGs and module in PPI network were analyzed by plug-in NetworkAnalyzer and MCODE seperately. Through the TargetScan and comparing target genes with DEGs, the miRNA-mRNA regulation network was established. Totally 346 DEGs and 90 DEMIs were found to be differentially expressed. These DEGs were enriched in biological processes and KEGG pathway of inflammatory immune response. 25 genes in the PPI network were selected as hub genes. Top 10 hub genes were TYROBP, HLA-DRA, VWF, PPBP, SERPING1, HLA-DPA1, SERPINA1, KIF20A, FERMT3, HLA-E. PPI network of DEGs followed a pattern of power law network and met the characteristics of small-world network. MCODE analysis identified 4 clusters and the most significant cluster consisted of 11 nodes and 55 edges. SEPP1, CKS2, TCAP, BPI were identified as the seed genes in their own clusters, respectively. The miRNA-mRNA regulation network which was composed of 89 pairs was established. MiR-210 had the highest connectivity with 12 target genes. Among the predicted target of MiR-96, HLA-DPA1 and TYROBP were the hub genes. Our study indicated possible differentially expressed genes and miRNA, and microRNA-mRNA negative regulatory networks in osteosarcoma by bioinformatics analysis, which may provide novel insights for unraveling pathogenesis of osteosarcoma.

Differential expression of the nuclear-encoded mitochondrial transcriptome in pediatric septic shock.

PubMed

Weiss, Scott L; Cvijanovich, Natalie Z; Allen, Geoffrey L; Thomas, Neal J; Freishtat, Robert J; Anas, Nick; Meyer, Keith; Checchia, Paul A; Shanley, Thomas P; Bigham, Michael T; Fitzgerald, Julie; Banschbach, Sharon; Beckman, Eileen; Howard, Kelli; Frank, Erin; Harmon, Kelli; Wong, Hector R

2014-11-19

Increasing evidence supports a role for mitochondrial dysfunction in organ injury and immune dysregulation in sepsis. Although differential expression of mitochondrial genes in blood cells has been reported for several diseases in which bioenergetic failure is a postulated mechanism, there are no data about the blood cell mitochondrial transcriptome in pediatric sepsis. We conducted a focused analysis using a multicenter genome-wide expression database of 180 children ≤ 10 years of age with septic shock and 53 healthy controls. Using total RNA isolated from whole blood within 24 hours of PICU admission for septic shock, we evaluated 296 nuclear-encoded mitochondrial genes using a false discovery rate of 1%. A series of bioinformatic approaches were applied to compare differentially expressed genes across previously validated gene expression-based subclasses (groups A, B, and C) of pediatric septic shock. In total, 118 genes were differentially regulated in subjects with septic shock compared to healthy controls, including 48 genes that were upregulated and 70 that were downregulated. The top scoring canonical pathway was oxidative phosphorylation, with general downregulation of the 51 genes corresponding to the electron transport system (ETS). The top two gene networks were composed primarily of mitochondrial ribosomal proteins highly connected to ETS complex I, and genes encoding for ETS complexes I, II, and IV that were highly connected to the peroxisome proliferator activated receptor (PPAR) family. There were 162 mitochondrial genes differentially regulated between groups A, B, and C. Group A, which had the highest maximum number of organ failures and mortality, exhibited a greater downregulation of mitochondrial genes compared to groups B and C. Based on a focused analysis of a pediatric septic shock transcriptomic database, nuclear-encoded mitochondrial genes were differentially regulated early in pediatric septic shock compared to healthy controls, as well as across genotypic and phenotypic distinct pediatric septic shock subclasses. The nuclear genome may be an important mechanism contributing to alterations in mitochondrial bioenergetic function and outcomes in pediatric sepsis.

The TTSMI database: a catalog of triplex target DNA sites associated with genes and regulatory elements in the human genome.

PubMed

Jenjaroenpun, Piroon; Chew, Chee Siang; Yong, Tai Pang; Choowongkomon, Kiattawee; Thammasorn, Wimada; Kuznetsov, Vladimir A

2015-01-01

A triplex target DNA site (TTS), a stretch of DNA that is composed of polypurines, is able to form a triple-helix (triplex) structure with triplex-forming oligonucleotides (TFOs) and is able to influence the site-specific modulation of gene expression and/or the modification of genomic DNA. The co-localization of a genomic TTS with gene regulatory signals and functional genome structures suggests that TFOs could potentially be exploited in antigene strategies for the therapy of cancers and other genetic diseases. Here, we present the TTS Mapping and Integration (TTSMI; http://ttsmi.bii.a-star.edu.sg) database, which provides a catalog of unique TTS locations in the human genome and tools for analyzing the co-localization of TTSs with genomic regulatory sequences and signals that were identified using next-generation sequencing techniques and/or predicted by computational models. TTSMI was designed as a user-friendly tool that facilitates (i) fast searching/filtering of TTSs using several search terms and criteria associated with sequence stability and specificity, (ii) interactive filtering of TTSs that co-localize with gene regulatory signals and non-B DNA structures, (iii) exploration of dynamic combinations of the biological signals of specific TTSs and (iv) visualization of a TTS simultaneously with diverse annotation tracks via the UCSC genome browser. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

A system view and analysis of essential hypertension.

PubMed

Botzer, Alon; Grossman, Ehud; Moult, John; Unger, Ron

2018-05-01

The goal of this study was to investigate genes associated with essential hypertension from a system perspective, making use of bioinformatic tools to gain insights that are not evident when focusing at a detail-based resolution. Using various databases (pathways, Genome Wide Association Studies, knockouts etc.), we compiled a set of about 200 genes that play a major role in hypertension and identified the interactions between them. This enabled us to create a protein-protein interaction network graph, from which we identified key elements, based on graph centrality analysis. Enriched gene regulatory elements (transcription factors and microRNAs) were extracted by motif finding techniques and knowledge-based tools. We found that the network is composed of modules associated with functions such as water retention, endothelial vasoconstriction, sympathetic activity and others. We identified the transcription factor SP1 and the two microRNAs miR27 (a and b) and miR548c-3p that seem to play a major role in regulating the network as they exert their control over several modules and are not restricted to specific functions. We also noticed that genes involved in metabolic diseases (e.g. insulin) are central to the network. We view the blood-pressure regulation mechanism as a system-of-systems, composed of several contributing subsystems and pathways rather than a single module. The system is regulated by distributed elements. Understanding this mode of action can lead to a more precise treatment and drug target discovery. Our analysis suggests that insulin plays a primary role in hypertension, highlighting the tight link between essential hypertension and diseases associated with the metabolic syndrome.

JICST Factual Database JICST DNA Database

NASA Astrophysics Data System (ADS)

Shirokizawa, Yoshiko; Abe, Atsushi

Japan Information Center of Science and Technology (JICST) has started the on-line service of DNA database in October 1988. This database is composed of EMBL Nucleotide Sequence Library and Genetic Sequence Data Bank. The authors outline the database system, data items and search commands. Examples of retrieval session are presented.

Comparative Pan-Genome Analysis of Piscirickettsia salmonis Reveals Genomic Divergences within Genogroups.

PubMed

Nourdin-Galindo, Guillermo; Sánchez, Patricio; Molina, Cristian F; Espinoza-Rojas, Daniela A; Oliver, Cristian; Ruiz, Pamela; Vargas-Chacoff, Luis; Cárcamo, Juan G; Figueroa, Jaime E; Mancilla, Marcos; Maracaja-Coutinho, Vinicius; Yañez, Alejandro J

2017-01-01

Piscirickettsia salmonis is the etiological agent of salmonid rickettsial septicemia, a disease that seriously affects the salmonid industry. Despite efforts to genomically characterize P. salmonis , functional information on the life cycle, pathogenesis mechanisms, diagnosis, treatment, and control of this fish pathogen remain lacking. To address this knowledge gap, the present study conducted an in silico pan-genome analysis of 19 P. salmonis strains from distinct geographic locations and genogroups. Results revealed an expected open pan-genome of 3,463 genes and a core-genome of 1,732 genes. Two marked genogroups were identified, as confirmed by phylogenetic and phylogenomic relationships to the LF-89 and EM-90 reference strains, as well as by assessments of genomic structures. Different structural configurations were found for the six identified copies of the ribosomal operon in the P. salmonis genome, indicating translocation throughout the genetic material. Chromosomal divergences in genomic localization and quantity of genetic cassettes were also found for the Dot/Icm type IVB secretion system. To determine divergences between core-genomes, additional pan-genome descriptions were compiled for the so-termed LF and EM genogroups. Open pan-genomes composed of 2,924 and 2,778 genes and core-genomes composed of 2,170 and 2,228 genes were respectively found for the LF and EM genogroups. The core-genomes were functionally annotated using the Gene Ontology, KEGG, and Virulence Factor databases, revealing the presence of several shared groups of genes related to basic function of intracellular survival and bacterial pathogenesis. Additionally, the specific pan-genomes for the LF and EM genogroups were defined, resulting in the identification of 148 and 273 exclusive proteins, respectively. Notably, specific virulence factors linked to adherence, colonization, invasion factors, and endotoxins were established. The obtained data suggest that these genes could be directly associated with inter-genogroup differences in pathogenesis and host-pathogen interactions, information that could be useful in designing novel strategies for diagnosing and controlling P. salmonis infection.

Comparative Pan-Genome Analysis of Piscirickettsia salmonis Reveals Genomic Divergences within Genogroups

PubMed Central

Nourdin-Galindo, Guillermo; Sánchez, Patricio; Molina, Cristian F.; Espinoza-Rojas, Daniela A.; Oliver, Cristian; Ruiz, Pamela; Vargas-Chacoff, Luis; Cárcamo, Juan G.; Figueroa, Jaime E.; Mancilla, Marcos; Maracaja-Coutinho, Vinicius; Yañez, Alejandro J.

2017-01-01

Piscirickettsia salmonis is the etiological agent of salmonid rickettsial septicemia, a disease that seriously affects the salmonid industry. Despite efforts to genomically characterize P. salmonis, functional information on the life cycle, pathogenesis mechanisms, diagnosis, treatment, and control of this fish pathogen remain lacking. To address this knowledge gap, the present study conducted an in silico pan-genome analysis of 19 P. salmonis strains from distinct geographic locations and genogroups. Results revealed an expected open pan-genome of 3,463 genes and a core-genome of 1,732 genes. Two marked genogroups were identified, as confirmed by phylogenetic and phylogenomic relationships to the LF-89 and EM-90 reference strains, as well as by assessments of genomic structures. Different structural configurations were found for the six identified copies of the ribosomal operon in the P. salmonis genome, indicating translocation throughout the genetic material. Chromosomal divergences in genomic localization and quantity of genetic cassettes were also found for the Dot/Icm type IVB secretion system. To determine divergences between core-genomes, additional pan-genome descriptions were compiled for the so-termed LF and EM genogroups. Open pan-genomes composed of 2,924 and 2,778 genes and core-genomes composed of 2,170 and 2,228 genes were respectively found for the LF and EM genogroups. The core-genomes were functionally annotated using the Gene Ontology, KEGG, and Virulence Factor databases, revealing the presence of several shared groups of genes related to basic function of intracellular survival and bacterial pathogenesis. Additionally, the specific pan-genomes for the LF and EM genogroups were defined, resulting in the identification of 148 and 273 exclusive proteins, respectively. Notably, specific virulence factors linked to adherence, colonization, invasion factors, and endotoxins were established. The obtained data suggest that these genes could be directly associated with inter-genogroup differences in pathogenesis and host-pathogen interactions, information that could be useful in designing novel strategies for diagnosing and controlling P. salmonis infection. PMID:29164068

Purification and characterization of gamma poly glutamic acid from newly Bacillus licheniformis NRC20.

PubMed

Tork, Sanaa E; Aly, Magda M; Alakilli, Saleha Y; Al-Seeni, Madeha N

2015-03-01

γ-poly glutamic acid (γ-PGA) has received considerable attention for pharmaceutical and biomedical applications. γ-PGA from the newly isolate Bacillus licheniformis NRC20 was purified and characterized using diffusion distance agar plate, mass spectrometry and thin layer chromatography. All analysis indicated that γ-PGA is a homopolymer composed of glutamic acid. Its molecular weight was determined to be 1266 kDa. It was composed of L- and D-glutamic acid residues. An amplicon of 3050 represents the γ-PGA-coding genes was obtained, sequenced and submitted in genbank database. Its amino acid sequence showed high similarity with that obtained from B. licheniformis strains. The bacterium NRC 20 was independent of L-glutamic acid but the polymer production enhanced when cultivated in medium containing L-glutamic acid as the sole nitrogen source. Finally we can conclude that γ-PGA production from B. licheniformis NRC20 has many promised applications in medicine, industry and nanotechnology. Copyright © 2014 Elsevier B.V. All rights reserved.

Cloning of a gene (RIG-G) associated with retinoic acid-induced differentiation of acute promyelocytic leukemia cells and representing a new member of a family of interferon-stimulated genes

PubMed Central

Yu, Man; Tong, Jian-Hua; Mao, Mao; Kan, Li-Xin; Liu, Meng-Min; Sun, Yi-Wu; Fu, Gang; Jing, Yong-Kui; Yu, Long; Lepaslier, Denis; Lanotte, Michel; Wang, Zhen-Yi; Chen, Zhu; Waxman, Samuel; Wang, Ya-Xin; Tan, Jia-Zhen; Chen, Sai-Juan

1997-01-01

In a cell line (NB4) derived from a patient with acute promyelocytic leukemia, all-trans-retinoic acid (ATRA) and interferon (IFN) induce the expression of a novel gene we call RIG-G (for retinoic acid-induced gene G). This gene codes for a 58-kDa protein containing 490 amino acids with several potential sites for post-translational modification. In untreated NB4 cells, the expression of RIG-G is undetectable. ATRA treatment induces the transcriptional expression of RIG-G relatively late (12–24 hr) in a protein synthesis-dependent manner, whereas IFN-α induces its expression early (30 min to 3 hr). Database search has revealed a high-level homology between RIG-G and several IFN-stimulated genes in human (ISG54K, ISG56K, and IFN-inducible and retinoic acid-inducible 58K gene) and some other species, defining a well conserved gene family. The gene is composed of two exons and has been mapped by fluorescence in situ hybridization to chromosome 10q24, where two other human IFN-stimulated gene members are localized. A synergistic induction of RIG-G expression in NB4 cells by combined treatment with ATRA and IFNs suggests that a collaboration exists between their respective signaling pathways. PMID:9207104

Computational prediction of over-annotated protein-coding genes in the genome of Agrobacterium tumefaciens strain C58

NASA Astrophysics Data System (ADS)

Yu, Jia-Feng; Sui, Tian-Xiang; Wang, Hong-Mei; Wang, Chun-Ling; Jing, Li; Wang, Ji-Hua

2015-12-01

Agrobacterium tumefaciens strain C58 is a type of pathogen that can cause tumors in some dicotyledonous plants. Ever since the genome of A. tumefaciens strain C58 was sequenced, the quality of annotation of its protein-coding genes has been queried continually, because the annotation varies greatly among different databases. In this paper, the questionable hypothetical genes were re-predicted by integrating the TN curve and Z curve methods. As a result, 30 genes originally annotated as “hypothetical” were discriminated as being non-coding sequences. By testing the re-prediction program 10 times on data sets composed of the function-known genes, the mean accuracy of 99.99% and mean Matthews correlation coefficient value of 0.9999 were obtained. Further sequence analysis and COG analysis showed that the re-annotation results were very reliable. This work can provide an efficient tool and data resources for future studies of A. tumefaciens strain C58. Project supported by the National Natural Science Foundation of China (Grant Nos. 61302186 and 61271378) and the Funding from the State Key Laboratory of Bioelectronics of Southeast University.

Sugar transporter genes of the brown planthopper, Nilaparvata lugens: A facilitated glucose/fructose transporter.

PubMed

Kikuta, Shingo; Kikawada, Takahiro; Hagiwara-Komoda, Yuka; Nakashima, Nobuhiko; Noda, Hiroaki

2010-11-01

The brown planthopper (BPH), Nilaparvata lugens, attacks rice plants and feeds on their phloem sap, which contains large amounts of sugars. The main sugar component of phloem sap is sucrose, a disaccharide composed of glucose and fructose. Sugars appear to be incorporated into the planthopper body by sugar transporters in the midgut. A total of 93 expressed sequence tags (ESTs) for putative sugar transporters were obtained from a BPH EST database, and 18 putative sugar transporter genes (Nlst1-18) were identified. The most abundantly expressed of these genes was Nlst1. This gene has previously been identified in the BPH as the glucose transporter gene NlHT1, which belongs to the major facilitator superfamily. Nlst1, 4, 6, 9, 12, 16, and 18 were highly expressed in the midgut, and Nlst2, 7, 8, 10, 15, 17, and 18 were highly expressed during the embryonic stages. Functional analyses were performed using Xenopus oocytes expressing NlST1 or 6. This showed that NlST6 is a facilitative glucose/fructose transporter that mediates sugar uptake from rice phloem sap in the BPH midgut in a manner similar to NlST1. Copyright © 2010 Elsevier Ltd. All rights reserved.

Identification and Characterization of Multiple Spidroin 1 Genes Encoding Major Ampullate Silk Proteins in Nephila clavipes

PubMed Central

Gaines, William A.; Marcotte, William R.

2010-01-01

Spider dragline silk is primarily composed of proteins called major ampullate spidroins (MaSp) that consist of a large repeat array flanked by non-repetitive N- and C-terminal domains. Until recently, there has been little evidence for more than one gene encoding each of the two major spidroin silk proteins, MaSp1 and MaSp2. Here, we report the deduced N-terminal domain sequences for two distinct MaSp1 genes from Nephila clavipes (MaSp1A and MaSp1B) and for MaSp2. All three MaSp genes are co-expressed in the major ampullate gland. A search of the GenBank database also revealed two distinct MaSp1 C-terminal domain sequences. Sequencing confirmed that both MaSp1 genes are present in all seven Nephila clavipes spiders examined. The presence of nucleotide polymorphisms in these genes confirmed that MaSp1A and MaSp1B are distinct genetic loci and not merely alleles of the same gene. We have experimentally determined the transcription start sites for all three MaSp genes and established preliminary pairing between the two MaSp1 N- and C-terminal domains. Phylogenetic analysis of these new sequences and other published MaSp N- and C-terminal domain sequences illustrated that duplications of MaSp genes may be widespread among spider species. PMID:18828837

DockScreen: A database of in silico biomolecular interactions to support computational toxicology

EPA Science Inventory

We have developed DockScreen, a database of in silico biomolecular interactions designed to enable rational molecular toxicological insight within a computational toxicology framework. This database is composed of chemical/target (receptor and enzyme) binding scores calculated by...

GEM2Net: from gene expression modeling to -omics networks, a new CATdb module to investigate Arabidopsis thaliana genes involved in stress response.

PubMed

Zaag, Rim; Tamby, Jean Philippe; Guichard, Cécile; Tariq, Zakia; Rigaill, Guillem; Delannoy, Etienne; Renou, Jean-Pierre; Balzergue, Sandrine; Mary-Huard, Tristan; Aubourg, Sébastien; Martin-Magniette, Marie-Laure; Brunaud, Véronique

2015-01-01

CATdb (http://urgv.evry.inra.fr/CATdb) is a database providing a public access to a large collection of transcriptomic data, mainly for Arabidopsis but also for other plants. This resource has the rare advantage to contain several thousands of microarray experiments obtained with the same technical protocol and analyzed by the same statistical pipelines. In this paper, we present GEM2Net, a new module of CATdb that takes advantage of this homogeneous dataset to mine co-expression units and decipher Arabidopsis gene functions. GEM2Net explores 387 stress conditions organized into 18 biotic and abiotic stress categories. For each one, a model-based clustering is applied on expression differences to identify clusters of co-expressed genes. To characterize functions associated with these clusters, various resources are analyzed and integrated: Gene Ontology, subcellular localization of proteins, Hormone Families, Transcription Factor Families and a refined stress-related gene list associated to publications. Exploiting protein-protein interactions and transcription factors-targets interactions enables to display gene networks. GEM2Net presents the analysis of the 18 stress categories, in which 17,264 genes are involved and organized within 681 co-expression clusters. The meta-data analyses were stored and organized to compose a dynamic Web resource. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Association between the rs1143634 polymorphism in interleukin-1B and chronic periodontitis: Results from a meta-analysis composed by 54 case/control studies.

PubMed

da Silva, Felipe Rodolfo Pereira; Vasconcelos, Any Carolina Cardoso Guimarães; de Carvalho França, Luiz Felipe; Di Lenardo, David; Nascimento, Hélio Mateus Silva; Vasconcelos, Daniel Fernando Pereira

2018-08-20

Several factors are involved in the periodontitis with host response through cytokines and as well as with influence of polymorphisms in cytokine genes, however the results remained contradictory. This study aimed at evaluating the rs1143634 polymorphism in interleukin-1B gene, a cytokine gene, and the risk of chronic periodontitis with conducting a meta-analysis focusing in ethnicity. A review in literature was performed in several databases to studies published before June 2017. Data extraction was performed by two calibrated investigators and the calculations of the meta-analysis were obtained through Review Manager version 5.2 statistical software with Odds Ratio (OR) calculation and Funnel plot (P < 0.05) to heterogeneity and the Comprehensive Meta-analysis version 3.3.070 to assessment publication bias by Egger's and Begg's tests. In overall, 54 case/control studies composed the meta-analysis. T allele was significantly associated with patients case (OR = 1.35, 95% CI: 1.24, 1.48, P < 0.00001) in the overall analysis. The stratified evaluation showed the rs1143634 polymorphism had significant association with disease in Caucasian, Asian and mixed population was excepted in African ethnicity (P > 0.05). No publication bias was found in allelic evaluation. This meta-analysis in 9376 participants with 54 case/control studies revealed the rs1143634 polymorphism was associated with elevated risk of chronic periodontitis in overall analysis as well as Caucasian and Asian ethnicities and Mixed population. Copyright © 2018 Elsevier B.V. All rights reserved.

Rationale and design of the Duke Electrophysiology Genetic and Genomic Studies (EPGEN) biorepository.

PubMed

Koontz, Jason I; Haithcock, Daniel; Cumbea, Valerie; Waldron, Anthony; Stricker, Kristie; Hughes, Amy; Nilsson, Kent; Sun, Albert; Piccini, Jonathan P; Kraus, William E; Pitt, Geoffrey S; Shah, Svati H; Hranitzky, Patrick

2009-11-01

Disturbances in cardiac rhythm can lead to significant morbidity and mortality. Many arrhythmias are known to have a heritable component, but the degree to which genetic variation contributes to disease risk and morbidity is poorly understood. The EPGEN is a prospective single-center repository that archives DNA, RNA, and protein samples obtained at the time of an electrophysiologic evaluation or intervention. To identify genes and molecular variants that are associated with risk for arrhythmic phenotypes, EPGEN uses unbiased genomic screening; candidate gene analysis; and both unbiased and targeted transcript, protein, and metabolite profiling. To date, EPGEN has successfully enrolled >1,500 subjects. The median age of the study population is 62.9 years; 35% of the subjects are female and 21% are black. To this point, the study population has been composed of patients who had undergone defibrillator (implantable cardioverter-defibrillator or cardiac resynchronization therapy defibrillator) implantation (45%), electrophysiology studies or ablation procedures (35%), and pacemaker implantation or other procedures (20%). The cohort has a high prevalence of comorbidities, including diabetes (33%), hypertension (73%), chronic kidney disease (26%), and peripheral vascular disease (13%). We have established a biorepository and clinical database composed of patients with electrophysiologic diseases. EPGEN will seek to (1) improve risk stratification, (2) elucidate mechanisms of arrhythmogenesis, and (3) identify novel pharmacologic targets for the treatment of heart rhythm disorders.

The complete mitochondrial genome of the Anabas testudineus (Perciformes, Anabantidae) and its comparison with other related fish species.

PubMed

Behera, Bijay Kumar; Baisvar, Vishwamitra Singh; Kumari, Kavita; Rout, Ajaya Kumar; Pakrashi, Sudip; Paria, Prasenjet; Rao, A R; Rai, Anil

2017-03-01

In the present study, the complete mitochondrial genome sequence of Anabas testudineusis reported using PGM sequencer (Ion Torrent, Life Technologies, La Jolla, CA). The complete mitogenome of climbing perch, A. testudineusis obtained by the de novo sequences assembly of genomic reads using the Torrent Mapping Alignment Program (TMAP), which is 16 603 bp in length. The mitogenome of A. testudineus composed of 13 protein- coding genes, two rRNA, and 22 tRNAs. Here, 20 tRNAs genes showed typical clover leaf model, and D-Loop as the control region along with gene order and organization, being closely similar to Osphronemidae and most of other Perciformes fish mitogenomes of NCBI databases. The mitogenome in the present study has 99% similarity to the complete mitogenome sequence of earlier reported A. testudineus. The phylogenetic analysis of Anabantidae depicted that their mitogenomes are closely related to each other. The complete mitogenome sequence of A. testudineus would be helpful in understanding the population genetics, phylogenetics, and evolution of Anabantidae.

HLA-F polymorphisms in a Euro-Brazilian population from Southern Brazil.

PubMed

Manvailer, L F S; Wowk, P F; Mattar, S B; da Siva, J S; da Graça Bicalho, M; Roxo, V M M S

2014-12-01

HLA-F is a non-classical major histocompatibility complex (MHC) gene. It codes class Ib MHC molecules with restricted distribution and less nucleotide variations than MHC class Ia genes. Of the 22 alleles registered on the IMGT database only four alleles encode for proteins that differ in their primary structure. To estimate genotype and allele frequencies, this study targeted on known protein coding regions of the HLA-F gene. Genotyping was performed by Sequence Base Typing (SBT). The sample was composed by 199-unrelated bone marrow donors from the Brazilian Bone Marrow Donor Registry (REDOME), Euro-Brazilians, from Southern Brazil. About 1673 bp were analyzed. The most frequent allele was HLA-F*01:01 (87.19%), followed by HLA-F*01:03 (12.31%), HLA-F*01:02 (0.25%) and HLA-F*01:04 (0.25%). Significant linkage disequilibrium (LD) was verified between HLA-F and HLA classes I and II alleles. This is the first study regarding HLA-F polymorphisms in a Euro-Brazilian population contributing to the Southern Brazilian genetic characterization. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Mutation databases for inherited renal disease: are they complete, accurate, clinically relevant, and freely available?

PubMed

Savige, Judy; Dagher, Hayat; Povey, Sue

2014-07-01

This study examined whether gene-specific DNA variant databases for inherited diseases of the kidney fulfilled the Human Variome Project recommendations of being complete, accurate, clinically relevant and freely available. A recent review identified 60 inherited renal diseases caused by mutations in 132 genes. The disease name, MIM number, gene name, together with "mutation" or "database," were used to identify web-based databases. Fifty-nine diseases (98%) due to mutations in 128 genes had a variant database. Altogether there were 349 databases (a median of 3 per gene, range 0-6), but no gene had two databases with the same number of variants, and 165 (50%) databases included fewer than 10 variants. About half the databases (180, 54%) had been updated in the previous year. Few (77, 23%) were curated by "experts" but these included nine of the 11 with the most variants. Even fewer databases (41, 12%) included clinical features apart from the name of the associated disease. Most (223, 67%) could be accessed without charge, including those for 50 genes (40%) with the maximum number of variants. Future efforts should focus on encouraging experts to collaborate on a single database for each gene affected in inherited renal disease, including both unpublished variants, and clinical phenotypes. © 2014 WILEY PERIODICALS, INC.

Gene-expression signature regulated by the KEAP1-NRF2-CUL3 axis is associated with a poor prognosis in head and neck squamous cell cancer.

PubMed

Namani, Akhileshwar; Matiur Rahaman, Md; Chen, Ming; Tang, Xiuwen

2018-01-06

NRF2 is the key regulator of oxidative stress in normal cells and aberrant expression of the NRF2 pathway due to genetic alterations in the KEAP1 (Kelch-like ECH-associated protein 1)-NRF2 (nuclear factor erythroid 2 like 2)-CUL3 (cullin 3) axis leads to tumorigenesis and drug resistance in many cancers including head and neck squamous cell cancer (HNSCC). The main goal of this study was to identify specific genes regulated by the KEAP1-NRF2-CUL3 axis in HNSCC patients, to assess the prognostic value of this gene signature in different cohorts, and to reveal potential biomarkers. RNA-Seq V2 level 3 data from 279 tumor samples along with 37 adjacent normal samples from patients enrolled in the The Cancer Genome Atlas (TCGA)-HNSCC study were used to identify upregulated genes using two methods (altered KEAP1-NRF2-CUL3 versus normal, and altered KEAP1-NRF2-CUL3 versus wild-type). We then used a new approach to identify the combined gene signature by integrating both datasets and subsequently tested this signature in 4 independent HNSCC datasets to assess its prognostic value. In addition, functional annotation using the DAVID v6.8 database and protein-protein interaction (PPI) analysis using the STRING v10 database were performed on the signature. A signature composed of a subset of 17 genes regulated by the KEAP1-NRF2-CUL3 axis was identified by overlapping both the upregulated genes of altered versus normal (251 genes) and altered versus wild-type (25 genes) datasets. We showed that increased expression was significantly associated with poor survival in 4 independent HNSCC datasets, including the TCGA-HNSCC dataset. Furthermore, Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and PPI analysis revealed that most of the genes in this signature are associated with drug metabolism and glutathione metabolic pathways. Altogether, our study emphasizes the discovery of a gene signature regulated by the KEAP1-NRF2-CUL3 axis which is strongly associated with tumorigenesis and drug resistance in HNSCC. This 17-gene signature provides potential biomarkers and therapeutic targets for HNSCC cases in which the NRF2 pathway is activated.

PIGD: a database for intronless genes in the Poaceae.

PubMed

Yan, Hanwei; Jiang, Cuiping; Li, Xiaoyu; Sheng, Lei; Dong, Qing; Peng, Xiaojian; Li, Qian; Zhao, Yang; Jiang, Haiyang; Cheng, Beijiu

2014-10-01

Intronless genes are a feature of prokaryotes; however, they are widespread and unequally distributed among eukaryotes and represent an important resource to study the evolution of gene architecture. Although many databases on exons and introns exist, there is currently no cohesive database that collects intronless genes in plants into a single database. In this study, we present the Poaceae Intronless Genes Database (PIGD), a user-friendly web interface to explore information on intronless genes from different plants. Five Poaceae species, Sorghum bicolor, Zea mays, Setaria italica, Panicum virgatum and Brachypodium distachyon, are included in the current release of PIGD. Gene annotations and sequence data were collected and integrated from different databases. The primary focus of this study was to provide gene descriptions and gene product records. In addition, functional annotations, subcellular localization prediction and taxonomic distribution are reported. PIGD allows users to readily browse, search and download data. BLAST and comparative analyses are also provided through this online database, which is available at http://pigd.ahau.edu.cn/. PIGD provides a solid platform for the collection, integration and analysis of intronless genes in the Poaceae. As such, this database will be useful for subsequent bio-computational analysis in comparative genomics and evolutionary studies.

Developing expressed sequence tag libraries and the discovery of simple sequence repeat markers for two species of raspberry (Rubus L.).

PubMed

Bushakra, Jill M; Lewers, Kim S; Staton, Margaret E; Zhebentyayeva, Tetyana; Saski, Christopher A

2015-10-26

Due to a relatively high level of codominant inheritance and transferability within and among taxonomic groups, simple sequence repeat (SSR) markers are important elements in comparative mapping and delineation of genomic regions associated with traits of economic importance. Expressed sequence tags (ESTs) are a source of SSRs that can be used to develop markers to facilitate plant breeding and for more basic research across genera and higher plant orders. Leaf and meristem tissue from 'Heritage' red raspberry (Rubus idaeus) and 'Bristol' black raspberry (R. occidentalis) were utilized for RNA extraction. After conversion to cDNA and library construction, ESTs were sequenced, quality verified, assembled and scanned for SSRs.  Primers flanking the SSRs were designed and a subset tested for amplification, polymorphism and transferability across species. ESTs containing SSRs were functionally annotated using the GenBank non-redundant (nr) database and further classified using the gene ontology database. To accelerate development of EST-SSRs in the genus Rubus (Rosaceae), 1149 and 2358 cDNA sequences were generated from red raspberry and black raspberry, respectively. The cDNA sequences were screened using rigorous filtering criteria which resulted in the identification of 121 and 257 SSR loci for red and black raspberry, respectively. Primers were designed from the surrounding sequences resulting in 131 and 288 primer pairs, respectively, as some sequences contained more than one SSR locus. Sequence analysis revealed that the SSR-containing genes span a diversity of functions and share more sequence identity with strawberry genes than with other Rosaceous species. This resource of Rubus-specific, gene-derived markers will facilitate the construction of linkage maps composed of transferable markers for studying and manipulating important traits in this economically important genus.

LCGbase: A Comprehensive Database for Lineage-Based Co-regulated Genes.

PubMed

Wang, Dapeng; Zhang, Yubin; Fan, Zhonghua; Liu, Guiming; Yu, Jun

2012-01-01

Animal genes of different lineages, such as vertebrates and arthropods, are well-organized and blended into dynamic chromosomal structures that represent a primary regulatory mechanism for body development and cellular differentiation. The majority of genes in a genome are actually clustered, which are evolutionarily stable to different extents and biologically meaningful when evaluated among genomes within and across lineages. Until now, many questions concerning gene organization, such as what is the minimal number of genes in a cluster and what is the driving force leading to gene co-regulation, remain to be addressed. Here, we provide a user-friendly database-LCGbase (a comprehensive database for lineage-based co-regulated genes)-hosting information on evolutionary dynamics of gene clustering and ordering within animal kingdoms in two different lineages: vertebrates and arthropods. The database is constructed on a web-based Linux-Apache-MySQL-PHP framework and effective interactive user-inquiry service. Compared to other gene annotation databases with similar purposes, our database has three comprehensible advantages. First, our database is inclusive, including all high-quality genome assemblies of vertebrates and representative arthropod species. Second, it is human-centric since we map all gene clusters from other genomes in an order of lineage-ranks (such as primates, mammals, warm-blooded, and reptiles) onto human genome and start the database from well-defined gene pairs (a minimal cluster where the two adjacent genes are oriented as co-directional, convergent, and divergent pairs) to large gene clusters. Furthermore, users can search for any adjacent genes and their detailed annotations. Third, the database provides flexible parameter definitions, such as the distance of transcription start sites between two adjacent genes, which is extendable to genes that flanking the cluster across species. We also provide useful tools for sequence alignment, gene ontology (GO) annotation, promoter identification, gene expression (co-expression), and evolutionary analysis. This database not only provides a way to define lineage-specific and species-specific gene clusters but also facilitates future studies on gene co-regulation, epigenetic control of gene expression (DNA methylation and histone marks), and chromosomal structures in a context of gene clusters and species evolution. LCGbase is freely available at http://lcgbase.big.ac.cn/LCGbase.

[Establishment of a comprehensive database for laryngeal cancer related genes and the miRNAs].

PubMed

Li, Mengjiao; E, Qimin; Liu, Jialin; Huang, Tingting; Liang, Chuanyu

2015-09-01

By collecting and analyzing the laryngeal cancer related genes and the miRNAs, to build a comprehensive laryngeal cancer-related gene database, which differs from the current biological information database with complex and clumsy structure and focuses on the theme of gene and miRNA, and it could make the research and teaching more convenient and efficient. Based on the B/S architecture, using Apache as a Web server, MySQL as coding language of database design and PHP as coding language of web design, a comprehensive database for laryngeal cancer-related genes was established, providing with the gene tables, protein tables, miRNA tables and clinical information tables of the patients with laryngeal cancer. The established database containsed 207 laryngeal cancer related genes, 243 proteins, 26 miRNAs, and their particular information such as mutations, methylations, diversified expressions, and the empirical references of laryngeal cancer relevant molecules. The database could be accessed and operated via the Internet, by which browsing and retrieval of the information were performed. The database were maintained and updated regularly. The database for laryngeal cancer related genes is resource-integrated and user-friendly, providing a genetic information query tool for the study of laryngeal cancer.

Product Descriptions: Database Software for Science. A MicroSIFT Quarterly Report.

ERIC Educational Resources Information Center

Batey, Anne; And Others

Specific programs and software resources are described in this report on database software for science instruction. Materials are reviewed in the categories of: (1) database management (reviewing AppleWorks, Bank Street School Filer, FileVision, Friendly Filer, MECC DataQuest: The Composer, Scholastic PFS:File, PFS:Report); (2) data files…

Application of the ToxMiner Database: Network Analysis of ...

EPA Pesticide Factsheets

The US EPA ToxCast program is using in vitro HTS (High-Throughput Screening) methods to profile and model bioactivity of environmental chemicals. The main goals of the ToxCast program are to generate predictive signatures of toxicity, and ultimately provide rapid and cost-effective alternatives to animal testing. The chemicals selected for Phase I are composed largely by a diverse set of pesticide active ingredients, which had sufficient supporting in vivo data included as part of their registration process with the EPA. Other miscellaneous chemicals of environmental concern were also included. Application of HTS to environmental toxicants is a novel approach to predictive toxicology and health risk assessment, and differs from what is required for drug efficacy screening in that biochemical interaction of environmental chemicals are sometimes weaker than that seen with drugs and their intended targets. Additionally, the chemical space covered by environmental chemicals is much broader compared to that of pharmaceuticals. The ToxMiner database has been created and added to the EPA’s ACToR (Aggregated Computational Toxicology Resource) chemical database. One purpose of the ToxMiner database is to link biological, metabolic and cellular pathway data to genes and in vitro assay data for the initial subset of chemicals screened in the ToxCast Phase I HTS assays. Also included in ToxMiner is human disease information, which correlates with ToxCast assays that tar

Application of the ToxMiner Database: Network Analysis ...

EPA Pesticide Factsheets

The US EPA ToxCast program is using in vitro HTS (High-Throughput Screening) methods to profile and model bioactivity of environmental chemicals. The main goals of the ToxCast program are to generate predictive signatures of toxicity, and ultimately provide rapid and cost-effective alternatives to animal testing. The chemicals selected for Phase I are composed largely by a diverse set of pesticide active ingredients, which had sufficient supporting in vivo data included as part of their registration process with the EPA. Other miscellaneous chemicals of environmental concern were also included. Application of HTS to environmental toxicants is a novel approach to predictive toxicology and health risk assessment, and differs from what is required for drug efficacy screening in that biochemical interaction of environmental chemicals are sometimes weaker than that seen with drugs and their intended targets. Additionally, the chemical space covered by environmental chemicals is much broader compared to that of pharmaceuticals. The ToxMiner database has been created and added to the EPA’s ACToR (Aggregated Computational Toxicology Resource) chemical database. One purpose of the ToxMiner database is to link biological, metabolic, and cellular pathway data to genes and in vitro assay data for the initial subset of chemicals screened in the ToxCast Phase I HTS assays. Also included in ToxMiner is human disease information, which correlates with ToxCast assays that ta

Genus-specific PCR Primers Targeting Intracellular Parasite Euduboscquella (Dinoflagellata: Syndinea)

NASA Astrophysics Data System (ADS)

Jung, Jae-Ho; Choi, Jung Min; Kim, Young-Ok

2018-03-01

We designed a genus-specific primer pair targeting the intracellular parasite Euduboscquella. To increase target specificity and inhibit untargeted PCR, two nucleotides were added at the 3' end of the reverse primer, one being a complementary nucleotide to the Euduboscquella-specific SNP (single-nucleotide polymorphism) and the other a deliberately mismatched nucleotide. Target specificity of the primer set was verified experimentally using PCR of two Euduboscquella species (positive controls) and 15 related species (negative controls composed of ciliates, diatoms and dinoflagellates), and analytical comparison with SILVA SSU rRNA gene database (release 119) in silico. In addition, we applied the Euduboscquella-specific primer set to four environmental samples previously determined by cytological staining to be either positive or negative for Euduboscquella. As expected, only positive controls and environmental samples known to contain Euduboscquella were successfully amplified by the primer set. An inferred SSU rRNA gene phylogeny placed environmental samples containing aloricate ciliates infected by Euduboscquella in a cluster discrete from Euduboscquella groups a-d previously reported from loricate, tintinnid ciliates.

AccuNet/AP (Associated Press) Multimedia Archive

ERIC Educational Resources Information Center

Young, Terrence E., Jr.

2004-01-01

The AccuNet/AP Multimedia Archive is an electronic library containing the AP's current photos and a selection of pictures from their enormous print and negative library, as well as text and graphic material. It is composed of two photo databases as well as graphics, text, and audio databases. The features of this database are briefly described in…

HRGFish: A database of hypoxia responsive genes in fishes

NASA Astrophysics Data System (ADS)

Rashid, Iliyas; Nagpure, Naresh Sahebrao; Srivastava, Prachi; Kumar, Ravindra; Pathak, Ajey Kumar; Singh, Mahender; Kushwaha, Basdeo

2017-02-01

Several studies have highlighted the changes in the gene expression due to the hypoxia response in fishes, but the systematic organization of the information and the analytical platform for such genes are lacking. In the present study, an attempt was made to develop a database of hypoxia responsive genes in fishes (HRGFish), integrated with analytical tools, using LAMPP technology. Genes reported in hypoxia response for fishes were compiled through literature survey and the database presently covers 818 gene sequences and 35 gene types from 38 fishes. The upstream fragments (3,000 bp), covered in this database, enables to compute CG dinucleotides frequencies, motif finding of the hypoxia response element, identification of CpG island and mapping with the reference promoter of zebrafish. The database also includes functional annotation of genes and provides tools for analyzing sequences and designing primers for selected gene fragments. This may be the first database on the hypoxia response genes in fishes that provides a workbench to the scientific community involved in studying the evolution and ecological adaptation of the fish species in relation to hypoxia.

Prostate cancer-associated gene expression alterations determined from needle biopsies.

PubMed

Qian, David Z; Huang, Chung-Ying; O'Brien, Catherine A; Coleman, Ilsa M; Garzotto, Mark; True, Lawrence D; Higano, Celestia S; Vessella, Robert; Lange, Paul H; Nelson, Peter S; Beer, Tomasz M

2009-05-01

To accurately identify gene expression alterations that differentiate neoplastic from normal prostate epithelium using an approach that avoids contamination by unwanted cellular components and is not compromised by acute gene expression changes associated with tumor devascularization and resulting ischemia. Approximately 3,000 neoplastic and benign prostate epithelial cells were isolated using laser capture microdissection from snap-frozen prostate biopsy specimens provided by 31 patients who subsequently participated in a clinical trial of preoperative chemotherapy. cDNA synthesized from amplified total RNA was hybridized to custom-made microarrays composed of 6,200 clones derived from the Prostate Expression Database. Expression differences for selected genes were verified using quantitative reverse transcription-PCR. Comparative analyses identified 954 transcript alterations associated with cancer (q < 0.01%), including 149 differentially expressed genes with no known functional roles. Gene expression changes associated with ischemia and surgical removal of the prostate gland were absent. Genes up-regulated in prostate cancer were statistically enriched in categories related to cellular metabolism, energy use, signal transduction, and molecular transport. Genes down-regulated in prostate cancers were enriched in categories related to immune response, cellular responses to pathogens, and apoptosis. A heterogeneous pattern of androgen receptor expression changes was noted. In exploratory analyses, androgen receptor down-regulation was associated with a lower probability of cancer relapse after neoadjuvant chemotherapy followed by radical prostatectomy. Assessments of tumor phenotypes based on gene expression for treatment stratification and drug targeting of oncogenic alterations may best be ascertained using biopsy-based analyses where the effects of ischemia do not complicate interpretation.

Identification of Abundantly Expressed Novel and Conserved Genes from the Infective Larval Stage of Toxocara canis by an Expressed Sequence Tag Strategy

PubMed Central

Tetteh, Kevin K. A.; Loukas, Alex; Tripp, Cindy; Maizels, Rick M.

1999-01-01

Larvae of Toxocara canis, a nematode parasite of dogs, infect humans, causing visceral and ocular larva migrans. In noncanid hosts, larvae neither grow nor differentiate but endure in a state of arrested development. Reasoning that parasite protein production is orientated to immune evasion, we undertook a random sequencing project from a larval cDNA library to characterize the most highly expressed transcripts. In all, 266 clones were sequenced, most from both 3′ and 5′ ends, and similarity searches against GenBank protein and dbEST nucleotide databases were conducted. Cluster analyses showed that 128 distinct gene products had been found, all but 3 of which represented newly identified genes. Ninety-five genes were represented by a single clone, but seven transcripts were present at high frequencies, each composing >2% of all clones sequenced. These high-abundance transcripts include a mucin and a C-type lectin, which are both major excretory-secretory antigens released by parasites. Four highly expressed novel gene transcripts, termed ant (abundant novel transcript) genes, were found. Together, these four genes comprised 18% of all cDNA clones isolated, but no similar sequences occur in the Caenorhabditis elegans genome. While the coding regions of the four genes are dissimilar, their 3′ untranslated tracts have significant homology in nucleotide sequence. The discovery of these abundant, parasite-specific genes of newly identified lectins and mucins, as well as a range of conserved and novel proteins, provides defined candidates for future analysis of the molecular basis of immune evasion by T. canis. PMID:10456930

Causal biological network database: a comprehensive platform of causal biological network models focused on the pulmonary and vascular systems

PubMed Central

Boué, Stéphanie; Talikka, Marja; Westra, Jurjen Willem; Hayes, William; Di Fabio, Anselmo; Park, Jennifer; Schlage, Walter K.; Sewer, Alain; Fields, Brett; Ansari, Sam; Martin, Florian; Veljkovic, Emilija; Kenney, Renee; Peitsch, Manuel C.; Hoeng, Julia

2015-01-01

With the wealth of publications and data available, powerful and transparent computational approaches are required to represent measured data and scientific knowledge in a computable and searchable format. We developed a set of biological network models, scripted in the Biological Expression Language, that reflect causal signaling pathways across a wide range of biological processes, including cell fate, cell stress, cell proliferation, inflammation, tissue repair and angiogenesis in the pulmonary and cardiovascular context. This comprehensive collection of networks is now freely available to the scientific community in a centralized web-based repository, the Causal Biological Network database, which is composed of over 120 manually curated and well annotated biological network models and can be accessed at http://causalbionet.com. The website accesses a MongoDB, which stores all versions of the networks as JSON objects and allows users to search for genes, proteins, biological processes, small molecules and keywords in the network descriptions to retrieve biological networks of interest. The content of the networks can be visualized and browsed. Nodes and edges can be filtered and all supporting evidence for the edges can be browsed and is linked to the original articles in PubMed. Moreover, networks may be downloaded for further visualization and evaluation. Database URL: http://causalbionet.com PMID:25887162

An integrated database-pipeline system for studying single nucleotide polymorphisms and diseases.

PubMed

Yang, Jin Ok; Hwang, Sohyun; Oh, Jeongsu; Bhak, Jong; Sohn, Tae-Kwon

2008-12-12

Studies on the relationship between disease and genetic variations such as single nucleotide polymorphisms (SNPs) are important. Genetic variations can cause disease by influencing important biological regulation processes. Despite the needs for analyzing SNP and disease correlation, most existing databases provide information only on functional variants at specific locations on the genome, or deal with only a few genes associated with disease. There is no combined resource to widely support gene-, SNP-, and disease-related information, and to capture relationships among such data. Therefore, we developed an integrated database-pipeline system for studying SNPs and diseases. To implement the pipeline system for the integrated database, we first unified complicated and redundant disease terms and gene names using the Unified Medical Language System (UMLS) for classification and noun modification, and the HUGO Gene Nomenclature Committee (HGNC) and NCBI gene databases. Next, we collected and integrated representative databases for three categories of information. For genes and proteins, we examined the NCBI mRNA, UniProt, UCSC Table Track and MitoDat databases. For genetic variants we used the dbSNP, JSNP, ALFRED, and HGVbase databases. For disease, we employed OMIM, GAD, and HGMD databases. The database-pipeline system provides a disease thesaurus, including genes and SNPs associated with disease. The search results for these categories are available on the web page http://diseasome.kobic.re.kr/, and a genome browser is also available to highlight findings, as well as to permit the convenient review of potentially deleterious SNPs among genes strongly associated with specific diseases and clinical phenotypes. Our system is designed to capture the relationships between SNPs associated with disease and disease-causing genes. The integrated database-pipeline provides a list of candidate genes and SNP markers for evaluation in both epidemiological and molecular biological approaches to diseases-gene association studies. Furthermore, researchers then can decide semi-automatically the data set for association studies while considering the relationships between genetic variation and diseases. The database can also be economical for disease-association studies, as well as to facilitate an understanding of the processes which cause disease. Currently, the database contains 14,674 SNP records and 109,715 gene records associated with human diseases and it is updated at regular intervals.

Genomic Organization, Transcriptomic Analysis, and Functional Characterization of Avian α- and β-Keratins in Diverse Feather Forms

PubMed Central

Fan, Wen-Lang; Yan, Jie; Chen, Chih-Kuan; Lai, Yu-Ting; Wu, Siao-Man; Mao, Chi-Tang; Chen, Jun-Jie; Lu, Mei-Yeh Jade; Ho, Meng-Ru; Widelitz, Randall B.; Chen, Chih-Feng; Chuong, Cheng-Ming; Li, Wen-Hsiung

2014-01-01

Feathers are hallmark avian integument appendages, although they were also present on theropods. They are composed of flexible corneous materials made of α- and β-keratins, but their genomic organization and their functional roles in feathers have not been well studied. First, we made an exhaustive search of α- and β-keratin genes in the new chicken genome assembly (Galgal4). Then, using transcriptomic analysis, we studied α- and β-keratin gene expression patterns in five types of feather epidermis. The expression patterns of β-keratin genes were different in different feather types, whereas those of α-keratin genes were less variable. In addition, we obtained extensive α- and β-keratin mRNA in situ hybridization data, showing that α-keratins and β-keratins are preferentially expressed in different parts of the feather components. Together, our data suggest that feather morphological and structural diversity can largely be attributed to differential combinations of α- and β-keratin genes in different intrafeather regions and/or feather types from different body parts. The expression profiles provide new insights into the evolutionary origin and diversification of feathers. Finally, functional analysis using mutant chicken keratin forms based on those found in the human α-keratin mutation database led to abnormal phenotypes. This demonstrates that the chicken can be a convenient model for studying the molecular biology of human keratin-based diseases. PMID:25152353

Renal Gene Expression Database (RGED): a relational database of gene expression profiles in kidney disease

PubMed Central

Zhang, Qingzhou; Yang, Bo; Chen, Xujiao; Xu, Jing; Mei, Changlin; Mao, Zhiguo

2014-01-01

We present a bioinformatics database named Renal Gene Expression Database (RGED), which contains comprehensive gene expression data sets from renal disease research. The web-based interface of RGED allows users to query the gene expression profiles in various kidney-related samples, including renal cell lines, human kidney tissues and murine model kidneys. Researchers can explore certain gene profiles, the relationships between genes of interests and identify biomarkers or even drug targets in kidney diseases. The aim of this work is to provide a user-friendly utility for the renal disease research community to query expression profiles of genes of their own interest without the requirement of advanced computational skills. Availability and implementation: Website is implemented in PHP, R, MySQL and Nginx and freely available from http://rged.wall-eva.net. Database URL: http://rged.wall-eva.net PMID:25252782

MiRNA-TF-gene network analysis through ranking of biomolecules for multi-informative uterine leiomyoma dataset.

PubMed

Mallik, Saurav; Maulik, Ujjwal

2015-10-01

Gene ranking is an important problem in bioinformatics. Here, we propose a new framework for ranking biomolecules (viz., miRNAs, transcription-factors/TFs and genes) in a multi-informative uterine leiomyoma dataset having both gene expression and methylation data using (statistical) eigenvector centrality based approach. At first, genes that are both differentially expressed and methylated, are identified using Limma statistical test. A network, comprising these genes, corresponding TFs from TRANSFAC and ITFP databases, and targeter miRNAs from miRWalk database, is then built. The biomolecules are then ranked based on eigenvector centrality. Our proposed method provides better average accuracy in hub gene and non-hub gene classifications than other methods. Furthermore, pre-ranked Gene set enrichment analysis is applied on the pathway database as well as GO-term databases of Molecular Signatures Database with providing a pre-ranked gene-list based on different centrality values for comparing among the ranking methods. Finally, top novel potential gene-markers for the uterine leiomyoma are provided. Copyright © 2015 Elsevier Inc. All rights reserved.

BGDB: a database of bivalent genes.

PubMed

Li, Qingyan; Lian, Shuabin; Dai, Zhiming; Xiang, Qian; Dai, Xianhua

2013-01-01

Bivalent gene is a gene marked with both H3K4me3 and H3K27me3 epigenetic modification in the same area, and is proposed to play a pivotal role related to pluripotency in embryonic stem (ES) cells. Identification of these bivalent genes and understanding their functions are important for further research of lineage specification and embryo development. So far, lots of genome-wide histone modification data were generated in mouse and human ES cells. These valuable data make it possible to identify bivalent genes, but no comprehensive data repositories or analysis tools are available for bivalent genes currently. In this work, we develop BGDB, the database of bivalent genes. The database contains 6897 bivalent genes in human and mouse ES cells, which are manually collected from scientific literature. Each entry contains curated information, including genomic context, sequences, gene ontology and other relevant information. The web services of BGDB database were implemented with PHP + MySQL + JavaScript, and provide diverse query functions. Database URL: http://dailab.sysu.edu.cn/bgdb/

Using the TIGR gene index databases for biological discovery.

PubMed

Lee, Yuandan; Quackenbush, John

2003-11-01

The TIGR Gene Index web pages provide access to analyses of ESTs and gene sequences for nearly 60 species, as well as a number of resources derived from these. Each species-specific database is presented using a common format with a homepage. A variety of methods exist that allow users to search each species-specific database. Methods implemented currently include nucleotide or protein sequence queries using WU-BLAST, text-based searches using various sequence identifiers, searches by gene, tissue and library name, and searches using functional classes through Gene Ontology assignments. This protocol provides guidance for using the Gene Index Databases to extract information.

The "GeneTrustee": a universal identification system that ensures privacy and confidentiality for human genetic databases.

PubMed

Burnett, Leslie; Barlow-Stewart, Kris; Proos, Anné L; Aizenberg, Harry

2003-05-01

This article describes a generic model for access to samples and information in human genetic databases. The model utilises a "GeneTrustee", a third-party intermediary independent of the subjects and of the investigators or database custodians. The GeneTrustee model has been implemented successfully in various community genetics screening programs and has facilitated research access to genetic databases while protecting the privacy and confidentiality of research subjects. The GeneTrustee model could also be applied to various types of non-conventional genetic databases, including neonatal screening Guthrie card collections, and to forensic DNA samples.

Integration of Information Retrieval and Database Management Systems.

ERIC Educational Resources Information Center

Deogun, Jitender S.; Raghavan, Vijay V.

1988-01-01

Discusses the motivation for integrating information retrieval and database management systems, and proposes a probabilistic retrieval model in which records in a file may be composed of attributes (formatted data items) and descriptors (content indicators). The details and resolutions of difficulties involved in integrating such systems are…

Liverome: a curated database of liver cancer-related gene signatures with self-contained context information.

PubMed

Lee, Langho; Wang, Kai; Li, Gang; Xie, Zhi; Wang, Yuli; Xu, Jiangchun; Sun, Shaoxian; Pocalyko, David; Bhak, Jong; Kim, Chulhong; Lee, Kee-Ho; Jang, Ye Jin; Yeom, Young Il; Yoo, Hyang-Sook; Hwang, Seungwoo

2011-11-30

Hepatocellular carcinoma (HCC) is the fifth most common cancer worldwide. A number of molecular profiling studies have investigated the changes in gene and protein expression that are associated with various clinicopathological characteristics of HCC and generated a wealth of scattered information, usually in the form of gene signature tables. A database of the published HCC gene signatures would be useful to liver cancer researchers seeking to retrieve existing differential expression information on a candidate gene and to make comparisons between signatures for prioritization of common genes. A challenge in constructing such database is that a direct import of the signatures as appeared in articles would lead to a loss or ambiguity of their context information that is essential for a correct biological interpretation of a gene's expression change. This challenge arises because designation of compared sample groups is most often abbreviated, ad hoc, or even missing from published signature tables. Without manual curation, the context information becomes lost, leading to uninformative database contents. Although several databases of gene signatures are available, none of them contains informative form of signatures nor shows comprehensive coverage on liver cancer. Thus we constructed Liverome, a curated database of liver cancer-related gene signatures with self-contained context information. Liverome's data coverage is more than three times larger than any other signature database, consisting of 143 signatures taken from 98 HCC studies, mostly microarray and proteome, and involving 6,927 genes. The signatures were post-processed into an informative and uniform representation and annotated with an itemized summary so that all context information is unambiguously self-contained within the database. The signatures were further informatively named and meaningfully organized according to ten functional categories for guided browsing. Its web interface enables a straightforward retrieval of known differential expression information on a query gene and a comparison of signatures to prioritize common genes. The utility of Liverome-collected data is shown by case studies in which useful biological insights on HCC are produced. Liverome database provides a comprehensive collection of well-curated HCC gene signatures and straightforward interfaces for gene search and signature comparison as well. Liverome is available at http://liverome.kobic.re.kr.

A literature search tool for intelligent extraction of disease-associated genes.

PubMed

Jung, Jae-Yoon; DeLuca, Todd F; Nelson, Tristan H; Wall, Dennis P

2014-01-01

To extract disorder-associated genes from the scientific literature in PubMed with greater sensitivity for literature-based support than existing methods. We developed a PubMed query to retrieve disorder-related, original research articles. Then we applied a rule-based text-mining algorithm with keyword matching to extract target disorders, genes with significant results, and the type of study described by the article. We compared our resulting candidate disorder genes and supporting references with existing databases. We demonstrated that our candidate gene set covers nearly all genes in manually curated databases, and that the references supporting the disorder-gene link are more extensive and accurate than other general purpose gene-to-disorder association databases. We implemented a novel publication search tool to find target articles, specifically focused on links between disorders and genotypes. Through comparison against gold-standard manually updated gene-disorder databases and comparison with automated databases of similar functionality we show that our tool can search through the entirety of PubMed to extract the main gene findings for human diseases rapidly and accurately.

Gene annotation from scientific literature using mappings between keyword systems.

PubMed

Pérez, Antonio J; Perez-Iratxeta, Carolina; Bork, Peer; Thode, Guillermo; Andrade, Miguel A

2004-09-01

The description of genes in databases by keywords helps the non-specialist to quickly grasp the properties of a gene and increases the efficiency of computational tools that are applied to gene data (e.g. searching a gene database for sequences related to a particular biological process). However, the association of keywords to genes or protein sequences is a difficult process that ultimately implies examination of the literature related to a gene. To support this task, we present a procedure to derive keywords from the set of scientific abstracts related to a gene. Our system is based on the automated extraction of mappings between related terms from different databases using a model of fuzzy associations that can be applied with all generality to any pair of linked databases. We tested the system by annotating genes of the SWISS-PROT database with keywords derived from the abstracts linked to their entries (stored in the MEDLINE database of scientific references). The performance of the annotation procedure was much better for SWISS-PROT keywords (recall of 47%, precision of 68%) than for Gene Ontology terms (recall of 8%, precision of 67%). The algorithm can be publicly accessed and used for the annotation of sequences through a web server at http://www.bork.embl.de/kat

A method for automatically extracting infectious disease-related primers and probes from the literature

PubMed Central

2010-01-01

Background Primer and probe sequences are the main components of nucleic acid-based detection systems. Biologists use primers and probes for different tasks, some related to the diagnosis and prescription of infectious diseases. The biological literature is the main information source for empirically validated primer and probe sequences. Therefore, it is becoming increasingly important for researchers to navigate this important information. In this paper, we present a four-phase method for extracting and annotating primer/probe sequences from the literature. These phases are: (1) convert each document into a tree of paper sections, (2) detect the candidate sequences using a set of finite state machine-based recognizers, (3) refine problem sequences using a rule-based expert system, and (4) annotate the extracted sequences with their related organism/gene information. Results We tested our approach using a test set composed of 297 manuscripts. The extracted sequences and their organism/gene annotations were manually evaluated by a panel of molecular biologists. The results of the evaluation show that our approach is suitable for automatically extracting DNA sequences, achieving precision/recall rates of 97.98% and 95.77%, respectively. In addition, 76.66% of the detected sequences were correctly annotated with their organism name. The system also provided correct gene-related information for 46.18% of the sequences assigned a correct organism name. Conclusions We believe that the proposed method can facilitate routine tasks for biomedical researchers using molecular methods to diagnose and prescribe different infectious diseases. In addition, the proposed method can be expanded to detect and extract other biological sequences from the literature. The extracted information can also be used to readily update available primer/probe databases or to create new databases from scratch. PMID:20682041

SGDB: a database of synthetic genes re-designed for optimizing protein over-expression.

PubMed

Wu, Gang; Zheng, Yuanpu; Qureshi, Imran; Zin, Htar Thant; Beck, Tyler; Bulka, Blazej; Freeland, Stephen J

2007-01-01

Here we present the Synthetic Gene Database (SGDB): a relational database that houses sequences and associated experimental information on synthetic (artificially engineered) genes from all peer-reviewed studies published to date. At present, the database comprises information from more than 200 published experiments. This resource not only provides reference material to guide experimentalists in designing new genes that improve protein expression, but also offers a dataset for analysis by bioinformaticians who seek to test ideas regarding the underlying factors that influence gene expression. The SGDB was built under MySQL database management system. We also offer an XML schema for standardized data description of synthetic genes. Users can access the database at http://www.evolvingcode.net/codon/sgdb/index.php, or batch downloads all information through XML files. Moreover, users may visually compare the coding sequences of a synthetic gene and its natural counterpart with an integrated web tool at http://www.evolvingcode.net/codon/sgdb/aligner.php, and discuss questions, findings and related information on an associated e-forum at http://www.evolvingcode.net/forum/viewforum.php?f=27.

SASD: the Synthetic Alternative Splicing Database for identifying novel isoform from proteomics

PubMed Central

2013-01-01

Background Alternative splicing is an important and widespread mechanism for generating protein diversity and regulating protein expression. High-throughput identification and analysis of alternative splicing in the protein level has more advantages than in the mRNA level. The combination of alternative splicing database and tandem mass spectrometry provides a powerful technique for identification, analysis and characterization of potential novel alternative splicing protein isoforms from proteomics. Therefore, based on the peptidomic database of human protein isoforms for proteomics experiments, our objective is to design a new alternative splicing database to 1) provide more coverage of genes, transcripts and alternative splicing, 2) exclusively focus on the alternative splicing, and 3) perform context-specific alternative splicing analysis. Results We used a three-step pipeline to create a synthetic alternative splicing database (SASD) to identify novel alternative splicing isoforms and interpret them at the context of pathway, disease, drug and organ specificity or custom gene set with maximum coverage and exclusive focus on alternative splicing. First, we extracted information on gene structures of all genes in the Ensembl Genes 71 database and incorporated the Integrated Pathway Analysis Database. Then, we compiled artificial splicing transcripts. Lastly, we translated the artificial transcripts into alternative splicing peptides. The SASD is a comprehensive database containing 56,630 genes (Ensembl gene IDs), 95,260 transcripts (Ensembl transcript IDs), and 11,919,779 Alternative Splicing peptides, and also covering about 1,956 pathways, 6,704 diseases, 5,615 drugs, and 52 organs. The database has a web-based user interface that allows users to search, display and download a single gene/transcript/protein, custom gene set, pathway, disease, drug, organ related alternative splicing. Moreover, the quality of the database was validated with comparison to other known databases and two case studies: 1) in liver cancer and 2) in breast cancer. Conclusions The SASD provides the scientific community with an efficient means to identify, analyze, and characterize novel Exon Skipping and Intron Retention protein isoforms from mass spectrometry and interpret them at the context of pathway, disease, drug and organ specificity or custom gene set with maximum coverage and exclusive focus on alternative splicing. PMID:24267658

BGDB: a database of bivalent genes

PubMed Central

Li, Qingyan; Lian, Shuabin; Dai, Zhiming; Xiang, Qian; Dai, Xianhua

2013-01-01

Bivalent gene is a gene marked with both H3K4me3 and H3K27me3 epigenetic modification in the same area, and is proposed to play a pivotal role related to pluripotency in embryonic stem (ES) cells. Identification of these bivalent genes and understanding their functions are important for further research of lineage specification and embryo development. So far, lots of genome-wide histone modification data were generated in mouse and human ES cells. These valuable data make it possible to identify bivalent genes, but no comprehensive data repositories or analysis tools are available for bivalent genes currently. In this work, we develop BGDB, the database of bivalent genes. The database contains 6897 bivalent genes in human and mouse ES cells, which are manually collected from scientific literature. Each entry contains curated information, including genomic context, sequences, gene ontology and other relevant information. The web services of BGDB database were implemented with PHP + MySQL + JavaScript, and provide diverse query functions. Database URL: http://dailab.sysu.edu.cn/bgdb/ PMID:23894186

Characterization of multiple enolase genes from Trichomonas vaginalis. Potential novel targets for drug and vaccine design.

PubMed

Mirasol-Meléndez, Elibeth; Brieba, Luis G; Díaz-Quezada, Corina; López-Hidalgo, Marisol; Figueroa-Angulo, Elisa E; Ávila-González, Leticia; Arroyo-Verástegui, Rossana; Benítez-Cardoza, Claudia G

2018-08-01

Trichomonas vaginalis is the protist parasite that causes the most common, non-viral sexually transmitted infection called trichomonosis. Enolase is a moonlighting protein that apart from its canonical function as a glycolytic enzyme, serves as a plasminogen receptor on the cell surface of T. vaginalis and, in consequence, it has been stablished as a virulence factor in this parasite. In the Trichomonas vaginalis sequence database there are nine genes annotated as enolase. In this work, we analyzed these genes as well as their products. We found that seven out of nine genes might indeed perform enolase activity, whereas two genes might have been equivocally identified, or they might be pseudogenes. Furthermore, a combination of qRT-PCR and proteomic approaches was used to assess, for the first time, the expression of these genes in the highly virulent mexican isolate of T. vaginalis CNCD-147 at different iron concentrations. We could find peptides corresponding to enolases encoded by genes TVAG_464170, TVAG_043500 and TVAG_329460. Moreover, we identified two distinctive characteristics within enolases from Trichomonas vaginalis. One of them corresponds to three key substitutions within one of the loops of the active site, compared to host enolase. The other, is a unique N-terminal motif, composed of 15 to 18 residues, on all the potentially active enolases, whose function still has to be stablished. Both differential features merit further studies as potential drug and vaccine targets as well as diagnosis markers. These findings offer new possibilities to fight trichomonosis. Copyright © 2018 Elsevier B.V. All rights reserved.

Evolutionary Genomics and Adaptive Evolution of the Hedgehog Gene Family (Shh, Ihh and Dhh) in Vertebrates

PubMed Central

Pereira, Joana; Johnson, Warren E.; O’Brien, Stephen J.; Jarvis, Erich D.; Zhang, Guojie; Gilbert, M. Thomas P.; Vasconcelos, Vitor; Antunes, Agostinho

2014-01-01

The Hedgehog (Hh) gene family codes for a class of secreted proteins composed of two active domains that act as signalling molecules during embryo development, namely for the development of the nervous and skeletal systems and the formation of the testis cord. While only one Hh gene is found typically in invertebrate genomes, most vertebrates species have three (Sonic hedgehog – Shh; Indian hedgehog – Ihh; and Desert hedgehog – Dhh), each with different expression patterns and functions, which likely helped promote the increasing complexity of vertebrates and their successful diversification. In this study, we used comparative genomic and adaptive evolutionary analyses to characterize the evolution of the Hh genes in vertebrates following the two major whole genome duplication (WGD) events. To overcome the lack of Hh-coding sequences on avian publicly available databases, we used an extensive dataset of 45 avian and three non-avian reptilian genomes to show that birds have all three Hh paralogs. We find suggestions that following the WGD events, vertebrate Hh paralogous genes evolved independently within similar linkage groups and under different evolutionary rates, especially within the catalytic domain. The structural regions around the ion-binding site were identified to be under positive selection in the signaling domain. These findings contrast with those observed in invertebrates, where different lineages that experienced gene duplication retained similar selective constraints in the Hh orthologs. Our results provide new insights on the evolutionary history of the Hh gene family, the functional roles of these paralogs in vertebrate species, and on the location of mutational hotspots. PMID:25549322

A Genome-Wide Survey of the Microsatellite Content of the Globe Artichoke Genome and the Development of a Web-Based Database

PubMed Central

Portis, Ezio; Portis, Flavio; Valente, Luisa; Moglia, Andrea; Barchi, Lorenzo; Lanteri, Sergio; Acquadro, Alberto

2016-01-01

The recently acquired genome sequence of globe artichoke (Cynara cardunculus var. scolymus) has been used to catalog the genome’s content of simple sequence repeat (SSR) markers. More than 177,000 perfect SSRs were revealed, equivalent to an overall density across the genome of 244.5 SSRs/Mbp, but some 224,000 imperfect SSRs were also identified. About 21% of these SSRs were complex (two stretches of repeats separated by <100 nt). Some 73% of the SSRs were composed of dinucleotide motifs. The SSRs were categorized for the numbers of repeats present, their overall length and were allocated to their linkage group. A total of 4,761 perfect and 6,583 imperfect SSRs were present in 3,781 genes (14.11% of the total), corresponding to an overall density across the gene space of 32,5 and 44,9 SSRs/Mbp for perfect and imperfect motifs, respectively. A putative function has been assigned, using the gene ontology approach, to the set of genes harboring at least one SSR. The same search parameters were applied to reveal the SSR content of 14 other plant species for which genome sequence is available. Certain species-specific SSR motifs were identified, along with a hexa-nucleotide motif shared only with the other two Compositae species (sunflower (Helianthus annuus) and horseweed (Conyza canadensis)) included in the study. Finally, a database, called “Cynara cardunculus MicroSatellite DataBase” (CyMSatDB) was developed to provide a searchable interface to the SSR data. CyMSatDB facilitates the retrieval of SSR markers, as well as suggested forward and reverse primers, on the basis of genomic location, genomic vs genic context, perfect vs imperfect repeat, motif type, motif sequence and repeat number. The SSR markers were validated via an in silico based PCR analysis adopting two available assembled transcriptomes, derived from contrasting globe artichoke accessions, as templates. PMID:27648830

AgeFactDB--the JenAge Ageing Factor Database--towards data integration in ageing research.

PubMed

Hühne, Rolf; Thalheim, Torsten; Sühnel, Jürgen

2014-01-01

AgeFactDB (http://agefactdb.jenage.de) is a database aimed at the collection and integration of ageing phenotype data including lifespan information. Ageing factors are considered to be genes, chemical compounds or other factors such as dietary restriction, whose action results in a changed lifespan or another ageing phenotype. Any information related to the effects of ageing factors is called an observation and is presented on observation pages. To provide concise access to the complete information for a particular ageing factor, corresponding observations are also summarized on ageing factor pages. In a first step, ageing-related data were primarily taken from existing databases such as the Ageing Gene Database--GenAge, the Lifespan Observations Database and the Dietary Restriction Gene Database--GenDR. In addition, we have started to include new ageing-related information. Based on homology data taken from the HomoloGene Database, AgeFactDB also provides observation and ageing factor pages of genes that are homologous to known ageing-related genes. These homologues are considered as candidate or putative ageing-related genes. AgeFactDB offers a variety of search and browse options, and also allows the download of ageing factor or observation lists in TSV, CSV and XML formats.

MIrExpress: A Database for Gene Coexpression Correlation in Immune Cells Based on Mutual Information and Pearson Correlation

PubMed Central

Wang, Luman; Mo, Qiaochu; Wang, Jianxin

2015-01-01

Most current gene coexpression databases support the analysis for linear correlation of gene pairs, but not nonlinear correlation of them, which hinders precisely evaluating the gene-gene coexpression strengths. Here, we report a new database, MIrExpress, which takes advantage of the information theory, as well as the Pearson linear correlation method, to measure the linear correlation, nonlinear correlation, and their hybrid of cell-specific gene coexpressions in immune cells. For a given gene pair or probe set pair input by web users, both mutual information (MI) and Pearson correlation coefficient (r) are calculated, and several corresponding values are reported to reflect their coexpression correlation nature, including MI and r values, their respective rank orderings, their rank comparison, and their hybrid correlation value. Furthermore, for a given gene, the top 10 most relevant genes to it are displayed with the MI, r, or their hybrid perspective, respectively. Currently, the database totally includes 16 human cell groups, involving 20,283 human genes. The expression data and the calculated correlation results from the database are interactively accessible on the web page and can be implemented for other related applications and researches. PMID:26881263

MIrExpress: A Database for Gene Coexpression Correlation in Immune Cells Based on Mutual Information and Pearson Correlation.

PubMed

Wang, Luman; Mo, Qiaochu; Wang, Jianxin

2015-01-01

Most current gene coexpression databases support the analysis for linear correlation of gene pairs, but not nonlinear correlation of them, which hinders precisely evaluating the gene-gene coexpression strengths. Here, we report a new database, MIrExpress, which takes advantage of the information theory, as well as the Pearson linear correlation method, to measure the linear correlation, nonlinear correlation, and their hybrid of cell-specific gene coexpressions in immune cells. For a given gene pair or probe set pair input by web users, both mutual information (MI) and Pearson correlation coefficient (r) are calculated, and several corresponding values are reported to reflect their coexpression correlation nature, including MI and r values, their respective rank orderings, their rank comparison, and their hybrid correlation value. Furthermore, for a given gene, the top 10 most relevant genes to it are displayed with the MI, r, or their hybrid perspective, respectively. Currently, the database totally includes 16 human cell groups, involving 20,283 human genes. The expression data and the calculated correlation results from the database are interactively accessible on the web page and can be implemented for other related applications and researches.

Drug-Path: a database for drug-induced pathways

PubMed Central

Zeng, Hui; Cui, Qinghua

2015-01-01

Some databases for drug-associated pathways have been built and are publicly available. However, the pathways curated in most of these databases are drug-action or drug-metabolism pathways. In recent years, high-throughput technologies such as microarray and RNA-sequencing have produced lots of drug-induced gene expression profiles. Interestingly, drug-induced gene expression profile frequently show distinct patterns, indicating that drugs normally induce the activation or repression of distinct pathways. Therefore, these pathways contribute to study the mechanisms of drugs and drug-repurposing. Here, we present Drug-Path, a database of drug-induced pathways, which was generated by KEGG pathway enrichment analysis for drug-induced upregulated genes and downregulated genes based on drug-induced gene expression datasets in Connectivity Map. Drug-Path provides user-friendly interfaces to retrieve, visualize and download the drug-induced pathway data in the database. In addition, the genes deregulated by a given drug are highlighted in the pathways. All data were organized using SQLite. The web site was implemented using Django, a Python web framework. Finally, we believe that this database will be useful for related researches. Database URL: http://www.cuilab.cn/drugpath PMID:26130661

Novel LOVD databases for hereditary breast cancer and colorectal cancer genes in the Chinese population.

PubMed

Pan, Min; Cong, Peikuan; Wang, Yue; Lin, Changsong; Yuan, Ying; Dong, Jian; Banerjee, Santasree; Zhang, Tao; Chen, Yanling; Zhang, Ting; Chen, Mingqing; Hu, Peter; Zheng, Shu; Zhang, Jin; Qi, Ming

2011-12-01

The Human Variome Project (HVP) is an international consortium of clinicians, geneticists, and researchers from over 30 countries, aiming to facilitate the establishment and maintenance of standards, systems, and infrastructure for the worldwide collection and sharing of all genetic variations effecting human disease. The HVP-China Node will build new and supplement existing databases of genetic diseases. As the first effort, we have created a novel variant database of BRCA1 and BRCA2, mismatch repair genes (MMR), and APC genes for breast cancer, Lynch syndrome, and familial adenomatous polyposis (FAP), respectively, in the Chinese population using the Leiden Open Variation Database (LOVD) format. We searched PubMed and some Chinese search engines to collect all the variants of these genes in the Chinese population that have already been detected and reported. There are some differences in the gene variants between the Chinese population and that of other ethnicities. The database is available online at http://www.genomed.org/LOVD/. Our database will appear to users who survey other LOVD databases (e.g., by Google search, or by NCBI GeneTests search). Remote submissions are accepted, and the information is updated monthly. © 2011 Wiley Periodicals, Inc.

The GermOnline cross-species systems browser provides comprehensive information on genes and gene products relevant for sexual reproduction.

PubMed

Gattiker, Alexandre; Niederhauser-Wiederkehr, Christa; Moore, James; Hermida, Leandro; Primig, Michael

2007-01-01

We report a novel release of the GermOnline knowledgebase covering genes relevant for the cell cycle, gametogenesis and fertility. GermOnline was extended into a cross-species systems browser including information on DNA sequence annotation, gene expression and the function of gene products. The database covers eight model organisms and Homo sapiens, for which complete genome annotation data are available. The database is now built around a sophisticated genome browser (Ensembl), our own microarray information management and annotation system (MIMAS) used to extensively describe experimental data obtained with high-density oligonucleotide microarrays (GeneChips) and a comprehensive system for online editing of database entries (MediaWiki). The RNA data include results from classical microarrays as well as tiling arrays that yield information on RNA expression levels, transcript start sites and lengths as well as exon composition. Members of the research community are solicited to help GermOnline curators keep database entries on genes and gene products complete and accurate. The database is accessible at http://www.germonline.org/.

DynGO: a tool for visualizing and mining of Gene Ontology and its associations

PubMed Central

Liu, Hongfang; Hu, Zhang-Zhi; Wu, Cathy H

2005-01-01

Background A large volume of data and information about genes and gene products has been stored in various molecular biology databases. A major challenge for knowledge discovery using these databases is to identify related genes and gene products in disparate databases. The development of Gene Ontology (GO) as a common vocabulary for annotation allows integrated queries across multiple databases and identification of semantically related genes and gene products (i.e., genes and gene products that have similar GO annotations). Meanwhile, dozens of tools have been developed for browsing, mining or editing GO terms, their hierarchical relationships, or their "associated" genes and gene products (i.e., genes and gene products annotated with GO terms). Tools that allow users to directly search and inspect relations among all GO terms and their associated genes and gene products from multiple databases are needed. Results We present a standalone package called DynGO, which provides several advanced functionalities in addition to the standard browsing capability of the official GO browsing tool (AmiGO). DynGO allows users to conduct batch retrieval of GO annotations for a list of genes and gene products, and semantic retrieval of genes and gene products sharing similar GO annotations. The result are shown in an association tree organized according to GO hierarchies and supported with many dynamic display options such as sorting tree nodes or changing orientation of the tree. For GO curators and frequent GO users, DynGO provides fast and convenient access to GO annotation data. DynGO is generally applicable to any data set where the records are annotated with GO terms, as illustrated by two examples. Conclusion We have presented a standalone package DynGO that provides functionalities to search and browse GO and its association databases as well as several additional functions such as batch retrieval and semantic retrieval. The complete documentation and software are freely available for download from the website . PMID:16091147

Renal Gene Expression Database (RGED): a relational database of gene expression profiles in kidney disease.

PubMed

Zhang, Qingzhou; Yang, Bo; Chen, Xujiao; Xu, Jing; Mei, Changlin; Mao, Zhiguo

2014-01-01

We present a bioinformatics database named Renal Gene Expression Database (RGED), which contains comprehensive gene expression data sets from renal disease research. The web-based interface of RGED allows users to query the gene expression profiles in various kidney-related samples, including renal cell lines, human kidney tissues and murine model kidneys. Researchers can explore certain gene profiles, the relationships between genes of interests and identify biomarkers or even drug targets in kidney diseases. The aim of this work is to provide a user-friendly utility for the renal disease research community to query expression profiles of genes of their own interest without the requirement of advanced computational skills. Website is implemented in PHP, R, MySQL and Nginx and freely available from http://rged.wall-eva.net. http://rged.wall-eva.net. © The Author(s) 2014. Published by Oxford University Press.

Microarray analysis of genes associated with cell surface NIS protein levels in breast cancer.

PubMed

Beyer, Sasha J; Zhang, Xiaoli; Jimenez, Rafael E; Lee, Mei-Ling T; Richardson, Andrea L; Huang, Kun; Jhiang, Sissy M

2011-10-11

Na+/I- symporter (NIS)-mediated iodide uptake allows radioiodine therapy for thyroid cancer. NIS is also expressed in breast tumors, raising potential for radionuclide therapy of breast cancer. However, NIS expression in most breast cancers is low and may not be sufficient for radionuclide therapy. We aimed to identify biomarkers associated with NIS expression such that mechanisms underlying NIS modulation in human breast tumors may be elucidated. Published oligonucleotide microarray data within the National Center for Biotechnology Information Gene Expression Omnibus database were analyzed to identify gene expression tightly correlated with NIS mRNA level among human breast tumors. NIS immunostaining was performed in a tissue microarray composed of 28 human breast tumors which had corresponding oligonucleotide microarray data available for each tumor such that gene expression associated with cell surface NIS protein level could be identified. NIS mRNA levels do not vary among breast tumors or when compared to normal breast tissues when detected by Affymetrix oligonucleotide microarray platforms. Cell surface NIS protein levels are much more variable than their corresponding NIS mRNA levels. Despite a limited number of breast tumors examined, our analysis identified cysteinyl-tRNA synthetase as a biomarker that is highly associated with cell surface NIS protein levels in the ER-positive breast cancer subtype. Further investigation on genes associated with cell surface NIS protein levels within each breast cancer molecular subtype may lead to novel targets for selectively increasing NIS expression/function in a subset of breast cancers patients.

Causal biological network database: a comprehensive platform of causal biological network models focused on the pulmonary and vascular systems.

PubMed

Boué, Stéphanie; Talikka, Marja; Westra, Jurjen Willem; Hayes, William; Di Fabio, Anselmo; Park, Jennifer; Schlage, Walter K; Sewer, Alain; Fields, Brett; Ansari, Sam; Martin, Florian; Veljkovic, Emilija; Kenney, Renee; Peitsch, Manuel C; Hoeng, Julia

2015-01-01

With the wealth of publications and data available, powerful and transparent computational approaches are required to represent measured data and scientific knowledge in a computable and searchable format. We developed a set of biological network models, scripted in the Biological Expression Language, that reflect causal signaling pathways across a wide range of biological processes, including cell fate, cell stress, cell proliferation, inflammation, tissue repair and angiogenesis in the pulmonary and cardiovascular context. This comprehensive collection of networks is now freely available to the scientific community in a centralized web-based repository, the Causal Biological Network database, which is composed of over 120 manually curated and well annotated biological network models and can be accessed at http://causalbionet.com. The website accesses a MongoDB, which stores all versions of the networks as JSON objects and allows users to search for genes, proteins, biological processes, small molecules and keywords in the network descriptions to retrieve biological networks of interest. The content of the networks can be visualized and browsed. Nodes and edges can be filtered and all supporting evidence for the edges can be browsed and is linked to the original articles in PubMed. Moreover, networks may be downloaded for further visualization and evaluation. Database URL: http://causalbionet.com © The Author(s) 2015. Published by Oxford University Press.

SoyFN: a knowledge database of soybean functional networks.

PubMed

Xu, Yungang; Guo, Maozu; Liu, Xiaoyan; Wang, Chunyu; Liu, Yang

2014-01-01

Many databases for soybean genomic analysis have been built and made publicly available, but few of them contain knowledge specifically targeting the omics-level gene-gene, gene-microRNA (miRNA) and miRNA-miRNA interactions. Here, we present SoyFN, a knowledge database of soybean functional gene networks and miRNA functional networks. SoyFN provides user-friendly interfaces to retrieve, visualize, analyze and download the functional networks of soybean genes and miRNAs. In addition, it incorporates much information about KEGG pathways, gene ontology annotations and 3'-UTR sequences as well as many useful tools including SoySearch, ID mapping, Genome Browser, eFP Browser and promoter motif scan. SoyFN is a schema-free database that can be accessed as a Web service from any modern programming language using a simple Hypertext Transfer Protocol call. The Web site is implemented in Java, JavaScript, PHP, HTML and Apache, with all major browsers supported. We anticipate that this database will be useful for members of research communities both in soybean experimental science and bioinformatics. Database URL: http://nclab.hit.edu.cn/SoyFN.

Metabolic Pathway Assignment of Plant Genes based on Phylogenetic Profiling–A Feasibility Study

PubMed Central

Weißenborn, Sandra; Walther, Dirk

2017-01-01

Despite many developed experimental and computational approaches, functional gene annotation remains challenging. With the rapidly growing number of sequenced genomes, the concept of phylogenetic profiling, which predicts functional links between genes that share a common co-occurrence pattern across different genomes, has gained renewed attention as it promises to annotate gene functions based on presence/absence calls alone. We applied phylogenetic profiling to the problem of metabolic pathway assignments of plant genes with a particular focus on secondary metabolism pathways. We determined phylogenetic profiles for 40,960 metabolic pathway enzyme genes with assigned EC numbers from 24 plant species based on sequence and pathway annotation data from KEGG and Ensembl Plants. For gene sequence family assignments, needed to determine the presence or absence of particular gene functions in the given plant species, we included data of all 39 species available at the Ensembl Plants database and established gene families based on pairwise sequence identities and annotation information. Aside from performing profiling comparisons, we used machine learning approaches to predict pathway associations from phylogenetic profiles alone. Selected metabolic pathways were indeed found to be composed of gene families of greater than expected phylogenetic profile similarity. This was particularly evident for primary metabolism pathways, whereas for secondary pathways, both the available annotation in different species as well as the abstraction of functional association via distinct pathways proved limiting. While phylogenetic profile similarity was generally not found to correlate with gene co-expression, direct physical interactions of proteins were reflected by a significantly increased profile similarity suggesting an application of phylogenetic profiling methods as a filtering step in the identification of protein-protein interactions. This feasibility study highlights the potential and challenges associated with phylogenetic profiling methods for the detection of functional relationships between genes as well as the need to enlarge the set of plant genes with proven secondary metabolism involvement as well as the limitations of distinct pathways as abstractions of relationships between genes. PMID:29163570

Database resources of the National Center for Biotechnology Information

PubMed Central

2015-01-01

The National Center for Biotechnology Information (NCBI) provides a large suite of online resources for biological information and data, including the GenBank® nucleic acid sequence database and the PubMed database of citations and abstracts for published life science journals. Additional NCBI resources focus on literature (Bookshelf, PubMed Central (PMC) and PubReader); medical genetics (ClinVar, dbMHC, the Genetic Testing Registry, HIV-1/Human Protein Interaction Database and MedGen); genes and genomics (BioProject, BioSample, dbSNP, dbVar, Epigenomics, Gene, Gene Expression Omnibus (GEO), Genome, HomoloGene, the Map Viewer, Nucleotide, PopSet, Probe, RefSeq, Sequence Read Archive, the Taxonomy Browser, Trace Archive and UniGene); and proteins and chemicals (Biosystems, COBALT, the Conserved Domain Database (CDD), the Conserved Domain Architecture Retrieval Tool (CDART), the Molecular Modeling Database (MMDB), Protein Clusters, Protein and the PubChem suite of small molecule databases). The Entrez system provides search and retrieval operations for many of these databases. Augmenting many of the Web applications are custom implementations of the BLAST program optimized to search specialized data sets. All of these resources can be accessed through the NCBI home page at http://www.ncbi.nlm.nih.gov. PMID:25398906

Database resources of the National Center for Biotechnology Information

PubMed Central

2016-01-01

The National Center for Biotechnology Information (NCBI) provides a large suite of online resources for biological information and data, including the GenBank® nucleic acid sequence database and the PubMed database of citations and abstracts for published life science journals. Additional NCBI resources focus on literature (PubMed Central (PMC), Bookshelf and PubReader), health (ClinVar, dbGaP, dbMHC, the Genetic Testing Registry, HIV-1/Human Protein Interaction Database and MedGen), genomes (BioProject, Assembly, Genome, BioSample, dbSNP, dbVar, Epigenomics, the Map Viewer, Nucleotide, Probe, RefSeq, Sequence Read Archive, the Taxonomy Browser and the Trace Archive), genes (Gene, Gene Expression Omnibus (GEO), HomoloGene, PopSet and UniGene), proteins (Protein, the Conserved Domain Database (CDD), COBALT, Conserved Domain Architecture Retrieval Tool (CDART), the Molecular Modeling Database (MMDB) and Protein Clusters) and chemicals (Biosystems and the PubChem suite of small molecule databases). The Entrez system provides search and retrieval operations for most of these databases. Augmenting many of the web applications are custom implementations of the BLAST program optimized to search specialized datasets. All of these resources can be accessed through the NCBI home page at www.ncbi.nlm.nih.gov. PMID:26615191

Rice Annotation Project Database (RAP-DB): an integrative and interactive database for rice genomics.

PubMed

Sakai, Hiroaki; Lee, Sung Shin; Tanaka, Tsuyoshi; Numa, Hisataka; Kim, Jungsok; Kawahara, Yoshihiro; Wakimoto, Hironobu; Yang, Ching-chia; Iwamoto, Masao; Abe, Takashi; Yamada, Yuko; Muto, Akira; Inokuchi, Hachiro; Ikemura, Toshimichi; Matsumoto, Takashi; Sasaki, Takuji; Itoh, Takeshi

2013-02-01

The Rice Annotation Project Database (RAP-DB, http://rapdb.dna.affrc.go.jp/) has been providing a comprehensive set of gene annotations for the genome sequence of rice, Oryza sativa (japonica group) cv. Nipponbare. Since the first release in 2005, RAP-DB has been updated several times along with the genome assembly updates. Here, we present our newest RAP-DB based on the latest genome assembly, Os-Nipponbare-Reference-IRGSP-1.0 (IRGSP-1.0), which was released in 2011. We detected 37,869 loci by mapping transcript and protein sequences of 150 monocot species. To provide plant researchers with highly reliable and up to date rice gene annotations, we have been incorporating literature-based manually curated data, and 1,626 loci currently incorporate literature-based annotation data, including commonly used gene names or gene symbols. Transcriptional activities are shown at the nucleotide level by mapping RNA-Seq reads derived from 27 samples. We also mapped the Illumina reads of a Japanese leading japonica cultivar, Koshihikari, and a Chinese indica cultivar, Guangluai-4, to the genome and show alignments together with the single nucleotide polymorphisms (SNPs) and gene functional annotations through a newly developed browser, Short-Read Assembly Browser (S-RAB). We have developed two satellite databases, Plant Gene Family Database (PGFD) and Integrative Database of Cereal Gene Phylogeny (IDCGP), which display gene family and homologous gene relationships among diverse plant species. RAP-DB and the satellite databases offer simple and user-friendly web interfaces, enabling plant and genome researchers to access the data easily and facilitating a broad range of plant research topics.

PlantGI: a database for searching gene indices in agricultural plants developed at NIAB, Korea

PubMed Central

Kim, Chang Kug; Choi, Ji Weon; Park, DongSuk; Kang, Man Jung; Seol, Young-Joo; Hyun, Do Yoon; Hahn, Jang Ho

2008-01-01

The Plant Gene Index (PlantGI) database is developed as a web-based search system with search capabilities for keywords to provide information on gene indices specifically for agricultural plants. The database contains specific Gene Index information for ten agricultural species, namely, rice, Chinese cabbage, wheat, maize, soybean, barley, mushroom, Arabidopsis, hot pepper and tomato. PlantGI differs from other Gene Index databases in being specific to agricultural plant species and thus complements services from similar other developments. The database includes options for interactive mining of EST CONTIGS and assembled EST data for user specific keyword queries. The current version of PlantGI contains a total of 34,000 EST CONTIGS data for rice (8488 records), wheat (8560 records), maize (4570 records), soybean (3726 records), barley (3417 records), Chinese cabbage (3602 records), tomato (1236 records), hot pepper (998 records), mushroom (130 records) and Arabidopsis (8 records). Availability The database is available for free at http://www.niab.go.kr/nabic/. PMID:18685722

IntPath--an integrated pathway gene relationship database for model organisms and important pathogens.

PubMed

Zhou, Hufeng; Jin, Jingjing; Zhang, Haojun; Yi, Bo; Wozniak, Michal; Wong, Limsoon

2012-01-01

Pathway data are important for understanding the relationship between genes, proteins and many other molecules in living organisms. Pathway gene relationships are crucial information for guidance, prediction, reference and assessment in biochemistry, computational biology, and medicine. Many well-established databases--e.g., KEGG, WikiPathways, and BioCyc--are dedicated to collecting pathway data for public access. However, the effectiveness of these databases is hindered by issues such as incompatible data formats, inconsistent molecular representations, inconsistent molecular relationship representations, inconsistent referrals to pathway names, and incomprehensive data from different databases. In this paper, we overcome these issues through extraction, normalization and integration of pathway data from several major public databases (KEGG, WikiPathways, BioCyc, etc). We build a database that not only hosts our integrated pathway gene relationship data for public access but also maintains the necessary updates in the long run. This public repository is named IntPath (Integrated Pathway gene relationship database for model organisms and important pathogens). Four organisms--S. cerevisiae, M. tuberculosis H37Rv, H. Sapiens and M. musculus--are included in this version (V2.0) of IntPath. IntPath uses the "full unification" approach to ensure no deletion and no introduced noise in this process. Therefore, IntPath contains much richer pathway-gene and pathway-gene pair relationships and much larger number of non-redundant genes and gene pairs than any of the single-source databases. The gene relationships of each gene (measured by average node degree) per pathway are significantly richer. The gene relationships in each pathway (measured by average number of gene pairs per pathway) are also considerably richer in the integrated pathways. Moderate manual curation are involved to get rid of errors and noises from source data (e.g., the gene ID errors in WikiPathways and relationship errors in KEGG). We turn complicated and incompatible xml data formats and inconsistent gene and gene relationship representations from different source databases into normalized and unified pathway-gene and pathway-gene pair relationships neatly recorded in simple tab-delimited text format and MySQL tables, which facilitates convenient automatic computation and large-scale referencing in many related studies. IntPath data can be downloaded in text format or MySQL dump. IntPath data can also be retrieved and analyzed conveniently through web service by local programs or through web interface by mouse clicks. Several useful analysis tools are also provided in IntPath. We have overcome in IntPath the issues of compatibility, consistency, and comprehensiveness that often hamper effective use of pathway databases. We have included four organisms in the current release of IntPath. Our methodology and programs described in this work can be easily applied to other organisms; and we will include more model organisms and important pathogens in future releases of IntPath. IntPath maintains regular updates and is freely available at http://compbio.ddns.comp.nus.edu.sg:8080/IntPath.

Microarray and comparative genomics-based identification of genes and gene regulatory regions of the mouse immune system

PubMed Central

Hutton, John J; Jegga, Anil G; Kong, Sue; Gupta, Ashima; Ebert, Catherine; Williams, Sarah; Katz, Jonathan D; Aronow, Bruce J

2004-01-01

Background In this study we have built and mined a gene expression database composed of 65 diverse mouse tissues for genes preferentially expressed in immune tissues and cell types. Using expression pattern criteria, we identified 360 genes with preferential expression in thymus, spleen, peripheral blood mononuclear cells, lymph nodes (unstimulated or stimulated), or in vitro activated T-cells. Results Gene clusters, formed based on similarity of expression-pattern across either all tissues or the immune tissues only, had highly significant associations both with immunological processes such as chemokine-mediated response, antigen processing, receptor-related signal transduction, and transcriptional regulation, and also with more general processes such as replication and cell cycle control. Within-cluster gene correlations implicated known associations of known genes, as well as immune process-related roles for poorly described genes. To characterize regulatory mechanisms and cis-elements of genes with similar patterns of expression, we used a new version of a comparative genomics-based cis-element analysis tool to identify clusters of cis-elements with compositional similarity among multiple genes. Several clusters contained genes that shared 5–6 cis-elements that included ETS and zinc-finger binding sites. cis-Elements AP2 EGRF ETSF MAZF SP1F ZF5F and AREB ETSF MZF1 PAX5 STAT were shared in a thymus-expressed set; AP4R E2FF EBOX ETSF MAZF SP1F ZF5F and CREB E2FF MAZF PCAT SP1F STAT cis-clusters occurred in activated T-cells; CEBP CREB NFKB SORY and GATA NKXH OCT1 RBIT occurred in stimulated lymph nodes. Conclusion This study demonstrates a series of analytic approaches that have allowed the implication of genes and regulatory elements that participate in the differentiation, maintenance, and function of the immune system. Polymorphism or mutation of these could adversely impact immune system functions. PMID:15504237

Aspergillus flavus Blast2GO gene ontology database: elevated growth temperature alters amino acid metabolism

USDA-ARS?s Scientific Manuscript database

The availability of a representative gene ontology (GO) database is a prerequisite for a successful functional genomics study. Using online Blast2GO resources we constructed a GO database of Aspergillus flavus. Of the predicted total 13,485 A. flavus genes 8,987 were annotated with GO terms. The mea...

Genic insights from integrated human proteomics in GeneCards.

PubMed

Fishilevich, Simon; Zimmerman, Shahar; Kohn, Asher; Iny Stein, Tsippi; Olender, Tsviya; Kolker, Eugene; Safran, Marilyn; Lancet, Doron

2016-01-01

GeneCards is a one-stop shop for searchable human gene annotations (http://www.genecards.org/). Data are automatically mined from ∼120 sources and presented in an integrated web card for every human gene. We report the application of recent advances in proteomics to enhance gene annotation and classification in GeneCards. First, we constructed the Human Integrated Protein Expression Database (HIPED), a unified database of protein abundance in human tissues, based on the publically available mass spectrometry (MS)-based proteomics sources ProteomicsDB, Multi-Omics Profiling Expression Database, Protein Abundance Across Organisms and The MaxQuant DataBase. The integrated database, residing within GeneCards, compares favourably with its individual sources, covering nearly 90% of human protein-coding genes. For gene annotation and comparisons, we first defined a protein expression vector for each gene, based on normalized abundances in 69 normal human tissues. This vector is portrayed in the GeneCards expression section as a bar graph, allowing visual inspection and comparison. These data are juxtaposed with transcriptome bar graphs. Using the protein expression vectors, we further defined a pairwise metric that helps assess expression-based pairwise proximity. This new metric for finding functional partners complements eight others, including sharing of pathways, gene ontology (GO) terms and domains, implemented in the GeneCards Suite. In parallel, we calculated proteome-based differential expression, highlighting a subset of tissues that overexpress a gene and subserving gene classification. This textual annotation allows users of VarElect, the suite's next-generation phenotyper, to more effectively discover causative disease variants. Finally, we define the protein-RNA expression ratio and correlation as yet another attribute of every gene in each tissue, adding further annotative information. The results constitute a significant enhancement of several GeneCards sections and help promote and organize the genome-wide structural and functional knowledge of the human proteome. Database URL:http://www.genecards.org/. © The Author(s) 2016. Published by Oxford University Press.

OGRO: The Overview of functionally characterized Genes in Rice online database.

PubMed

Yamamoto, Eiji; Yonemaru, Jun-Ichi; Yamamoto, Toshio; Yano, Masahiro

2012-12-01

The high-quality sequence information and rich bioinformatics tools available for rice have contributed to remarkable advances in functional genomics. To facilitate the application of gene function information to the study of natural variation in rice, we comprehensively searched for articles related to rice functional genomics and extracted information on functionally characterized genes. As of 31 March 2012, 702 functionally characterized genes were annotated. This number represents about 1.6% of the predicted loci in the Rice Annotation Project Database. The compiled gene information is organized to facilitate direct comparisons with quantitative trait locus (QTL) information in the Q-TARO database. Comparison of genomic locations between functionally characterized genes and the QTLs revealed that QTL clusters were often co-localized with high-density gene regions, and that the genes associated with the QTLs in these clusters were different genes, suggesting that these QTL clusters are likely to be explained by tightly linked but distinct genes. Information on the functionally characterized genes compiled during this study is now available in the O verview of Functionally Characterized G enes in R ice O nline database (OGRO) on the Q-TARO website ( http://qtaro.abr.affrc.go.jp/ogro ). The database has two interfaces: a table containing gene information, and a genome viewer that allows users to compare the locations of QTLs and functionally characterized genes. OGRO on Q-TARO will facilitate a candidate-gene approach to identifying the genes responsible for QTLs. Because the QTL descriptions in Q-TARO contain information on agronomic traits, such comparisons will also facilitate the annotation of functionally characterized genes in terms of their effects on traits important for rice breeding. The increasing amount of information on rice gene function being generated from mutant panels and other types of studies will make the OGRO database even more valuable in the future.

Online Analytical Processing (OLAP): A Fast and Effective Data Mining Tool for Gene Expression Databases

PubMed Central

2005-01-01

Gene expression databases contain a wealth of information, but current data mining tools are limited in their speed and effectiveness in extracting meaningful biological knowledge from them. Online analytical processing (OLAP) can be used as a supplement to cluster analysis for fast and effective data mining of gene expression databases. We used Analysis Services 2000, a product that ships with SQLServer2000, to construct an OLAP cube that was used to mine a time series experiment designed to identify genes associated with resistance of soybean to the soybean cyst nematode, a devastating pest of soybean. The data for these experiments is stored in the soybean genomics and microarray database (SGMD). A number of candidate resistance genes and pathways were found. Compared to traditional cluster analysis of gene expression data, OLAP was more effective and faster in finding biologically meaningful information. OLAP is available from a number of vendors and can work with any relational database management system through OLE DB. PMID:16046824

Entamoeba histolytica: construction and applications of subgenomic databases.

PubMed

Hofer, Margit; Duchêne, Michael

2005-07-01

Knowledge about the influence of environmental stress such as the action of chemotherapeutic agents on gene expression in Entamoeba histolytica is limited. We plan to use oligonucleotide microarray hybridization to approach these questions. As the basis for our array, sequence data from the genome project carried out by the Institute for Genomic Research (TIGR) and the Sanger Institute were used to annotate parts of the parasite genome. Three subgenomic databases containing enzymes, cytoskeleton genes, and stress genes were compiled with the help of the ExPASy proteomics website and the BLAST servers at the two genome project sites. The known sequences from reference species, mostly human and Escherichia coli, were searched against TIGR and Sanger E. histolytica sequence contigs and the homologs were copied into a Microsoft Access database. In a similar way, two additional databases of cytoskeletal genes and stress genes were generated. Metabolic pathways could be assembled from our enzyme database, but sometimes they were incomplete as is the case for the sterol biosynthesis pathway. The raw databases contained a significant number of duplicate entries which were merged to obtain curated non-redundant databases. This procedure revealed that some E. histolytica genes may have several putative functions. Representative examples such as the case of the delta-aminolevulinate synthase/serine palmitoyltransferase are discussed.

Advancement of a soil parameters geodatabase for the modeling assessment of conservation practice outcomes in the United States

USDA-ARS?s Scientific Manuscript database

US-ModSoilParms-TEMPLE is a database composed of a set of geographic databases functionally storing soil-spatial units and soil hydraulic, physical, and chemical parameters for three agriculture management simulation models, SWAT, APEX, and ALMANAC. This paper introduces the updated US-ModSoilParms-...

Cry-Bt identifier: a biological database for PCR detection of Cry genes present in transgenic plants.

PubMed

Singh, Vinay Kumar; Ambwani, Sonu; Marla, Soma; Kumar, Anil

2009-10-23

We describe the development of a user friendly tool that would assist in the retrieval of information relating to Cry genes in transgenic crops. The tool also helps in detection of transformed Cry genes from Bacillus thuringiensis present in transgenic plants by providing suitable designed primers for PCR identification of these genes. The tool designed based on relational database model enables easy retrieval of information from the database with simple user queries. The tool also enables users to access related information about Cry genes present in various databases by interacting with different sources (nucleotide sequences, protein sequence, sequence comparison tools, published literature, conserved domains, evolutionary and structural data). http://insilicogenomics.in/Cry-btIdentifier/welcome.html.

Cationic niosomes an effective gene carrier composed of novel spermine-derivative cationic lipids: effect of central core structures.

PubMed

Opanasopit, Praneet; Leksantikul, Lalita; Niyomtham, Nattisa; Rojanarata, Theerasak; Ngawhirunpat, Tanasait; Yingyongnarongkul, Boon-Ek

2017-05-01

Cationic niosomes formulated from Span 20, cholesterol (Chol) and novel spermine-based cationic lipids of multiple central core structures (di(oxyethyl)amino, di(oxyethyl)amino carboxy, 3-amino-1,2-dioxypropyl and 2-amino-1,3-dioxypropyl) were successfully prepared for improving transfection efficiency in vitro. The niosomes composed of spermine cationic lipid with central core structure of di(oxyethyl)amino revealed the highest gene transfection efficiency. To investigate the factors affecting gene transfection and cell viability including differences in the central core structures of cationic lipids, the composition of vesicles, molar ratio of cationic lipids in formulations and the weight ratio of niosomes to DNA. Cationic niosomes composed of nonionic surfactants (Span20), cholesterol and spermine-based cationic lipids of multiple central core structures were formulated. Gene transfection and cell viability were evaluated on a human cervical carcinoma cell line (HeLa cells) using pDNA encoding green fluorescent protein (pEGFP-C2). The morphology, size and charge were also characterized. High transfection efficiency was obtained from cationic niosomes composed of Span20:Chol:cationic lipid at the molar ratio of 2.5:2.5:0.5 mM. Cationic lipids with di(oxyethyl)amino as a central core structure exhibited highest transfection efficiency. In addition, there was also no serum effect on transfection efficiency. These novel cationic niosomes may constitute a good alternative carrier for gene transfection.

Pairwise gene GO-based measures for biclustering of high-dimensional expression data.

PubMed

Nepomuceno, Juan A; Troncoso, Alicia; Nepomuceno-Chamorro, Isabel A; Aguilar-Ruiz, Jesús S

2018-01-01

Biclustering algorithms search for groups of genes that share the same behavior under a subset of samples in gene expression data. Nowadays, the biological knowledge available in public repositories can be used to drive these algorithms to find biclusters composed of groups of genes functionally coherent. On the other hand, a distance among genes can be defined according to their information stored in Gene Ontology (GO). Gene pairwise GO semantic similarity measures report a value for each pair of genes which establishes their functional similarity. A scatter search-based algorithm that optimizes a merit function that integrates GO information is studied in this paper. This merit function uses a term that addresses the information through a GO measure. The effect of two possible different gene pairwise GO measures on the performance of the algorithm is analyzed. Firstly, three well known yeast datasets with approximately one thousand of genes are studied. Secondly, a group of human datasets related to clinical data of cancer is also explored by the algorithm. Most of these data are high-dimensional datasets composed of a huge number of genes. The resultant biclusters reveal groups of genes linked by a same functionality when the search procedure is driven by one of the proposed GO measures. Furthermore, a qualitative biological study of a group of biclusters show their relevance from a cancer disease perspective. It can be concluded that the integration of biological information improves the performance of the biclustering process. The two different GO measures studied show an improvement in the results obtained for the yeast dataset. However, if datasets are composed of a huge number of genes, only one of them really improves the algorithm performance. This second case constitutes a clear option to explore interesting datasets from a clinical point of view.

Genevar: a database and Java application for the analysis and visualization of SNP-gene associations in eQTL studies.

PubMed

Yang, Tsun-Po; Beazley, Claude; Montgomery, Stephen B; Dimas, Antigone S; Gutierrez-Arcelus, Maria; Stranger, Barbara E; Deloukas, Panos; Dermitzakis, Emmanouil T

2010-10-01

Genevar (GENe Expression VARiation) is a database and Java tool designed to integrate multiple datasets, and provides analysis and visualization of associations between sequence variation and gene expression. Genevar allows researchers to investigate expression quantitative trait loci (eQTL) associations within a gene locus of interest in real time. The database and application can be installed on a standard computer in database mode and, in addition, on a server to share discoveries among affiliations or the broader community over the Internet via web services protocols. http://www.sanger.ac.uk/resources/software/genevar.

Development and Implementation of Kumamoto Technopolis Regional Database T-KIND

NASA Astrophysics Data System (ADS)

Onoue, Noriaki

T-KIND (Techno-Kumamoto Information Network for Data-Base) is a system for effectively searching information of technology, human resources and industries which are necessary to realize Kumamoto Technopolis. It is composed of coded database, image database and LAN inside technoresearch park which is the center of R & D in the Technopolis. It constructs on-line system by networking general-purposed computers, minicomputers, optical disk file systems and so on, and provides the service through public telephone line. Two databases are now available on enterprise information and human resource information. The former covers about 4,000 enterprises, and the latter does about 2,000 persons.

Drug-Path: a database for drug-induced pathways.

PubMed

Zeng, Hui; Qiu, Chengxiang; Cui, Qinghua

2015-01-01

Some databases for drug-associated pathways have been built and are publicly available. However, the pathways curated in most of these databases are drug-action or drug-metabolism pathways. In recent years, high-throughput technologies such as microarray and RNA-sequencing have produced lots of drug-induced gene expression profiles. Interestingly, drug-induced gene expression profile frequently show distinct patterns, indicating that drugs normally induce the activation or repression of distinct pathways. Therefore, these pathways contribute to study the mechanisms of drugs and drug-repurposing. Here, we present Drug-Path, a database of drug-induced pathways, which was generated by KEGG pathway enrichment analysis for drug-induced upregulated genes and downregulated genes based on drug-induced gene expression datasets in Connectivity Map. Drug-Path provides user-friendly interfaces to retrieve, visualize and download the drug-induced pathway data in the database. In addition, the genes deregulated by a given drug are highlighted in the pathways. All data were organized using SQLite. The web site was implemented using Django, a Python web framework. Finally, we believe that this database will be useful for related researches. © The Author(s) 2015. Published by Oxford University Press.

Production of individualized V gene databases reveals high levels of immunoglobulin genetic diversity

NASA Astrophysics Data System (ADS)

Corcoran, Martin M.; Phad, Ganesh E.; Bernat, Néstor Vázquez; Stahl-Hennig, Christiane; Sumida, Noriyuki; Persson, Mats A. A.; Martin, Marcel; Hedestam, Gunilla B. Karlsson

2016-12-01

Comprehensive knowledge of immunoglobulin genetics is required to advance our understanding of B cell biology. Validated immunoglobulin variable (V) gene databases are close to completion only for human and mouse. We present a novel computational approach, IgDiscover, that identifies germline V genes from expressed repertoires to a specificity of 100%. IgDiscover uses a cluster identification process to produce candidate sequences that, once filtered, results in individualized germline V gene databases. IgDiscover was tested in multiple species, validated by genomic cloning and cross library comparisons and produces comprehensive gene databases even where limited genomic sequence is available. IgDiscover analysis of the allelic content of the Indian and Chinese-origin rhesus macaques reveals high levels of immunoglobulin gene diversity in this species. Further, we describe a novel human IGHV3-21 allele and confirm significant gene differences between Balb/c and C57BL6 mouse strains, demonstrating the power of IgDiscover as a germline V gene discovery tool.

Production of individualized V gene databases reveals high levels of immunoglobulin genetic diversity

PubMed Central

Corcoran, Martin M.; Phad, Ganesh E.; Bernat, Néstor Vázquez; Stahl-Hennig, Christiane; Sumida, Noriyuki; Persson, Mats A.A.; Martin, Marcel; Hedestam, Gunilla B. Karlsson

2016-01-01

Comprehensive knowledge of immunoglobulin genetics is required to advance our understanding of B cell biology. Validated immunoglobulin variable (V) gene databases are close to completion only for human and mouse. We present a novel computational approach, IgDiscover, that identifies germline V genes from expressed repertoires to a specificity of 100%. IgDiscover uses a cluster identification process to produce candidate sequences that, once filtered, results in individualized germline V gene databases. IgDiscover was tested in multiple species, validated by genomic cloning and cross library comparisons and produces comprehensive gene databases even where limited genomic sequence is available. IgDiscover analysis of the allelic content of the Indian and Chinese-origin rhesus macaques reveals high levels of immunoglobulin gene diversity in this species. Further, we describe a novel human IGHV3-21 allele and confirm significant gene differences between Balb/c and C57BL6 mouse strains, demonstrating the power of IgDiscover as a germline V gene discovery tool. PMID:27995928

The Molecular Signatures Database (MSigDB) hallmark gene set collection.

PubMed

Liberzon, Arthur; Birger, Chet; Thorvaldsdóttir, Helga; Ghandi, Mahmoud; Mesirov, Jill P; Tamayo, Pablo

2015-12-23

The Molecular Signatures Database (MSigDB) is one of the most widely used and comprehensive databases of gene sets for performing gene set enrichment analysis. Since its creation, MSigDB has grown beyond its roots in metabolic disease and cancer to include >10,000 gene sets. These better represent a wider range of biological processes and diseases, but the utility of the database is reduced by increased redundancy across, and heterogeneity within, gene sets. To address this challenge, here we use a combination of automated approaches and expert curation to develop a collection of "hallmark" gene sets as part of MSigDB. Each hallmark in this collection consists of a "refined" gene set, derived from multiple "founder" sets, that conveys a specific biological state or process and displays coherent expression. The hallmarks effectively summarize most of the relevant information of the original founder sets and, by reducing both variation and redundancy, provide more refined and concise inputs for gene set enrichment analysis.

Development of a gene expression database and related analysis programs for evaluation of anticancer compounds.

PubMed

Ushijima, Masaru; Mashima, Tetsuo; Tomida, Akihiro; Dan, Shingo; Saito, Sakae; Furuno, Aki; Tsukahara, Satomi; Seimiya, Hiroyuki; Yamori, Takao; Matsuura, Masaaki

2013-03-01

Genome-wide transcriptional expression analysis is a powerful strategy for characterizing the biological activity of anticancer compounds. It is often instructive to identify gene sets involved in the activity of a given drug compound for comparison with different compounds. Currently, however, there is no comprehensive gene expression database and related application system that is; (i) specialized in anticancer agents; (ii) easy to use; and (iii) open to the public. To develop a public gene expression database of antitumor agents, we first examined gene expression profiles in human cancer cells after exposure to 35 compounds including 25 clinically used anticancer agents. Gene signatures were extracted that were classified as upregulated or downregulated after exposure to the drug. Hierarchical clustering showed that drugs with similar mechanisms of action, such as genotoxic drugs, were clustered. Connectivity map analysis further revealed that our gene signature data reflected modes of action of the respective agents. Together with the database, we developed analysis programs that calculate scores for ranking changes in gene expression and for searching statistically significant pathways from the Kyoto Encyclopedia of Genes and Genomes database in order to analyze the datasets more easily. Our database and the analysis programs are available online at our website (http://scads.jfcr.or.jp/db/cs/). Using these systems, we successfully showed that proteasome inhibitors are selectively classified as endoplasmic reticulum stress inducers and induce atypical endoplasmic reticulum stress. Thus, our public access database and related analysis programs constitute a set of efficient tools to evaluate the mode of action of novel compounds and identify promising anticancer lead compounds. © 2012 Japanese Cancer Association.

CCDB: a curated database of genes involved in cervix cancer.

PubMed

Agarwal, Subhash M; Raghav, Dhwani; Singh, Harinder; Raghava, G P S

2011-01-01

The Cervical Cancer gene DataBase (CCDB, http://crdd.osdd.net/raghava/ccdb) is a manually curated catalog of experimentally validated genes that are thought, or are known to be involved in the different stages of cervical carcinogenesis. In spite of the large women population that is presently affected from this malignancy still at present, no database exists that catalogs information on genes associated with cervical cancer. Therefore, we have compiled 537 genes in CCDB that are linked with cervical cancer causation processes such as methylation, gene amplification, mutation, polymorphism and change in expression level, as evident from published literature. Each record contains details related to gene like architecture (exon-intron structure), location, function, sequences (mRNA/CDS/protein), ontology, interacting partners, homology to other eukaryotic genomes, structure and links to other public databases, thus augmenting CCDB with external data. Also, manually curated literature references have been provided to support the inclusion of the gene in the database and establish its association with cervix cancer. In addition, CCDB provides information on microRNA altered in cervical cancer as well as search facility for querying, several browse options and an online tool for sequence similarity search, thereby providing researchers with easy access to the latest information on genes involved in cervix cancer.

Oral cancer databases: A comprehensive review.

PubMed

Sarode, Gargi S; Sarode, Sachin C; Maniyar, Nikunj; Anand, Rahul; Patil, Shankargouda

2017-11-29

Cancer database is a systematic collection and analysis of information on various human cancers at genomic and molecular level that can be utilized to understand various steps in carcinogenesis and for therapeutic advancement in cancer field. Oral cancer is one of the leading causes of morbidity and mortality all over the world. The current research efforts in this field are aimed at cancer etiology and therapy. Advanced genomic technologies including microarrays, proteomics, transcrpitomics, and gene sequencing development have culminated in generation of extensive data and subjection of several genes and microRNAs that are distinctively expressed and this information is stored in the form of various databases. Extensive data from various resources have brought the need for collaboration and data sharing to make effective use of this new knowledge. The current review provides comprehensive information of various publicly accessible databases that contain information pertinent to oral squamous cell carcinoma (OSCC) and databases designed exclusively for OSCC. The databases discussed in this paper are Protein-Coding Gene Databases and microRNA Databases. This paper also describes gene overlap in various databases, which will help researchers to reduce redundancy and focus on only those genes, which are common to more than one databases. We hope such introduction will promote awareness and facilitate the usage of these resources in the cancer research community, and researchers can explore the molecular mechanisms involved in the development of cancer, which can help in subsequent crafting of therapeutic strategies. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Human Variome Project Quality Assessment Criteria for Variation Databases.

PubMed

Vihinen, Mauno; Hancock, John M; Maglott, Donna R; Landrum, Melissa J; Schaafsma, Gerard C P; Taschner, Peter

2016-06-01

Numerous databases containing information about DNA, RNA, and protein variations are available. Gene-specific variant databases (locus-specific variation databases, LSDBs) are typically curated and maintained for single genes or groups of genes for a certain disease(s). These databases are widely considered as the most reliable information source for a particular gene/protein/disease, but it should also be made clear they may have widely varying contents, infrastructure, and quality. Quality is very important to evaluate because these databases may affect health decision-making, research, and clinical practice. The Human Variome Project (HVP) established a Working Group for Variant Database Quality Assessment. The basic principle was to develop a simple system that nevertheless provides a good overview of the quality of a database. The HVP quality evaluation criteria that resulted are divided into four main components: data quality, technical quality, accessibility, and timeliness. This report elaborates on the developed quality criteria and how implementation of the quality scheme can be achieved. Examples are provided for the current status of the quality items in two different databases, BTKbase, an LSDB, and ClinVar, a central archive of submissions about variants and their clinical significance. © 2016 WILEY PERIODICALS, INC.

GRBase, a new gene regulation data base available by anonymous ftp.

PubMed Central

Collier, B; Danielsen, M

1994-01-01

The Gene Regulation Database (GRBase) is a compendium of information on the structure and function of proteins involved in the control of gene expression in eukaryotes. These proteins include transcription factors, proteins involved in signal transduction, and receptors. The database can be obtained by FTP in Filemaker Pro, text, and postscript formats. The database will be expanded in the coming year to include reviews on families of proteins involved in gene regulation and to allow online searching. PMID:7937071

IntPath--an integrated pathway gene relationship database for model organisms and important pathogens

PubMed Central

2012-01-01

Background Pathway data are important for understanding the relationship between genes, proteins and many other molecules in living organisms. Pathway gene relationships are crucial information for guidance, prediction, reference and assessment in biochemistry, computational biology, and medicine. Many well-established databases--e.g., KEGG, WikiPathways, and BioCyc--are dedicated to collecting pathway data for public access. However, the effectiveness of these databases is hindered by issues such as incompatible data formats, inconsistent molecular representations, inconsistent molecular relationship representations, inconsistent referrals to pathway names, and incomprehensive data from different databases. Results In this paper, we overcome these issues through extraction, normalization and integration of pathway data from several major public databases (KEGG, WikiPathways, BioCyc, etc). We build a database that not only hosts our integrated pathway gene relationship data for public access but also maintains the necessary updates in the long run. This public repository is named IntPath (Integrated Pathway gene relationship database for model organisms and important pathogens). Four organisms--S. cerevisiae, M. tuberculosis H37Rv, H. Sapiens and M. musculus--are included in this version (V2.0) of IntPath. IntPath uses the "full unification" approach to ensure no deletion and no introduced noise in this process. Therefore, IntPath contains much richer pathway-gene and pathway-gene pair relationships and much larger number of non-redundant genes and gene pairs than any of the single-source databases. The gene relationships of each gene (measured by average node degree) per pathway are significantly richer. The gene relationships in each pathway (measured by average number of gene pairs per pathway) are also considerably richer in the integrated pathways. Moderate manual curation are involved to get rid of errors and noises from source data (e.g., the gene ID errors in WikiPathways and relationship errors in KEGG). We turn complicated and incompatible xml data formats and inconsistent gene and gene relationship representations from different source databases into normalized and unified pathway-gene and pathway-gene pair relationships neatly recorded in simple tab-delimited text format and MySQL tables, which facilitates convenient automatic computation and large-scale referencing in many related studies. IntPath data can be downloaded in text format or MySQL dump. IntPath data can also be retrieved and analyzed conveniently through web service by local programs or through web interface by mouse clicks. Several useful analysis tools are also provided in IntPath. Conclusions We have overcome in IntPath the issues of compatibility, consistency, and comprehensiveness that often hamper effective use of pathway databases. We have included four organisms in the current release of IntPath. Our methodology and programs described in this work can be easily applied to other organisms; and we will include more model organisms and important pathogens in future releases of IntPath. IntPath maintains regular updates and is freely available at http://compbio.ddns.comp.nus.edu.sg:8080/IntPath. PMID:23282057

FARE-CAFE: a database of functional and regulatory elements of cancer-associated fusion events.

PubMed

Korla, Praveen Kumar; Cheng, Jack; Huang, Chien-Hung; Tsai, Jeffrey J P; Liu, Yu-Hsuan; Kurubanjerdjit, Nilubon; Hsieh, Wen-Tsong; Chen, Huey-Yi; Ng, Ka-Lok

2015-01-01

Chromosomal translocation (CT) is of enormous clinical interest because this disorder is associated with various major solid tumors and leukemia. A tumor-specific fusion gene event may occur when a translocation joins two separate genes. Currently, various CT databases provide information about fusion genes and their genomic elements. However, no database of the roles of fusion genes, in terms of essential functional and regulatory elements in oncogenesis, is available. FARE-CAFE is a unique combination of CTs, fusion proteins, protein domains, domain-domain interactions, protein-protein interactions, transcription factors and microRNAs, with subsequent experimental information, which cannot be found in any other CT database. Genomic DNA information including, for example, manually collected exact locations of the first and second break points, sequences and karyotypes of fusion genes are included. FARE-CAFE will substantially facilitate the cancer biologist's mission of elucidating the pathogenesis of various types of cancer. This database will ultimately help to develop 'novel' therapeutic approaches. Database URL: http://ppi.bioinfo.asia.edu.tw/FARE-CAFE. © The Author(s) 2015. Published by Oxford University Press.

FARE-CAFE: a database of functional and regulatory elements of cancer-associated fusion events

PubMed Central

Korla, Praveen Kumar; Cheng, Jack; Huang, Chien-Hung; Tsai, Jeffrey J. P.; Liu, Yu-Hsuan; Kurubanjerdjit, Nilubon; Hsieh, Wen-Tsong; Chen, Huey-Yi; Ng, Ka-Lok

2015-01-01

Chromosomal translocation (CT) is of enormous clinical interest because this disorder is associated with various major solid tumors and leukemia. A tumor-specific fusion gene event may occur when a translocation joins two separate genes. Currently, various CT databases provide information about fusion genes and their genomic elements. However, no database of the roles of fusion genes, in terms of essential functional and regulatory elements in oncogenesis, is available. FARE-CAFE is a unique combination of CTs, fusion proteins, protein domains, domain–domain interactions, protein–protein interactions, transcription factors and microRNAs, with subsequent experimental information, which cannot be found in any other CT database. Genomic DNA information including, for example, manually collected exact locations of the first and second break points, sequences and karyotypes of fusion genes are included. FARE-CAFE will substantially facilitate the cancer biologist’s mission of elucidating the pathogenesis of various types of cancer. This database will ultimately help to develop ‘novel’ therapeutic approaches. Database URL: http://ppi.bioinfo.asia.edu.tw/FARE-CAFE PMID:26384373

An Assessment of Database-Validated microRNA Target Genes in Normal Colonic Mucosa: Implications for Pathway Analysis.

PubMed

Slattery, Martha L; Herrick, Jennifer S; Stevens, John R; Wolff, Roger K; Mullany, Lila E

2017-01-01

Determination of functional pathways regulated by microRNAs (miRNAs), while an essential step in developing therapeutics, is challenging. Some miRNAs have been studied extensively; others have limited information. In this study, we focus on 254 miRNAs previously identified as being associated with colorectal cancer and their database-identified validated target genes. We use RNA-Seq data to evaluate messenger RNA (mRNA) expression for 157 subjects who also had miRNA expression data. In the replication phase of the study, we replicated associations between 254 miRNAs associated with colorectal cancer and mRNA expression of database-identified target genes in normal colonic mucosa. In the discovery phase of the study, we evaluated expression of 18 miR-NAs (those with 20 or fewer database-identified target genes along with miR-21-5p, miR-215-5p, and miR-124-3p which have more than 500 database-identified target genes) with expression of 17 434 mRNAs to identify new targets in colon tissue. Seed region matches between miRNA and newly identified targeted mRNA were used to help determine direct miRNA-mRNA associations. From the replication of the 121 miRNAs that had at least 1 database-identified target gene using mRNA expression methods, 97.9% were expressed in normal colonic mucosa. Of the 8622 target miRNA-mRNA associations identified in the database, 2658 (30.2%) were associated with gene expression in normal colonic mucosa after adjusting for multiple comparisons. Of the 133 miRNAs with database-identified target genes by non-mRNA expression methods, 97.2% were expressed in normal colonic mucosa. After adjustment for multiple comparisons, 2416 miRNA-mRNA associations remained significant (19.8%). Results from the discovery phase based on detailed examination of 18 miRNAs identified more than 80 000 miRNA-mRNA associations that had not previously linked to the miRNA. Of these miRNA-mRNA associations, 15.6% and 14.8% had seed matches for CRCh38 and CRCh37, respectively. Our data suggest that miRNA target gene databases are incomplete; pathways derived from these databases have similar deficiencies. Although we know a lot about several miRNAs, little is known about other miRNAs in terms of their targeted genes. We encourage others to use their data to continue to further identify and validate miRNA-targeted genes.

MGDB: a comprehensive database of genes involved in melanoma.

PubMed

Zhang, Di; Zhu, Rongrong; Zhang, Hanqian; Zheng, Chun-Hou; Xia, Junfeng

2015-01-01

The Melanoma Gene Database (MGDB) is a manually curated catalog of molecular genetic data relating to genes involved in melanoma. The main purpose of this database is to establish a network of melanoma related genes and to facilitate the mechanistic study of melanoma tumorigenesis. The entries describing the relationships between melanoma and genes in the current release were manually extracted from PubMed abstracts, which contains cumulative to date 527 human melanoma genes (422 protein-coding and 105 non-coding genes). Each melanoma gene was annotated in seven different aspects (General Information, Expression, Methylation, Mutation, Interaction, Pathway and Drug). In addition, manually curated literature references have also been provided to support the inclusion of the gene in MGDB and establish its association with melanoma. MGDB has a user-friendly web interface with multiple browse and search functions. We hoped MGDB will enrich our knowledge about melanoma genetics and serve as a useful complement to the existing public resources. Database URL: http://bioinfo.ahu.edu.cn:8080/Melanoma/index.jsp. © The Author(s) 2015. Published by Oxford University Press.

Gene: a gene-centered information resource at NCBI.

PubMed

Brown, Garth R; Hem, Vichet; Katz, Kenneth S; Ovetsky, Michael; Wallin, Craig; Ermolaeva, Olga; Tolstoy, Igor; Tatusova, Tatiana; Pruitt, Kim D; Maglott, Donna R; Murphy, Terence D

2015-01-01

The National Center for Biotechnology Information's (NCBI) Gene database (www.ncbi.nlm.nih.gov/gene) integrates gene-specific information from multiple data sources. NCBI Reference Sequence (RefSeq) genomes for viruses, prokaryotes and eukaryotes are the primary foundation for Gene records in that they form the critical association between sequence and a tracked gene upon which additional functional and descriptive content is anchored. Additional content is integrated based on the genomic location and RefSeq transcript and protein sequence data. The content of a Gene record represents the integration of curation and automated processing from RefSeq, collaborating model organism databases, consortia such as Gene Ontology, and other databases within NCBI. Records in Gene are assigned unique, tracked integers as identifiers. The content (citations, nomenclature, genomic location, gene products and their attributes, phenotypes, sequences, interactions, variation details, maps, expression, homologs, protein domains and external databases) is available via interactive browsing through NCBI's Entrez system, via NCBI's Entrez programming utilities (E-Utilities and Entrez Direct) and for bulk transfer by FTP. Published by Oxford University Press on behalf of Nucleic Acids Research 2014. This work is written by (a) US Government employee(s) and is in the public domain in the US.

In silico analysis of cacao (Theobroma cacao L.) genes that involved in pathogen and disease responses

NASA Astrophysics Data System (ADS)

Agung, Muhammad Budi; Budiarsa, I. Made; Suwastika, I. Nengah

2017-02-01

Cocoa bean is one of the main commodities from Indonesia for the world, which still have problem regarding yield degradation due to pathogens and disease attack. Developing robust cacao plant that genetically resistant to pathogen and disease attack is an ideal solution in over taking on this problem. The aim of this study was to identify Theobroma cacao genes on database of cacao genome that homolog to response genes of pathogen and disease attack in other plant, through in silico analysis. Basic information survey and gene identification were performed in GenBank and The Arabidopsis Information Resource database. The In silico analysis contains protein BLAST, homology test of each gene's protein candidates, and identification of homologue gene in Cacao Genome Database using data source "Theobroma cacao cv. Matina 1-6 v1.1" genome. Identification found that Thecc1EG011959t1 (EDS1), Thecc1EG006803t1 (EDS5), Thecc1EG013842t1 (ICS1), and Thecc1EG015614t1 (BG_PPAP) gene of Cacao Genome Database were Theobroma cacao genes that homolog to plant's resistance genes which highly possible to have similar functions of each gene's homologue gene.

IDPT: Insights into potential intrinsically disordered proteins through transcriptomic analysis of genes for prostate carcinoma epigenetic data.

PubMed

Mallik, Saurav; Sen, Sagnik; Maulik, Ujjwal

2016-07-15

Involvement of intrinsically disordered proteins (IDPs) with various dreadful diseases like cancer is an interesting research topic. In order to gain novel insights into the regulation of IDPs, in this article, we perform a transcriptomic analysis of mRNAs (genes) for transcripts encoding IDPs on a human multi-omics prostate carcinoma dataset having both gene expression and methylation data. In this regard, firstly the genes that consist of both the expression and methylation data, and that are corresponding to the cancer-related prostate-tissue-specific disordered proteins of MobiDb database, are selected. We apply standard t-test for determining differentially expressed genes as well as differentially methylated genes. A network having these genes and their targeter miRNAs from Diana Tarbase v7.0 database and corresponding Transcription Factors from TRANSFAC and ITFP databases, is then built. Thereafter, we perform literature search, and KEGG pathway and Gene Ontology analyses using DAVID database. Finally, we report several significant potential gene-markers (with the corresponding IDPs) that have inverse relationship between differential expression and methylation patterns, and that are hub genes of the TF-miRNA-gene network. Copyright © 2016 Elsevier B.V. All rights reserved.

Gene and protein nomenclature in public databases

PubMed Central

Fundel, Katrin; Zimmer, Ralf

2006-01-01

Background Frequently, several alternative names are in use for biological objects such as genes and proteins. Applications like manual literature search, automated text-mining, named entity identification, gene/protein annotation, and linking of knowledge from different information sources require the knowledge of all used names referring to a given gene or protein. Various organism-specific or general public databases aim at organizing knowledge about genes and proteins. These databases can be used for deriving gene and protein name dictionaries. So far, little is known about the differences between databases in terms of size, ambiguities and overlap. Results We compiled five gene and protein name dictionaries for each of the five model organisms (yeast, fly, mouse, rat, and human) from different organism-specific and general public databases. We analyzed the degree of ambiguity of gene and protein names within and between dictionaries, to a lexicon of common English words and domain-related non-gene terms, and we compared different data sources in terms of size of extracted dictionaries and overlap of synonyms between those. The study shows that the number of genes/proteins and synonyms covered in individual databases varies significantly for a given organism, and that the degree of ambiguity of synonyms varies significantly between different organisms. Furthermore, it shows that, despite considerable efforts of co-curation, the overlap of synonyms in different data sources is rather moderate and that the degree of ambiguity of gene names with common English words and domain-related non-gene terms varies depending on the considered organism. Conclusion In conclusion, these results indicate that the combination of data contained in different databases allows the generation of gene and protein name dictionaries that contain significantly more used names than dictionaries obtained from individual data sources. Furthermore, curation of combined dictionaries considerably increases size and decreases ambiguity. The entries of the curated synonym dictionary are available for manual querying, editing, and PubMed- or Google-search via the ProThesaurus-wiki. For automated querying via custom software, we offer a web service and an exemplary client application. PMID:16899134

IDENTIFICATION OF BIOLOGICALLY RELEVANT GENES USING A DATABASE OF RAT LIVER AND KIDNEY BASELINE GENE EXPRESSION

EPA Science Inventory

Microarray data from independent labs and studies can be compared to potentially identify toxicologically and biologically relevant genes. The Baseline Animal Database working group of HESI was formed to assess baseline gene expression from microarray data derived from control or...

KMeyeDB: a graphical database of mutations in genes that cause eye diseases.

PubMed

Kawamura, Takashi; Ohtsubo, Masafumi; Mitsuyama, Susumu; Ohno-Nakamura, Saho; Shimizu, Nobuyoshi; Minoshima, Shinsei

2010-06-01

KMeyeDB (http://mutview.dmb.med.keio.ac.jp/) is a database of human gene mutations that cause eye diseases. We have substantially enriched the amount of data in the database, which now contains information about the mutations of 167 human genes causing eye-related diseases including retinitis pigmentosa, cone-rod dystrophy, night blindness, Oguchi disease, Stargardt disease, macular degeneration, Leber congenital amaurosis, corneal dystrophy, cataract, glaucoma, retinoblastoma, Bardet-Biedl syndrome, and Usher syndrome. KMeyeDB is operated using the database software MutationView, which deals with various characters of mutations, gene structure, protein functional domains, and polymerase chain reaction (PCR) primers, as well as clinical data for each case. Users can access the database using an ordinary Internet browser with smooth user-interface, without user registration. The results are displayed on the graphical windows together with statistical calculations. All mutations and associated data have been collected from published articles. Careful data analysis with KMeyeDB revealed many interesting features regarding the mutations in 167 genes that cause 326 different types of eye diseases. Some genes are involved in multiple types of eye diseases, whereas several eye diseases are caused by different mutations in one gene.

An online model composition tool for system biology models

PubMed Central

2013-01-01

Background There are multiple representation formats for Systems Biology computational models, and the Systems Biology Markup Language (SBML) is one of the most widely used. SBML is used to capture, store, and distribute computational models by Systems Biology data sources (e.g., the BioModels Database) and researchers. Therefore, there is a need for all-in-one web-based solutions that support advance SBML functionalities such as uploading, editing, composing, visualizing, simulating, querying, and browsing computational models. Results We present the design and implementation of the Model Composition Tool (Interface) within the PathCase-SB (PathCase Systems Biology) web portal. The tool helps users compose systems biology models to facilitate the complex process of merging systems biology models. We also present three tools that support the model composition tool, namely, (1) Model Simulation Interface that generates a visual plot of the simulation according to user’s input, (2) iModel Tool as a platform for users to upload their own models to compose, and (3) SimCom Tool that provides a side by side comparison of models being composed in the same pathway. Finally, we provide a web site that hosts BioModels Database models and a separate web site that hosts SBML Test Suite models. Conclusions Model composition tool (and the other three tools) can be used with little or no knowledge of the SBML document structure. For this reason, students or anyone who wants to learn about systems biology will benefit from the described functionalities. SBML Test Suite models will be a nice starting point for beginners. And, for more advanced purposes, users will able to access and employ models of the BioModels Database as well. PMID:24006914

PLMItRNA, a database for mitochondrial tRNA genes and tRNAs in photosynthetic eukaryotes.

PubMed

Damiano, F; Gallerani, R; Liuni, S; Licciulli, F; Ceci, L R

2001-01-01

The PLMItRNA database for mitochondrial tRNA molecules and genes in VIRIDIPLANTAE: (green plants) [Volpetti,V., Gallerani,R., DeBenedetto,C., Liuni,S., Licciulli,F. and Ceci,L.R. (2000) Nucleic Acids Res., 28, 159-162] has been enlarged to include algae. The database now contains 436 genes and 16 tRNA entries relative to 25 higher plants, eight green algae, four red algae (RHODOPHYTAE:) and two STRAMENOPILES: The PLMItRNA database is accessible via the WWW at http://bio-www.ba.cnr.it:8000/PLMItRNA.

Genevar: a database and Java application for the analysis and visualization of SNP-gene associations in eQTL studies

PubMed Central

Yang, Tsun-Po; Beazley, Claude; Montgomery, Stephen B.; Dimas, Antigone S.; Gutierrez-Arcelus, Maria; Stranger, Barbara E.; Deloukas, Panos; Dermitzakis, Emmanouil T.

2010-01-01

Summary: Genevar (GENe Expression VARiation) is a database and Java tool designed to integrate multiple datasets, and provides analysis and visualization of associations between sequence variation and gene expression. Genevar allows researchers to investigate expression quantitative trait loci (eQTL) associations within a gene locus of interest in real time. The database and application can be installed on a standard computer in database mode and, in addition, on a server to share discoveries among affiliations or the broader community over the Internet via web services protocols. Availability: http://www.sanger.ac.uk/resources/software/genevar Contact: emmanouil.dermitzakis@unige.ch PMID:20702402

The construction of an EST database for Bombyx mori and its application

PubMed Central

Mita, Kazuei; Morimyo, Mitsuoki; Okano, Kazuhiro; Koike, Yoshiko; Nohata, Junko; Kawasaki, Hideki; Kadono-Okuda, Keiko; Yamamoto, Kimiko; Suzuki, Masataka G.; Shimada, Toru; Goldsmith, Marian R.; Maeda, Susumu

2003-01-01

To build a foundation for the complete genome analysis of Bombyx mori, we have constructed an EST database. Because gene expression patterns deeply depend on tissues as well as developmental stages, we analyzed many cDNA libraries prepared from various tissues and different developmental stages to cover the entire set of Bombyx genes. So far, the Bombyx EST database contains 35,000 ESTs from 36 cDNA libraries, which are grouped into ≈11,000 nonredundant ESTs with the average length of 1.25 kb. The comparison with FlyBase suggests that the present EST database, SilkBase, covers >55% of all genes of Bombyx. The fraction of library-specific ESTs in each cDNA library indicates that we have not yet reached saturation, showing the validity of our strategy for constructing an EST database to cover all genes. To tackle the coming saturation problem, we have checked two methods, subtraction and normalization, to increase coverage and decrease the number of housekeeping genes, resulting in a 5–11% increase of library-specific ESTs. The identification of a number of genes and comprehensive cloning of gene families have already emerged from the SilkBase search. Direct links of SilkBase with FlyBase and WormBase provide ready identification of candidate Lepidoptera-specific genes. PMID:14614147

A comprehensive aligned nifH gene database: a multipurpose tool for studies of nitrogen-fixing bacteria.

PubMed

Gaby, John Christian; Buckley, Daniel H

2014-01-01

We describe a nitrogenase gene sequence database that facilitates analysis of the evolution and ecology of nitrogen-fixing organisms. The database contains 32 954 aligned nitrogenase nifH sequences linked to phylogenetic trees and associated sequence metadata. The database includes 185 linked multigene entries including full-length nifH, nifD, nifK and 16S ribosomal RNA (rRNA) gene sequences. Evolutionary analyses enabled by the multigene entries support an ancient horizontal transfer of nitrogenase genes between Archaea and Bacteria and provide evidence that nifH has a different history of horizontal gene transfer from the nifDK enzyme core. Further analyses show that lineages in nitrogenase cluster I and cluster III have different rates of substitution within nifD, suggesting that nifD is under different selection pressure in these two lineages. Finally, we find that that the genetic divergence of nifH and 16S rRNA genes does not correlate well at sequence dissimilarity values used commonly to define microbial species, as stains having <3% sequence dissimilarity in their 16S rRNA genes can have up to 23% dissimilarity in nifH. The nifH database has a number of uses including phylogenetic and evolutionary analyses, the design and assessment of primers/probes and the evaluation of nitrogenase sequence diversity. Database URL: http://www.css.cornell.edu/faculty/buckley/nifh.htm.

A comprehensive aligned nifH gene database: a multipurpose tool for studies of nitrogen-fixing bacteria

PubMed Central

Gaby, John Christian; Buckley, Daniel H.

2014-01-01

We describe a nitrogenase gene sequence database that facilitates analysis of the evolution and ecology of nitrogen-fixing organisms. The database contains 32 954 aligned nitrogenase nifH sequences linked to phylogenetic trees and associated sequence metadata. The database includes 185 linked multigene entries including full-length nifH, nifD, nifK and 16S ribosomal RNA (rRNA) gene sequences. Evolutionary analyses enabled by the multigene entries support an ancient horizontal transfer of nitrogenase genes between Archaea and Bacteria and provide evidence that nifH has a different history of horizontal gene transfer from the nifDK enzyme core. Further analyses show that lineages in nitrogenase cluster I and cluster III have different rates of substitution within nifD, suggesting that nifD is under different selection pressure in these two lineages. Finally, we find that that the genetic divergence of nifH and 16S rRNA genes does not correlate well at sequence dissimilarity values used commonly to define microbial species, as stains having <3% sequence dissimilarity in their 16S rRNA genes can have up to 23% dissimilarity in nifH. The nifH database has a number of uses including phylogenetic and evolutionary analyses, the design and assessment of primers/probes and the evaluation of nitrogenase sequence diversity. Database URL: http://www.css.cornell.edu/faculty/buckley/nifh.htm PMID:24501396

dbWFA: a web-based database for functional annotation of Triticum aestivum transcripts

PubMed Central

Vincent, Jonathan; Dai, Zhanwu; Ravel, Catherine; Choulet, Frédéric; Mouzeyar, Said; Bouzidi, M. Fouad; Agier, Marie; Martre, Pierre

2013-01-01

The functional annotation of genes based on sequence homology with genes from model species genomes is time-consuming because it is necessary to mine several unrelated databases. The aim of the present work was to develop a functional annotation database for common wheat Triticum aestivum (L.). The database, named dbWFA, is based on the reference NCBI UniGene set, an expressed gene catalogue built by expressed sequence tag clustering, and on full-length coding sequences retrieved from the TriFLDB database. Information from good-quality heterogeneous sources, including annotations for model plant species Arabidopsis thaliana (L.) Heynh. and Oryza sativa L., was gathered and linked to T. aestivum sequences through BLAST-based homology searches. Even though the complexity of the transcriptome cannot yet be fully appreciated, we developed a tool to easily and promptly obtain information from multiple functional annotation systems (Gene Ontology, MapMan bin codes, MIPS Functional Categories, PlantCyc pathway reactions and TAIR gene families). The use of dbWFA is illustrated here with several query examples. We were able to assign a putative function to 45% of the UniGenes and 81% of the full-length coding sequences from TriFLDB. Moreover, comparison of the annotation of the whole T. aestivum UniGene set along with curated annotations of the two model species assessed the accuracy of the annotation provided by dbWFA. To further illustrate the use of dbWFA, genes specifically expressed during the early cell division or late storage polymer accumulation phases of T. aestivum grain development were identified using a clustering analysis and then annotated using dbWFA. The annotation of these two sets of genes was consistent with previous analyses of T. aestivum grain transcriptomes and proteomes. Database URL: urgi.versailles.inra.fr/dbWFA/ PMID:23660284

Database resources of the National Center for Biotechnology Information.

PubMed

2016-01-04

The National Center for Biotechnology Information (NCBI) provides a large suite of online resources for biological information and data, including the GenBank(®) nucleic acid sequence database and the PubMed database of citations and abstracts for published life science journals. Additional NCBI resources focus on literature (PubMed Central (PMC), Bookshelf and PubReader), health (ClinVar, dbGaP, dbMHC, the Genetic Testing Registry, HIV-1/Human Protein Interaction Database and MedGen), genomes (BioProject, Assembly, Genome, BioSample, dbSNP, dbVar, Epigenomics, the Map Viewer, Nucleotide, Probe, RefSeq, Sequence Read Archive, the Taxonomy Browser and the Trace Archive), genes (Gene, Gene Expression Omnibus (GEO), HomoloGene, PopSet and UniGene), proteins (Protein, the Conserved Domain Database (CDD), COBALT, Conserved Domain Architecture Retrieval Tool (CDART), the Molecular Modeling Database (MMDB) and Protein Clusters) and chemicals (Biosystems and the PubChem suite of small molecule databases). The Entrez system provides search and retrieval operations for most of these databases. Augmenting many of the web applications are custom implementations of the BLAST program optimized to search specialized datasets. All of these resources can be accessed through the NCBI home page at www.ncbi.nlm.nih.gov. Published by Oxford University Press on behalf of Nucleic Acids Research 2015. This work is written by (a) US Government employee(s) and is in the public domain in the US.

Database resources of the National Center for Biotechnology Information.

PubMed

2015-01-01

The National Center for Biotechnology Information (NCBI) provides a large suite of online resources for biological information and data, including the GenBank(®) nucleic acid sequence database and the PubMed database of citations and abstracts for published life science journals. Additional NCBI resources focus on literature (Bookshelf, PubMed Central (PMC) and PubReader); medical genetics (ClinVar, dbMHC, the Genetic Testing Registry, HIV-1/Human Protein Interaction Database and MedGen); genes and genomics (BioProject, BioSample, dbSNP, dbVar, Epigenomics, Gene, Gene Expression Omnibus (GEO), Genome, HomoloGene, the Map Viewer, Nucleotide, PopSet, Probe, RefSeq, Sequence Read Archive, the Taxonomy Browser, Trace Archive and UniGene); and proteins and chemicals (Biosystems, COBALT, the Conserved Domain Database (CDD), the Conserved Domain Architecture Retrieval Tool (CDART), the Molecular Modeling Database (MMDB), Protein Clusters, Protein and the PubChem suite of small molecule databases). The Entrez system provides search and retrieval operations for many of these databases. Augmenting many of the Web applications are custom implementations of the BLAST program optimized to search specialized data sets. All of these resources can be accessed through the NCBI home page at http://www.ncbi.nlm.nih.gov. Published by Oxford University Press on behalf of Nucleic Acids Research 2014. This work is written by (a) US Government employee(s) and is in the public domain in the US.

RegNetwork: an integrated database of transcriptional and post-transcriptional regulatory networks in human and mouse

PubMed Central

Liu, Zhi-Ping; Wu, Canglin; Miao, Hongyu; Wu, Hulin

2015-01-01

Transcriptional and post-transcriptional regulation of gene expression is of fundamental importance to numerous biological processes. Nowadays, an increasing amount of gene regulatory relationships have been documented in various databases and literature. However, to more efficiently exploit such knowledge for biomedical research and applications, it is necessary to construct a genome-wide regulatory network database to integrate the information on gene regulatory relationships that are widely scattered in many different places. Therefore, in this work, we build a knowledge-based database, named ‘RegNetwork’, of gene regulatory networks for human and mouse by collecting and integrating the documented regulatory interactions among transcription factors (TFs), microRNAs (miRNAs) and target genes from 25 selected databases. Moreover, we also inferred and incorporated potential regulatory relationships based on transcription factor binding site (TFBS) motifs into RegNetwork. As a result, RegNetwork contains a comprehensive set of experimentally observed or predicted transcriptional and post-transcriptional regulatory relationships, and the database framework is flexibly designed for potential extensions to include gene regulatory networks for other organisms in the future. Based on RegNetwork, we characterized the statistical and topological properties of genome-wide regulatory networks for human and mouse, we also extracted and interpreted simple yet important network motifs that involve the interplays between TF-miRNA and their targets. In summary, RegNetwork provides an integrated resource on the prior information for gene regulatory relationships, and it enables us to further investigate context-specific transcriptional and post-transcriptional regulatory interactions based on domain-specific experimental data. Database URL: http://www.regnetworkweb.org PMID:26424082

MEPD: a Medaka gene expression pattern database

PubMed Central

Henrich, Thorsten; Ramialison, Mirana; Quiring, Rebecca; Wittbrodt, Beate; Furutani-Seiki, Makoto; Wittbrodt, Joachim; Kondoh, Hisato

2003-01-01

The Medaka Expression Pattern Database (MEPD) stores and integrates information of gene expression during embryonic development of the small freshwater fish Medaka (Oryzias latipes). Expression patterns of genes identified by ESTs are documented by images and by descriptions through parameters such as staining intensity, category and comments and through a comprehensive, hierarchically organized dictionary of anatomical terms. Sequences of the ESTs are available and searchable through BLAST. ESTs in the database are clustered upon entry and have been blasted against public data-bases. The BLAST results are updated regularly, stored within the database and searchable. The MEPD is a project within the Medaka Genome Initiative (MGI) and entries will be interconnected to integrated genomic map databases. MEPD is accessible through the WWW at http://medaka.dsp.jst.go.jp/MEPD. PMID:12519950

RPG: the Ribosomal Protein Gene database.

PubMed

Nakao, Akihiro; Yoshihama, Maki; Kenmochi, Naoya

2004-01-01

RPG (http://ribosome.miyazaki-med.ac.jp/) is a new database that provides detailed information about ribosomal protein (RP) genes. It contains data from humans and other organisms, including Drosophila melanogaster, Caenorhabditis elegans, Saccharo myces cerevisiae, Methanococcus jannaschii and Escherichia coli. Users can search the database by gene name and organism. Each record includes sequences (genomic, cDNA and amino acid sequences), intron/exon structures, genomic locations and information about orthologs. In addition, users can view and compare the gene structures of the above organisms and make multiple amino acid sequence alignments. RPG also provides information on small nucleolar RNAs (snoRNAs) that are encoded in the introns of RP genes.

RPG: the Ribosomal Protein Gene database

PubMed Central

Nakao, Akihiro; Yoshihama, Maki; Kenmochi, Naoya

2004-01-01

RPG (http://ribosome.miyazaki-med.ac.jp/) is a new database that provides detailed information about ribosomal protein (RP) genes. It contains data from humans and other organisms, including Drosophila melanogaster, Caenorhabditis elegans, Saccharo myces cerevisiae, Methanococcus jannaschii and Escherichia coli. Users can search the database by gene name and organism. Each record includes sequences (genomic, cDNA and amino acid sequences), intron/exon structures, genomic locations and information about orthologs. In addition, users can view and compare the gene structures of the above organisms and make multiple amino acid sequence alignments. RPG also provides information on small nucleolar RNAs (snoRNAs) that are encoded in the introns of RP genes. PMID:14681386

Identification and characterization of a new multigene family in the human MHC: A candidate autoimmune disease susceptibility element (3.8-1)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Harris, J.M.; Venditti, C.P.; Chorney, M.J.

1994-09-01

An association between idiopathic hemochromatosis (HFE) and the HLA-A3 locus has been previously well-established. In an attempt to identify potential HFE candidate genes, a genomic DNA fragment distal to the HLA-A9 breakpoint was used to screen a B cell cDNA library; a member (3.8-1) of a new multigene family, composed of five distinct genomic cross-reactive fragments, was identified. Clone 3.8-1 represents the 3{prime} end of 9.6 kb transcript which is expressed in multiple tissues including the spleen, thymus, lung and kidney. Sequencing and genome database analysis indicate that 3.8-1 is unique, with no homology to any known entries. The genomicmore » residence of 3-8.1, defined by polymorphism analysis and physical mapping using YAC clones, appears to be absent from the genomes of higher primates, although four other cross-reactivities are maintained. The absence of this gene as well as other probes which map in the TNF to HLA-B interval, suggest that this portion of the human HMC, located between the Class I and Class III regions, arose in humans as the result of a post-speciation insertional event. The large size of the 3.8-1 gene and the possible categorization of 3.8-1 as a human-specific gene are significant given the genetic data that place an autoimmune susceptibility element for IDDM and myasthenia gravis in the precise region where this gene resides. In an attempt to isolate the 5{prime} end of this large transcript, we have constructed a cosmid contig which encompasses the genomic locus of this gene and are progressively isolating coding sequences by exon trapping.« less

Characteristics of genomic signatures derived using univariate methods and mechanistically anchored functional descriptors for predicting drug- and xenobiotic-induced nephrotoxicity.

PubMed

Shi, Weiwei; Bugrim, Andrej; Nikolsky, Yuri; Nikolskya, Tatiana; Brennan, Richard J

2008-01-01

ABSTRACT The ideal toxicity biomarker is composed of the properties of prediction (is detected prior to traditional pathological signs of injury), accuracy (high sensitivity and specificity), and mechanistic relationships to the endpoint measured (biological relevance). Gene expression-based toxicity biomarkers ("signatures") have shown good predictive power and accuracy, but are difficult to interpret biologically. We have compared different statistical methods of feature selection with knowledge-based approaches, using GeneGo's database of canonical pathway maps, to generate gene sets for the classification of renal tubule toxicity. The gene set selection algorithms include four univariate analyses: t-statistics, fold-change, B-statistics, and RankProd, and their combination and overlap for the identification of differentially expressed probes. Enrichment analysis following the results of the four univariate analyses, Hotelling T-square test, and, finally out-of-bag selection, a variant of cross-validation, were used to identify canonical pathway maps-sets of genes coordinately involved in key biological processes-with classification power. Differentially expressed genes identified by the different statistical univariate analyses all generated reasonably performing classifiers of tubule toxicity. Maps identified by enrichment analysis or Hotelling T-square had lower classification power, but highlighted perturbed lipid homeostasis as a common discriminator of nephrotoxic treatments. The out-of-bag method yielded the best functionally integrated classifier. The map "ephrins signaling" performed comparably to a classifier derived using sparse linear programming, a machine learning algorithm, and represents a signaling network specifically involved in renal tubule development and integrity. Such functional descriptors of toxicity promise to better integrate predictive toxicogenomics with mechanistic analysis, facilitating the interpretation and risk assessment of predictive genomic investigations.

The merged basins of signal transduction pathways in spatiotemporal cell biology.

PubMed

Hou, Yingchun; Hou, Yang; He, Siyu; Ma, Caixia; Sun, Mengyao; He, Huimin; Gao, Ning

2014-03-01

Numerous evidences have indicated that a signal system is composed by signal pathways, each pathway is composed by sub-pathways, and the sub-pathway is composed by the original signal terminals initiated with a protein/gene. We infer the terminal signals merged signal transduction system as "signal basin". In this article, we discussed the composition and regulation of signal basins, and the relationship between the signal basin control and triple W of spatiotemporal cell biology. Finally, we evaluated the importance of the systemic regulation to gene expression by signal basins under triple W. We hope our discussion will be the beginning to cause the attention for this area from the scientists of life science. © 2013 Wiley Periodicals, Inc.

PGMapper: a web-based tool linking phenotype to genes.

PubMed

Xiong, Qing; Qiu, Yuhui; Gu, Weikuan

2008-04-01

With the availability of whole genome sequence in many species, linkage analysis, positional cloning and microarray are gradually becoming powerful tools for investigating the links between phenotype and genotype or genes. However, in these methods, causative genes underlying a quantitative trait locus, or a disease, are usually located within a large genomic region or a large set of genes. Examining the function of every gene is very time consuming and needs to retrieve and integrate the information from multiple databases or genome resources. PGMapper is a software tool for automatically matching phenotype to genes from a defined genome region or a group of given genes by combining the mapping information from the Ensembl database and gene function information from the OMIM and PubMed databases. PGMapper is currently available for candidate gene search of human, mouse, rat, zebrafish and 12 other species. Available online at http://www.genediscovery.org/pgmapper/index.jsp.

UniGene Tabulator: a full parser for the UniGene format.

PubMed

Lenzi, Luca; Frabetti, Flavia; Facchin, Federica; Casadei, Raffaella; Vitale, Lorenza; Canaider, Silvia; Carinci, Paolo; Zannotti, Maria; Strippoli, Pierluigi

2006-10-15

UniGene Tabulator 1.0 provides a solution for full parsing of UniGene flat file format; it implements a structured graphical representation of each data field present in UniGene following import into a common database managing system usable in a personal computer. This database includes related tables for sequence, protein similarity, sequence-tagged site (STS) and transcript map interval (TXMAP) data, plus a summary table where each record represents a UniGene cluster. UniGene Tabulator enables full local management of UniGene data, allowing parsing, querying, indexing, retrieving, exporting and analysis of UniGene data in a relational database form, usable on Macintosh (OS X 10.3.9 or later) and Windows (2000, with service pack 4, XP, with service pack 2 or later) operating systems-based computers. The current release, including both the FileMaker runtime applications, is freely available at http://apollo11.isto.unibo.it/software/

DRUMS: a human disease related unique gene mutation search engine.

PubMed

Li, Zuofeng; Liu, Xingnan; Wen, Jingran; Xu, Ye; Zhao, Xin; Li, Xuan; Liu, Lei; Zhang, Xiaoyan

2011-10-01

With the completion of the human genome project and the development of new methods for gene variant detection, the integration of mutation data and its phenotypic consequences has become more important than ever. Among all available resources, locus-specific databases (LSDBs) curate one or more specific genes' mutation data along with high-quality phenotypes. Although some genotype-phenotype data from LSDB have been integrated into central databases little effort has been made to integrate all these data by a search engine approach. In this work, we have developed disease related unique gene mutation search engine (DRUMS), a search engine for human disease related unique gene mutation as a convenient tool for biologists or physicians to retrieve gene variant and related phenotype information. Gene variant and phenotype information were stored in a gene-centred relational database. Moreover, the relationships between mutations and diseases were indexed by the uniform resource identifier from LSDB, or another central database. By querying DRUMS, users can access the most popular mutation databases under one interface. DRUMS could be treated as a domain specific search engine. By using web crawling, indexing, and searching technologies, it provides a competitively efficient interface for searching and retrieving mutation data and their relationships to diseases. The present system is freely accessible at http://www.scbit.org/glif/new/drums/index.html. © 2011 Wiley-Liss, Inc.

The Candidate Cancer Gene Database: a database of cancer driver genes from forward genetic screens in mice.

PubMed

Abbott, Kenneth L; Nyre, Erik T; Abrahante, Juan; Ho, Yen-Yi; Isaksson Vogel, Rachel; Starr, Timothy K

2015-01-01

Identification of cancer driver gene mutations is crucial for advancing cancer therapeutics. Due to the overwhelming number of passenger mutations in the human tumor genome, it is difficult to pinpoint causative driver genes. Using transposon mutagenesis in mice many laboratories have conducted forward genetic screens and identified thousands of candidate driver genes that are highly relevant to human cancer. Unfortunately, this information is difficult to access and utilize because it is scattered across multiple publications using different mouse genome builds and strength metrics. To improve access to these findings and facilitate meta-analyses, we developed the Candidate Cancer Gene Database (CCGD, http://ccgd-starrlab.oit.umn.edu/). The CCGD is a manually curated database containing a unified description of all identified candidate driver genes and the genomic location of transposon common insertion sites (CISs) from all currently published transposon-based screens. To demonstrate relevance to human cancer, we performed a modified gene set enrichment analysis using KEGG pathways and show that human cancer pathways are highly enriched in the database. We also used hierarchical clustering to identify pathways enriched in blood cancers compared to solid cancers. The CCGD is a novel resource available to scientists interested in the identification of genetic drivers of cancer. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Transactional Database Transformation and Its Application in Prioritizing Human Disease Genes

PubMed Central

Xiang, Yang; Payne, Philip R.O.; Huang, Kun

2013-01-01

Binary (0,1) matrices, commonly known as transactional databases, can represent many application data, including gene-phenotype data where “1” represents a confirmed gene-phenotype relation and “0” represents an unknown relation. It is natural to ask what information is hidden behind these “0”s and “1”s. Unfortunately, recent matrix completion methods, though very effective in many cases, are less likely to infer something interesting from these (0,1)-matrices. To answer this challenge, we propose IndEvi, a very succinct and effective algorithm to perform independent-evidence-based transactional database transformation. Each entry of a (0,1)-matrix is evaluated by “independent evidence” (maximal supporting patterns) extracted from the whole matrix for this entry. The value of an entry, regardless of its value as 0 or 1, has completely no effect for its independent evidence. The experiment on a gene-phenotype database shows that our method is highly promising in ranking candidate genes and predicting unknown disease genes. PMID:21422495

Evaluation of techniques for increasing recall in a dictionary approach to gene and protein name identification.

PubMed

Schuemie, Martijn J; Mons, Barend; Weeber, Marc; Kors, Jan A

2007-06-01

Gene and protein name identification in text requires a dictionary approach to relate synonyms to the same gene or protein, and to link names to external databases. However, existing dictionaries are incomplete. We investigate two complementary methods for automatic generation of a comprehensive dictionary: combination of information from existing gene and protein databases and rule-based generation of spelling variations. Both methods have been reported in literature before, but have hitherto not been combined and evaluated systematically. We combined gene and protein names from several existing databases of four different organisms. The combined dictionaries showed a substantial increase in recall on three different test sets, as compared to any single database. Application of 23 spelling variation rules to the combined dictionaries further increased recall. However, many rules appeared to have no effect and some appear to have a detrimental effect on precision.

Bioinformatic analysis of the nucleotide binding site-encoding disease-resistance genes in foxtail millet (Setaria italica (L.) Beauv.).

PubMed

Zhu, Y B; Xie, X Q; Li, Z Y; Bai, H; Dong, L; Dong, Z P; Dong, J G

2014-08-28

The nucleotide-binding site (NBS) disease-resistance genes are the largest category of plant disease-resistance gene analogs. The complete set of disease-resistant candidate genes, which encode the NBS sequence, was filtered in the genomes of two varieties of foxtail millet (Yugu1 and 'Zhang gu'). This study investigated a number of characteristics of the putative NBS genes, such as structural diversity and phylogenetic relationships. A total of 269 and 281 NBS-coding sequences were identified in Yugu1 and 'Zhang gu', respectively. When the two databases were compared, 72 genes were found to be identical and 164 genes showed more than 90% similarity. Physical positioning and gene family analysis of the NBS disease-resistance genes in the genome revealed that the number of genes on each chromosome was similar in both varieties. The eighth chromosome contained the largest number of genes and the ninth chromosome contained the lowest number of genes. Exactly 34 gene clusters containing the 161 genes were found in the Yugu1 genome, with each cluster containing 4.7 genes on average. In comparison, the 'Zhang gu' genome possessed 28 gene clusters, which had 151 genes, with an average of 5.4 genes in each cluster. The largest gene cluster, located on the eighth chromosome, contained 12 genes in the Yugu1 database, whereas it contained 16 genes in the 'Zhang gu' database. The classification results showed that the CC-NBS-LRR gene made up the largest part of each chromosome in the two databases. Two TIR-NBS genes were also found in the Yugu1 genome.

SinEx DB: a database for single exon coding sequences in mammalian genomes.

PubMed

Jorquera, Roddy; Ortiz, Rodrigo; Ossandon, F; Cárdenas, Juan Pablo; Sepúlveda, Rene; González, Carolina; Holmes, David S

2016-01-01

Eukaryotic genes are typically interrupted by intragenic, noncoding sequences termed introns. However, some genes lack introns in their coding sequence (CDS) and are generally known as 'single exon genes' (SEGs). In this work, a SEG is defined as a nuclear, protein-coding gene that lacks introns in its CDS. Whereas, many public databases of Eukaryotic multi-exon genes are available, there are only two specialized databases for SEGs. The present work addresses the need for a more extensive and diverse database by creating SinEx DB, a publicly available, searchable database of predicted SEGs from 10 completely sequenced mammalian genomes including human. SinEx DB houses the DNA and protein sequence information of these SEGs and includes their functional predictions (KOG) and the relative distribution of these functions within species. The information is stored in a relational database built with My SQL Server 5.1.33 and the complete dataset of SEG sequences and their functional predictions are available for downloading. SinEx DB can be interrogated by: (i) a browsable phylogenetic schema, (ii) carrying out BLAST searches to the in-house SinEx DB of SEGs and (iii) via an advanced search mode in which the database can be searched by key words and any combination of searches by species and predicted functions. SinEx DB provides a rich source of information for advancing our understanding of the evolution and function of SEGs.Database URL: www.sinex.cl. © The Author(s) 2016. Published by Oxford University Press.

FlyAtlas: database of gene expression in the tissues of Drosophila melanogaster

PubMed Central

Robinson, Scott W.; Herzyk, Pawel; Dow, Julian A. T.; Leader, David P.

2013-01-01

The FlyAtlas resource contains data on the expression of the genes of Drosophila melanogaster in different tissues (currently 25—17 adult and 8 larval) obtained by hybridization of messenger RNA to Affymetrix Drosophila Genome 2 microarrays. The microarray probe sets cover 13 250 Drosophila genes, detecting 12 533 in an unambiguous manner. The data underlying the original web application (http://flyatlas.org) have been restructured into a relational database and a Java servlet written to provide a new web interface, FlyAtlas 2 (http://flyatlas.gla.ac.uk/), which allows several additional queries. Users can retrieve data for individual genes or for groups of genes belonging to the same or related ontological categories. Assistance in selecting valid search terms is provided by an Ajax ‘autosuggest’ facility that polls the database as the user types. Searches can also focus on particular tissues, and data can be retrieved for the most highly expressed genes, for genes of a particular category with above-average expression or for genes with the greatest difference in expression between the larval and adult stages. A novel facility allows the database to be queried with a specific gene to find other genes with a similar pattern of expression across the different tissues. PMID:23203866

FlyAtlas: database of gene expression in the tissues of Drosophila melanogaster.

PubMed

Robinson, Scott W; Herzyk, Pawel; Dow, Julian A T; Leader, David P

2013-01-01

The FlyAtlas resource contains data on the expression of the genes of Drosophila melanogaster in different tissues (currently 25-17 adult and 8 larval) obtained by hybridization of messenger RNA to Affymetrix Drosophila Genome 2 microarrays. The microarray probe sets cover 13,250 Drosophila genes, detecting 12,533 in an unambiguous manner. The data underlying the original web application (http://flyatlas.org) have been restructured into a relational database and a Java servlet written to provide a new web interface, FlyAtlas 2 (http://flyatlas.gla.ac.uk/), which allows several additional queries. Users can retrieve data for individual genes or for groups of genes belonging to the same or related ontological categories. Assistance in selecting valid search terms is provided by an Ajax 'autosuggest' facility that polls the database as the user types. Searches can also focus on particular tissues, and data can be retrieved for the most highly expressed genes, for genes of a particular category with above-average expression or for genes with the greatest difference in expression between the larval and adult stages. A novel facility allows the database to be queried with a specific gene to find other genes with a similar pattern of expression across the different tissues.

NABIC marker database: A molecular markers information network of agricultural crops.

PubMed

Kim, Chang-Kug; Seol, Young-Joo; Lee, Dong-Jun; Jeong, In-Seon; Yoon, Ung-Han; Lee, Gang-Seob; Hahn, Jang-Ho; Park, Dong-Suk

2013-01-01

In 2013, National Agricultural Biotechnology Information Center (NABIC) reconstructs a molecular marker database for useful genetic resources. The web-based marker database consists of three major functional categories: map viewer, RSN marker and gene annotation. It provides 7250 marker locations, 3301 RSN marker property, 3280 molecular marker annotation information in agricultural plants. The individual molecular marker provides information such as marker name, expressed sequence tag number, gene definition and general marker information. This updated marker-based database provides useful information through a user-friendly web interface that assisted in tracing any new structures of the chromosomes and gene positional functions using specific molecular markers. The database is available for free at http://nabic.rda.go.kr/gere/rice/molecularMarkers/

Update of the Diatom EST Database: a new tool for digital transcriptomics

PubMed Central

Maheswari, Uma; Mock, Thomas; Armbrust, E. Virginia; Bowler, Chris

2009-01-01

The Diatom Expressed Sequence Tag (EST) Database was constructed to provide integral access to ESTs from these ecologically and evolutionarily interesting microalgae. It has now been updated with 130 000 Phaeodactylum tricornutum ESTs from 16 cDNA libraries and 77 000 Thalassiosira pseudonana ESTs from seven libraries, derived from cells grown in different nutrient and stress regimes. The updated relational database incorporates results from statistical analyses such as log-likelihood ratios and hierarchical clustering, which help to identify differentially expressed genes under different conditions, and allow similarities in gene expression in different libraries to be investigated in a functional context. The database also incorporates links to the recently sequenced genomes of P. tricornutum and T. pseudonana, enabling an easy cross-talk between the expression pattern of diatom orthologs and the genome browsers. These improvements will facilitate exploration of diatom responses to conditions of ecological relevance and will aid gene function identification of diatom-specific genes and in silico gene prediction in this largely unexplored class of eukaryotes. The updated Diatom EST Database is available at http://www.biologie.ens.fr/diatomics/EST3. PMID:19029140

PlantRGDB: A Database of Plant Retrocopied Genes.

PubMed

Wang, Yi

2017-01-01

RNA-based gene duplication, known as retrocopy, plays important roles in gene origination and genome evolution. The genomes of many plants have been sequenced, offering an opportunity to annotate and mine the retrocopies in plant genomes. However, comprehensive and unified annotation of retrocopies in these plants is still lacking. In this study I constructed the PlantRGDB (Plant Retrocopied Gene DataBase), the first database of plant retrocopies, to provide a putatively complete centralized list of retrocopies in plant genomes. The database is freely accessible at http://probes.pw.usda.gov/plantrgdb or http://aegilops.wheat.ucdavis.edu/plantrgdb. It currently integrates 49 plant species and 38,997 retrocopies along with characterization information. PlantRGDB provides a user-friendly web interface for searching, browsing and downloading the retrocopies in the database. PlantRGDB also offers graphical viewer-integrated sequence information for displaying the structure of each retrocopy. The attributes of the retrocopies of each species are reported using a browse function. In addition, useful tools, such as an advanced search and BLAST, are available to search the database more conveniently. In conclusion, the database will provide a web platform for obtaining valuable insight into the generation of retrocopies and will supplement research on gene duplication and genome evolution in plants. © The Author 2017. Published by Oxford University Press on behalf of Japanese Society of Plant Physiologists. All rights reserved. For permissions, please email: journals.permissions@oup.com.

The Finnish disease heritage database (FinDis) update-a database for the genes mutated in the Finnish disease heritage brought to the next-generation sequencing era.

PubMed

Polvi, Anne; Linturi, Henna; Varilo, Teppo; Anttonen, Anna-Kaisa; Byrne, Myles; Fokkema, Ivo F A C; Almusa, Henrikki; Metzidis, Anthony; Avela, Kristiina; Aula, Pertti; Kestilä, Marjo; Muilu, Juha

2013-11-01

The Finnish Disease Heritage Database (FinDis) (http://findis.org) was originally published in 2004 as a centralized information resource for rare monogenic diseases enriched in the Finnish population. The FinDis database originally contained 405 causative variants for 30 diseases. At the time, the FinDis database was a comprehensive collection of data, but since 1994, a large amount of new information has emerged, making the necessity to update the database evident. We collected information and updated the database to contain genes and causative variants for 35 diseases, including six more genes and more than 1,400 additional disease-causing variants. Information for causative variants for each gene is collected under the LOVD 3.0 platform, enabling easy updating. The FinDis portal provides a centralized resource and user interface to link information on each disease and gene with variant data in the LOVD 3.0 platform. The software written to achieve this has been open-sourced and made available on GitHub (http://github.com/findis-db), allowing biomedical institutions in other countries to present their national data in a similar way, and to both contribute to, and benefit from, standardized variation data. The updated FinDis portal provides a unique resource to assist patient diagnosis, research, and the development of new cures. © 2013 WILEY PERIODICALS, INC.

GIGA: a simple, efficient algorithm for gene tree inference in the genomic age

PubMed Central

2010-01-01

Background Phylogenetic relationships between genes are not only of theoretical interest: they enable us to learn about human genes through the experimental work on their relatives in numerous model organisms from bacteria to fruit flies and mice. Yet the most commonly used computational algorithms for reconstructing gene trees can be inaccurate for numerous reasons, both algorithmic and biological. Additional information beyond gene sequence data has been shown to improve the accuracy of reconstructions, though at great computational cost. Results We describe a simple, fast algorithm for inferring gene phylogenies, which makes use of information that was not available prior to the genomic age: namely, a reliable species tree spanning much of the tree of life, and knowledge of the complete complement of genes in a species' genome. The algorithm, called GIGA, constructs trees agglomeratively from a distance matrix representation of sequences, using simple rules to incorporate this genomic age information. GIGA makes use of a novel conceptualization of gene trees as being composed of orthologous subtrees (containing only speciation events), which are joined by other evolutionary events such as gene duplication or horizontal gene transfer. An important innovation in GIGA is that, at every step in the agglomeration process, the tree is interpreted/reinterpreted in terms of the evolutionary events that created it. Remarkably, GIGA performs well even when using a very simple distance metric (pairwise sequence differences) and no distance averaging over clades during the tree construction process. Conclusions GIGA is efficient, allowing phylogenetic reconstruction of very large gene families and determination of orthologs on a large scale. It is exceptionally robust to adding more gene sequences, opening up the possibility of creating stable identifiers for referring to not only extant genes, but also their common ancestors. We compared trees produced by GIGA to those in the TreeFam database, and they were very similar in general, with most differences likely due to poor alignment quality. However, some remaining differences are algorithmic, and can be explained by the fact that GIGA tends to put a larger emphasis on minimizing gene duplication and deletion events. PMID:20534164

GIGA: a simple, efficient algorithm for gene tree inference in the genomic age.

PubMed

Thomas, Paul D

2010-06-09

Phylogenetic relationships between genes are not only of theoretical interest: they enable us to learn about human genes through the experimental work on their relatives in numerous model organisms from bacteria to fruit flies and mice. Yet the most commonly used computational algorithms for reconstructing gene trees can be inaccurate for numerous reasons, both algorithmic and biological. Additional information beyond gene sequence data has been shown to improve the accuracy of reconstructions, though at great computational cost. We describe a simple, fast algorithm for inferring gene phylogenies, which makes use of information that was not available prior to the genomic age: namely, a reliable species tree spanning much of the tree of life, and knowledge of the complete complement of genes in a species' genome. The algorithm, called GIGA, constructs trees agglomeratively from a distance matrix representation of sequences, using simple rules to incorporate this genomic age information. GIGA makes use of a novel conceptualization of gene trees as being composed of orthologous subtrees (containing only speciation events), which are joined by other evolutionary events such as gene duplication or horizontal gene transfer. An important innovation in GIGA is that, at every step in the agglomeration process, the tree is interpreted/reinterpreted in terms of the evolutionary events that created it. Remarkably, GIGA performs well even when using a very simple distance metric (pairwise sequence differences) and no distance averaging over clades during the tree construction process. GIGA is efficient, allowing phylogenetic reconstruction of very large gene families and determination of orthologs on a large scale. It is exceptionally robust to adding more gene sequences, opening up the possibility of creating stable identifiers for referring to not only extant genes, but also their common ancestors. We compared trees produced by GIGA to those in the TreeFam database, and they were very similar in general, with most differences likely due to poor alignment quality. However, some remaining differences are algorithmic, and can be explained by the fact that GIGA tends to put a larger emphasis on minimizing gene duplication and deletion events.

Ensemble gene function prediction database reveals genes important for complex I formation in Arabidopsis thaliana.

PubMed

Hansen, Bjoern Oest; Meyer, Etienne H; Ferrari, Camilla; Vaid, Neha; Movahedi, Sara; Vandepoele, Klaas; Nikoloski, Zoran; Mutwil, Marek

2018-03-01

Recent advances in gene function prediction rely on ensemble approaches that integrate results from multiple inference methods to produce superior predictions. Yet, these developments remain largely unexplored in plants. We have explored and compared two methods to integrate 10 gene co-function networks for Arabidopsis thaliana and demonstrate how the integration of these networks produces more accurate gene function predictions for a larger fraction of genes with unknown function. These predictions were used to identify genes involved in mitochondrial complex I formation, and for five of them, we confirmed the predictions experimentally. The ensemble predictions are provided as a user-friendly online database, EnsembleNet. The methods presented here demonstrate that ensemble gene function prediction is a powerful method to boost prediction performance, whereas the EnsembleNet database provides a cutting-edge community tool to guide experimentalists. © 2017 The Authors. New Phytologist © 2017 New Phytologist Trust.

MGDB: crossing the marker genes of a user microarray with a database of public-microarrays marker genes.

PubMed

Huerta, Mario; Munyi, Marc; Expósito, David; Querol, Enric; Cedano, Juan

2014-06-15

The microarrays performed by scientific teams grow exponentially. These microarray data could be useful for researchers around the world, but unfortunately they are underused. To fully exploit these data, it is necessary (i) to extract these data from a repository of the high-throughput gene expression data like Gene Expression Omnibus (GEO) and (ii) to make the data from different microarrays comparable with tools easy to use for scientists. We have developed these two solutions in our server, implementing a database of microarray marker genes (Marker Genes Data Base). This database contains the marker genes of all GEO microarray datasets and it is updated monthly with the new microarrays from GEO. Thus, researchers can see whether the marker genes of their microarray are marker genes in other microarrays in the database, expanding the analysis of their microarray to the rest of the public microarrays. This solution helps not only to corroborate the conclusions regarding a researcher's microarray but also to identify the phenotype of different subsets of individuals under investigation, to frame the results with microarray experiments from other species, pathologies or tissues, to search for drugs that promote the transition between the studied phenotypes, to detect undesirable side effects of the treatment applied, etc. Thus, the researcher can quickly add relevant information to his/her studies from all of the previous analyses performed in other studies as long as they have been deposited in public repositories. Marker-gene database tool: http://ibb.uab.es/mgdb © The Author 2014. Published by Oxford University Press.

GeneSigDB—a curated database of gene expression signatures

PubMed Central

Culhane, Aedín C.; Schwarzl, Thomas; Sultana, Razvan; Picard, Kermshlise C.; Picard, Shaita C.; Lu, Tim H.; Franklin, Katherine R.; French, Simon J.; Papenhausen, Gerald; Correll, Mick; Quackenbush, John

2010-01-01

The primary objective of most gene expression studies is the identification of one or more gene signatures; lists of genes whose transcriptional levels are uniquely associated with a specific biological phenotype. Whilst thousands of experimentally derived gene signatures are published, their potential value to the community is limited by their computational inaccessibility. Gene signatures are embedded in published article figures, tables or in supplementary materials, and are frequently presented using non-standard gene or probeset nomenclature. We present GeneSigDB (http://compbio.dfci.harvard.edu/genesigdb) a manually curated database of gene expression signatures. GeneSigDB release 1.0 focuses on cancer and stem cells gene signatures and was constructed from more than 850 publications from which we manually transcribed 575 gene signatures. Most gene signatures (n = 560) were successfully mapped to the genome to extract standardized lists of EnsEMBL gene identifiers. GeneSigDB provides the original gene signature, the standardized gene list and a fully traceable gene mapping history for each gene from the original transcribed data table through to the standardized list of genes. The GeneSigDB web portal is easy to search, allows users to compare their own gene list to those in the database, and download gene signatures in most common gene identifier formats. PMID:19934259

New mutations and an updated database for the patched-1 (PTCH1) gene.

PubMed

Reinders, Marie G; van Hout, Antonius F; Cosgun, Betûl; Paulussen, Aimée D; Leter, Edward M; Steijlen, Peter M; Mosterd, Klara; van Geel, Michel; Gille, Johan J

2018-05-01

Basal cell nevus syndrome (BCNS) is an autosomal dominant disorder characterized by multiple basal cell carcinomas (BCCs), maxillary keratocysts, and cerebral calcifications. BCNS most commonly is caused by a germline mutation in the patched-1 (PTCH1) gene. PTCH1 mutations are also described in patients with holoprosencephaly. We have established a locus-specific database for the PTCH1 gene using the Leiden Open Variation Database (LOVD). We included 117 new PTCH1 variations, in addition to 331 previously published unique PTCH1 mutations. These new mutations were found in 141 patients who had a positive PTCH1 mutation analysis in either the VU University Medical Centre (VUMC) or Maastricht University Medical Centre (MUMC) between 1995 and 2015. The database contains 331 previously published unique PTCH1 mutations and 117 new PTCH1 variations. We have established a locus-specific database for the PTCH1 gene using the Leiden Open Variation Database (LOVD). The database provides an open collection for both clinicians and researchers and is accessible online at http://www.lovd.nl/PTCH1. © 2018 The Authors. Molecular Genetics & Genomic Medicine published by Wiley Periodicals, Inc.

Database resources of the National Center for Biotechnology Information

PubMed Central

Wheeler, David L.; Barrett, Tanya; Benson, Dennis A.; Bryant, Stephen H.; Canese, Kathi; Chetvernin, Vyacheslav; Church, Deanna M.; DiCuccio, Michael; Edgar, Ron; Federhen, Scott; Feolo, Michael; Geer, Lewis Y.; Helmberg, Wolfgang; Kapustin, Yuri; Khovayko, Oleg; Landsman, David; Lipman, David J.; Madden, Thomas L.; Maglott, Donna R.; Miller, Vadim; Ostell, James; Pruitt, Kim D.; Schuler, Gregory D.; Shumway, Martin; Sequeira, Edwin; Sherry, Steven T.; Sirotkin, Karl; Souvorov, Alexandre; Starchenko, Grigory; Tatusov, Roman L.; Tatusova, Tatiana A.; Wagner, Lukas; Yaschenko, Eugene

2008-01-01

In addition to maintaining the GenBank(R) nucleic acid sequence database, the National Center for Biotechnology Information (NCBI) provides analysis and retrieval resources for the data in GenBank and other biological data available through NCBI's web site. NCBI resources include Entrez, the Entrez Programming Utilities, My NCBI, PubMed, PubMed Central, Entrez Gene, the NCBI Taxonomy Browser, BLAST, BLAST Link, Electronic PCR, OrfFinder, Spidey, Splign, RefSeq, UniGene, HomoloGene, ProtEST, dbMHC, dbSNP, Cancer Chromosomes, Entrez Genome, Genome Project and related tools, the Trace, Assembly, and Short Read Archives, the Map Viewer, Model Maker, Evidence Viewer, Clusters of Orthologous Groups, Influenza Viral Resources, HIV-1/Human Protein Interaction Database, Gene Expression Omnibus, Entrez Probe, GENSAT, Database of Genotype and Phenotype, Online Mendelian Inheritance in Man, Online Mendelian Inheritance in Animals, the Molecular Modeling Database, the Conserved Domain Database, the Conserved Domain Architecture Retrieval Tool and the PubChem suite of small molecule databases. Augmenting the web applications are custom implementations of the BLAST program optimized to search specialized data sets. These resources can be accessed through the NCBI home page at www.ncbi.nlm.nih.gov. PMID:18045790

GrainGenes: Changing Times, Changing Databases, Digital Evolution.

USDA-ARS?s Scientific Manuscript database

The GrainGenes database is one of few agricultural databases that had an early start on the Internet and that has changed with the times. Initial goals were to collect a wide range of data relating to the developing maps and attributes of small grains crops, and to make them easily accessible. The ...

Database resources of the National Center for Biotechnology Information

PubMed Central

Wheeler, David L.; Barrett, Tanya; Benson, Dennis A.; Bryant, Stephen H.; Canese, Kathi; Chetvernin, Vyacheslav; Church, Deanna M.; DiCuccio, Michael; Edgar, Ron; Federhen, Scott; Geer, Lewis Y.; Helmberg, Wolfgang; Kapustin, Yuri; Kenton, David L.; Khovayko, Oleg; Lipman, David J.; Madden, Thomas L.; Maglott, Donna R.; Ostell, James; Pruitt, Kim D.; Schuler, Gregory D.; Schriml, Lynn M.; Sequeira, Edwin; Sherry, Stephen T.; Sirotkin, Karl; Souvorov, Alexandre; Starchenko, Grigory; Suzek, Tugba O.; Tatusov, Roman; Tatusova, Tatiana A.; Wagner, Lukas; Yaschenko, Eugene

2006-01-01

In addition to maintaining the GenBank(R) nucleic acid sequence database, the National Center for Biotechnology Information (NCBI) provides analysis and retrieval resources for the data in GenBank and other biological data made available through NCBI's Web site. NCBI resources include Entrez, the Entrez Programming Utilities, MyNCBI, PubMed, PubMed Central, Entrez Gene, the NCBI Taxonomy Browser, BLAST, BLAST Link (BLink), Electronic PCR, OrfFinder, Spidey, Splign, RefSeq, UniGene, HomoloGene, ProtEST, dbMHC, dbSNP, Cancer Chromosomes, Entrez Genomes and related tools, the Map Viewer, Model Maker, Evidence Viewer, Clusters of Orthologous Groups, Retroviral Genotyping Tools, HIV-1, Human Protein Interaction Database, SAGEmap, Gene Expression Omnibus, Entrez Probe, GENSAT, Online Mendelian Inheritance in Man, Online Mendelian Inheritance in Animals, the Molecular Modeling Database, the Conserved Domain Database, the Conserved Domain Architecture Retrieval Tool and the PubChem suite of small molecule databases. Augmenting many of the Web applications are custom implementations of the BLAST program optimized to search specialized datasets. All of the resources can be accessed through the NCBI home page at: . PMID:16381840

Database resources of the National Center for Biotechnology Information.

PubMed

Sayers, Eric W; Barrett, Tanya; Benson, Dennis A; Bolton, Evan; Bryant, Stephen H; Canese, Kathi; Chetvernin, Vyacheslav; Church, Deanna M; Dicuccio, Michael; Federhen, Scott; Feolo, Michael; Fingerman, Ian M; Geer, Lewis Y; Helmberg, Wolfgang; Kapustin, Yuri; Krasnov, Sergey; Landsman, David; Lipman, David J; Lu, Zhiyong; Madden, Thomas L; Madej, Tom; Maglott, Donna R; Marchler-Bauer, Aron; Miller, Vadim; Karsch-Mizrachi, Ilene; Ostell, James; Panchenko, Anna; Phan, Lon; Pruitt, Kim D; Schuler, Gregory D; Sequeira, Edwin; Sherry, Stephen T; Shumway, Martin; Sirotkin, Karl; Slotta, Douglas; Souvorov, Alexandre; Starchenko, Grigory; Tatusova, Tatiana A; Wagner, Lukas; Wang, Yanli; Wilbur, W John; Yaschenko, Eugene; Ye, Jian

2012-01-01

In addition to maintaining the GenBank® nucleic acid sequence database, the National Center for Biotechnology Information (NCBI) provides analysis and retrieval resources for the data in GenBank and other biological data made available through the NCBI Website. NCBI resources include Entrez, the Entrez Programming Utilities, MyNCBI, PubMed, PubMed Central (PMC), Gene, the NCBI Taxonomy Browser, BLAST, BLAST Link (BLink), Primer-BLAST, COBALT, Splign, RefSeq, UniGene, HomoloGene, ProtEST, dbMHC, dbSNP, dbVar, Epigenomics, Genome and related tools, the Map Viewer, Model Maker, Evidence Viewer, Trace Archive, Sequence Read Archive, BioProject, BioSample, Retroviral Genotyping Tools, HIV-1/Human Protein Interaction Database, Gene Expression Omnibus (GEO), Probe, Online Mendelian Inheritance in Animals (OMIA), the Molecular Modeling Database (MMDB), the Conserved Domain Database (CDD), the Conserved Domain Architecture Retrieval Tool (CDART), Biosystems, Protein Clusters and the PubChem suite of small molecule databases. Augmenting many of the Web applications are custom implementations of the BLAST program optimized to search specialized data sets. All of these resources can be accessed through the NCBI home page at www.ncbi.nlm.nih.gov.

Database resources of the National Center for Biotechnology Information

PubMed Central

Acland, Abigail; Agarwala, Richa; Barrett, Tanya; Beck, Jeff; Benson, Dennis A.; Bollin, Colleen; Bolton, Evan; Bryant, Stephen H.; Canese, Kathi; Church, Deanna M.; Clark, Karen; DiCuccio, Michael; Dondoshansky, Ilya; Federhen, Scott; Feolo, Michael; Geer, Lewis Y.; Gorelenkov, Viatcheslav; Hoeppner, Marilu; Johnson, Mark; Kelly, Christopher; Khotomlianski, Viatcheslav; Kimchi, Avi; Kimelman, Michael; Kitts, Paul; Krasnov, Sergey; Kuznetsov, Anatoliy; Landsman, David; Lipman, David J.; Lu, Zhiyong; Madden, Thomas L.; Madej, Tom; Maglott, Donna R.; Marchler-Bauer, Aron; Karsch-Mizrachi, Ilene; Murphy, Terence; Ostell, James; O'Sullivan, Christopher; Panchenko, Anna; Phan, Lon; Pruitt, Don Preussm Kim D.; Rubinstein, Wendy; Sayers, Eric W.; Schneider, Valerie; Schuler, Gregory D.; Sequeira, Edwin; Sherry, Stephen T.; Shumway, Martin; Sirotkin, Karl; Siyan, Karanjit; Slotta, Douglas; Soboleva, Alexandra; Soussov, Vladimir; Starchenko, Grigory; Tatusova, Tatiana A.; Trawick, Bart W.; Vakatov, Denis; Wang, Yanli; Ward, Minghong; John Wilbur, W.; Yaschenko, Eugene; Zbicz, Kerry

2014-01-01

In addition to maintaining the GenBank® nucleic acid sequence database, the National Center for Biotechnology Information (NCBI, http://www.ncbi.nlm.nih.gov) provides analysis and retrieval resources for the data in GenBank and other biological data made available through the NCBI Web site. NCBI resources include Entrez, the Entrez Programming Utilities, MyNCBI, PubMed, PubMed Central, PubReader, Gene, the NCBI Taxonomy Browser, BLAST, BLAST Link, Primer-BLAST, COBALT, RefSeq, UniGene, HomoloGene, ProtEST, dbMHC, dbSNP, dbVar, Epigenomics, the Genetic Testing Registry, Genome and related tools, the Map Viewer, Trace Archive, Sequence Read Archive, BioProject, BioSample, ClinVar, MedGen, HIV-1/Human Protein Interaction Database, Gene Expression Omnibus, Probe, Online Mendelian Inheritance in Animals, the Molecular Modeling Database, the Conserved Domain Database, the Conserved Domain Architecture Retrieval Tool, Biosystems, Protein Clusters and the PubChem suite of small molecule databases. Augmenting many of the Web applications are custom implementations of the BLAST program optimized to search specialized data sets. All these resources can be accessed through the NCBI home page. PMID:24259429

Database resources of the National Center for Biotechnology Information

PubMed Central

Wheeler, David L.; Church, Deanna M.; Lash, Alex E.; Leipe, Detlef D.; Madden, Thomas L.; Pontius, Joan U.; Schuler, Gregory D.; Schriml, Lynn M.; Tatusova, Tatiana A.; Wagner, Lukas; Rapp, Barbara A.

2001-01-01

In addition to maintaining the GenBank® nucleic acid sequence database, the National Center for Biotechnology Information (NCBI) provides data analysis and retrieval resources that operate on the data in GenBank and a variety of other biological data made available through NCBI’s Web site. NCBI data retrieval resources include Entrez, PubMed, LocusLink and the Taxonomy Browser. Data analysis resources include BLAST, Electronic PCR, OrfFinder, RefSeq, UniGene, HomoloGene, Database of Single Nucleotide Polymorphisms (dbSNP), Human Genome Sequencing, Human MapViewer, GeneMap’99, Human–Mouse Homology Map, Cancer Chromosome Aberration Project (CCAP), Entrez Genomes, Clusters of Orthologous Groups (COGs) database, Retroviral Genotyping Tools, Cancer Genome Anatomy Project (CGAP), SAGEmap, Gene Expression Omnibus (GEO), Online Mendelian Inheri­tance in Man (OMIM), the Molecular Modeling Database (MMDB) and the Conserved Domain Database (CDD). Augmenting many of the Web applications are custom implementations of the BLAST program optimized to search specialized data sets. All of the resources can be accessed through the NCBI home page at: http://www.ncbi.nlm.nih.gov. PMID:11125038

Follicle Online: an integrated database of follicle assembly, development and ovulation.

PubMed

Hua, Juan; Xu, Bo; Yang, Yifan; Ban, Rongjun; Iqbal, Furhan; Cooke, Howard J; Zhang, Yuanwei; Shi, Qinghua

2015-01-01

Folliculogenesis is an important part of ovarian function as it provides the oocytes for female reproductive life. Characterizing genes/proteins involved in folliculogenesis is fundamental for understanding the mechanisms associated with this biological function and to cure the diseases associated with folliculogenesis. A large number of genes/proteins associated with folliculogenesis have been identified from different species. However, no dedicated public resource is currently available for folliculogenesis-related genes/proteins that are validated by experiments. Here, we are reporting a database 'Follicle Online' that provides the experimentally validated gene/protein map of the folliculogenesis in a number of species. Follicle Online is a web-based database system for storing and retrieving folliculogenesis-related experimental data. It provides detailed information for 580 genes/proteins (from 23 model organisms, including Homo sapiens, Mus musculus, Rattus norvegicus, Mesocricetus auratus, Bos Taurus, Drosophila and Xenopus laevis) that have been reported to be involved in folliculogenesis, POF (premature ovarian failure) and PCOS (polycystic ovary syndrome). The literature was manually curated from more than 43,000 published articles (till 1 March 2014). The Follicle Online database is implemented in PHP + MySQL + JavaScript and this user-friendly web application provides access to the stored data. In summary, we have developed a centralized database that provides users with comprehensive information about genes/proteins involved in folliculogenesis. This database can be accessed freely and all the stored data can be viewed without any registration. Database URL: http://mcg.ustc.edu.cn/sdap1/follicle/index.php © The Author(s) 2015. Published by Oxford University Press.

Follicle Online: an integrated database of follicle assembly, development and ovulation

PubMed Central

Hua, Juan; Xu, Bo; Yang, Yifan; Ban, Rongjun; Iqbal, Furhan; Zhang, Yuanwei; Shi, Qinghua

2015-01-01

Folliculogenesis is an important part of ovarian function as it provides the oocytes for female reproductive life. Characterizing genes/proteins involved in folliculogenesis is fundamental for understanding the mechanisms associated with this biological function and to cure the diseases associated with folliculogenesis. A large number of genes/proteins associated with folliculogenesis have been identified from different species. However, no dedicated public resource is currently available for folliculogenesis-related genes/proteins that are validated by experiments. Here, we are reporting a database ‘Follicle Online’ that provides the experimentally validated gene/protein map of the folliculogenesis in a number of species. Follicle Online is a web-based database system for storing and retrieving folliculogenesis-related experimental data. It provides detailed information for 580 genes/proteins (from 23 model organisms, including Homo sapiens, Mus musculus, Rattus norvegicus, Mesocricetus auratus, Bos Taurus, Drosophila and Xenopus laevis) that have been reported to be involved in folliculogenesis, POF (premature ovarian failure) and PCOS (polycystic ovary syndrome). The literature was manually curated from more than 43 000 published articles (till 1 March 2014). The Follicle Online database is implemented in PHP + MySQL + JavaScript and this user-friendly web application provides access to the stored data. In summary, we have developed a centralized database that provides users with comprehensive information about genes/proteins involved in folliculogenesis. This database can be accessed freely and all the stored data can be viewed without any registration. Database URL: http://mcg.ustc.edu.cn/sdap1/follicle/index.php PMID:25931457

Information System through ANIS at CeSAM

NASA Astrophysics Data System (ADS)

Moreau, C.; Agneray, F.; Gimenez, S.

2015-09-01

ANIS (AstroNomical Information System) is a web generic tool developed at CeSAM to facilitate and standardize the implementation of astronomical data of various kinds through private and/or public dedicated Information Systems. The architecture of ANIS is composed of a database server which contains the project data, a web user interface template which provides high level services (search, extract and display imaging and spectroscopic data using a combination of criteria, an object list, a sql query module or a cone search interfaces), a framework composed of several packages, and a metadata database managed by a web administration entity. The process to implement a new ANIS instance at CeSAM is easy and fast : the scientific project has to submit data or a data secure access, the CeSAM team installs the new instance (web interface template and the metadata database), and the project administrator can configure the instance with the web ANIS-administration entity. Currently, the CeSAM offers through ANIS a web access to VO compliant Information Systems for different projects (HeDaM, HST-COSMOS, CFHTLS-ZPhots, ExoDAT,...).

PIECE 2.0: an update for the plant gene structure comparison and evolution database

USDA-ARS?s Scientific Manuscript database

PIECE (Plant Intron Exon Comparision and Evolution) is a web-accessible database that houses intron and exon information of plant genes. PIECE serves as a resource for biologists interested in comparing intron-exon organization and provides valuable insights into the evolution of gene structure in ...

The Chinchilla Research Resource Database: resource for an otolaryngology disease model

PubMed Central

Shimoyama, Mary; Smith, Jennifer R.; De Pons, Jeff; Tutaj, Marek; Khampang, Pawjai; Hong, Wenzhou; Erbe, Christy B.; Ehrlich, Garth D.; Bakaletz, Lauren O.; Kerschner, Joseph E.

2016-01-01

The long-tailed chinchilla (Chinchilla lanigera) is an established animal model for diseases of the inner and middle ear, among others. In particular, chinchilla is commonly used to study diseases involving viral and bacterial pathogens and polymicrobial infections of the upper respiratory tract and the ear, such as otitis media. The value of the chinchilla as a model for human diseases prompted the sequencing of its genome in 2012 and the more recent development of the Chinchilla Research Resource Database (http://crrd.mcw.edu) to provide investigators with easy access to relevant datasets and software tools to enhance their research. The Chinchilla Research Resource Database contains a complete catalog of genes for chinchilla and, for comparative purposes, human. Chinchilla genes can be viewed in the context of their genomic scaffold positions using the JBrowse genome browser. In contrast to the corresponding records at NCBI, individual gene reports at CRRD include functional annotations for Disease, Gene Ontology (GO) Biological Process, GO Molecular Function, GO Cellular Component and Pathway assigned to chinchilla genes based on annotations from the corresponding human orthologs. Data can be retrieved via keyword and gene-specific searches. Lists of genes with similar functional attributes can be assembled by leveraging the hierarchical structure of the Disease, GO and Pathway vocabularies through the Ontology Search and Browser tool. Such lists can then be further analyzed for commonalities using the Gene Annotator (GA) Tool. All data in the Chinchilla Research Resource Database is freely accessible and downloadable via the CRRD FTP site or using the download functions available in the search and analysis tools. The Chinchilla Research Resource Database is a rich resource for researchers using, or considering the use of, chinchilla as a model for human disease. Database URL: http://crrd.mcw.edu PMID:27173523

BloodSpot: a database of gene expression profiles and transcriptional programs for healthy and malignant haematopoiesis

PubMed Central

Bagger, Frederik Otzen; Sasivarevic, Damir; Sohi, Sina Hadi; Laursen, Linea Gøricke; Pundhir, Sachin; Sønderby, Casper Kaae; Winther, Ole; Rapin, Nicolas; Porse, Bo T.

2016-01-01

Research on human and murine haematopoiesis has resulted in a vast number of gene-expression data sets that can potentially answer questions regarding normal and aberrant blood formation. To researchers and clinicians with limited bioinformatics experience, these data have remained available, yet largely inaccessible. Current databases provide information about gene-expression but fail to answer key questions regarding co-regulation, genetic programs or effect on patient survival. To address these shortcomings, we present BloodSpot (www.bloodspot.eu), which includes and greatly extends our previously released database HemaExplorer, a database of gene expression profiles from FACS sorted healthy and malignant haematopoietic cells. A revised interactive interface simultaneously provides a plot of gene expression along with a Kaplan–Meier analysis and a hierarchical tree depicting the relationship between different cell types in the database. The database now includes 23 high-quality curated data sets relevant to normal and malignant blood formation and, in addition, we have assembled and built a unique integrated data set, BloodPool. Bloodpool contains more than 2000 samples assembled from six independent studies on acute myeloid leukemia. Furthermore, we have devised a robust sample integration procedure that allows for sensitive comparison of user-supplied patient samples in a well-defined haematopoietic cellular space. PMID:26507857

pGenN, a gene normalization tool for plant genes and proteins in scientific literature.

PubMed

Ding, Ruoyao; Arighi, Cecilia N; Lee, Jung-Youn; Wu, Cathy H; Vijay-Shanker, K

2015-01-01

Automatically detecting gene/protein names in the literature and connecting them to databases records, also known as gene normalization, provides a means to structure the information buried in free-text literature. Gene normalization is critical for improving the coverage of annotation in the databases, and is an essential component of many text mining systems and database curation pipelines. In this manuscript, we describe a gene normalization system specifically tailored for plant species, called pGenN (pivot-based Gene Normalization). The system consists of three steps: dictionary-based gene mention detection, species assignment, and intra species normalization. We have developed new heuristics to improve each of these phases. We evaluated the performance of pGenN on an in-house expertly annotated corpus consisting of 104 plant relevant abstracts. Our system achieved an F-value of 88.9% (Precision 90.9% and Recall 87.2%) on this corpus, outperforming state-of-art systems presented in BioCreative III. We have processed over 440,000 plant-related Medline abstracts using pGenN. The gene normalization results are stored in a local database for direct query from the pGenN web interface (proteininformationresource.org/pgenn/). The annotated literature corpus is also publicly available through the PIR text mining portal (proteininformationresource.org/iprolink/).

dbMDEGA: a database for meta-analysis of differentially expressed genes in autism spectrum disorder.

PubMed

Zhang, Shuyun; Deng, Libin; Jia, Qiyue; Huang, Shaoting; Gu, Junwang; Zhou, Fankun; Gao, Meng; Sun, Xinyi; Feng, Chang; Fan, Guangqin

2017-11-16

Autism spectrum disorders (ASD) are hereditary, heterogeneous and biologically complex neurodevelopmental disorders. Individual studies on gene expression in ASD cannot provide clear consensus conclusions. Therefore, a systematic review to synthesize the current findings from brain tissues and a search tool to share the meta-analysis results are urgently needed. Here, we conducted a meta-analysis of brain gene expression profiles in the current reported human ASD expression datasets (with 84 frozen male cortex samples, 17 female cortex samples, 32 cerebellum samples and 4 formalin fixed samples) and knock-out mouse ASD model expression datasets (with 80 collective brain samples). Then, we applied R language software and developed an interactive shared and updated database (dbMDEGA) displaying the results of meta-analysis of data from ASD studies regarding differentially expressed genes (DEGs) in the brain. This database, dbMDEGA ( https://dbmdega.shinyapps.io/dbMDEGA/ ), is a publicly available web-portal for manual annotation and visualization of DEGs in the brain from data from ASD studies. This database uniquely presents meta-analysis values and homologous forest plots of DEGs in brain tissues. Gene entries are annotated with meta-values, statistical values and forest plots of DEGs in brain samples. This database aims to provide searchable meta-analysis results based on the current reported brain gene expression datasets of ASD to help detect candidate genes underlying this disorder. This new analytical tool may provide valuable assistance in the discovery of DEGs and the elucidation of the molecular pathogenicity of ASD. This database model may be replicated to study other disorders.

The Androgen Receptor Gene Mutations Database.

PubMed

Gottlieb, B; Lehvaslaiho, H; Beitel, L K; Lumbroso, R; Pinsky, L; Trifiro, M

1998-01-01

The current version of the androgen receptor (AR) gene mutations database is described. The total number of reported mutations has risen from 272 to 309 in the past year. We have expanded the database: (i) by giving each entry an accession number; (ii) by adding information on the length of polymorphic polyglutamine (polyGln) and polyglycine (polyGly) tracts in exon 1; (iii) by adding information on large gene deletions; (iv) by providing a direct link with a completely searchable database (courtesy EMBL-European Bioinformatics Institute). The addition of the exon 1 polymorphisms is discussed in light of their possible relevance as markers for predisposition to prostate or breast cancer. The database is also available on the internet (http://www.mcgill. ca/androgendb/ ), from EMBL-European Bioinformatics Institute (ftp. ebi.ac.uk/pub/databases/androgen ), or as a Macintosh FilemakerPro or Word file (MC33@musica.mcgill.ca).

The Androgen Receptor Gene Mutations Database.

PubMed Central

Gottlieb, B; Lehvaslaiho, H; Beitel, L K; Lumbroso, R; Pinsky, L; Trifiro, M

1998-01-01

The current version of the androgen receptor (AR) gene mutations database is described. The total number of reported mutations has risen from 272 to 309 in the past year. We have expanded the database: (i) by giving each entry an accession number; (ii) by adding information on the length of polymorphic polyglutamine (polyGln) and polyglycine (polyGly) tracts in exon 1; (iii) by adding information on large gene deletions; (iv) by providing a direct link with a completely searchable database (courtesy EMBL-European Bioinformatics Institute). The addition of the exon 1 polymorphisms is discussed in light of their possible relevance as markers for predisposition to prostate or breast cancer. The database is also available on the internet (http://www.mcgill. ca/androgendb/ ), from EMBL-European Bioinformatics Institute (ftp. ebi.ac.uk/pub/databases/androgen ), or as a Macintosh FilemakerPro or Word file (MC33@musica.mcgill.ca). PMID:9399843

VitisExpDB: a database resource for grape functional genomics.

PubMed

Doddapaneni, Harshavardhan; Lin, Hong; Walker, M Andrew; Yao, Jiqiang; Civerolo, Edwin L

2008-02-28

The family Vitaceae consists of many different grape species that grow in a range of climatic conditions. In the past few years, several studies have generated functional genomic information on different Vitis species and cultivars, including the European grape vine, Vitis vinifera. Our goal is to develop a comprehensive web data source for Vitaceae. VitisExpDB is an online MySQL-PHP driven relational database that houses annotated EST and gene expression data for V. vinifera and non-vinifera grape species and varieties. Currently, the database stores approximately 320,000 EST sequences derived from 8 species/hybrids, their annotation (BLAST top match) details and Gene Ontology based structured vocabulary. Putative homologs for each EST in other species and varieties along with information on their percent nucleotide identities, phylogenetic relationship and common primers can be retrieved. The database also includes information on probe sequence and annotation features of the high density 60-mer gene expression chip consisting of approximately 20,000 non-redundant set of ESTs. Finally, the database includes 14 processed global microarray expression profile sets. Data from 12 of these expression profile sets have been mapped onto metabolic pathways. A user-friendly web interface with multiple search indices and extensively hyperlinked result features that permit efficient data retrieval has been developed. Several online bioinformatics tools that interact with the database along with other sequence analysis tools have been added. In addition, users can submit their ESTs to the database. The developed database provides genomic resource to grape community for functional analysis of genes in the collection and for the grape genome annotation and gene function identification. The VitisExpDB database is available through our website http://cropdisease.ars.usda.gov/vitis_at/main-page.htm.

VitisExpDB: A database resource for grape functional genomics

PubMed Central

Doddapaneni, Harshavardhan; Lin, Hong; Walker, M Andrew; Yao, Jiqiang; Civerolo, Edwin L

2008-01-01

Background The family Vitaceae consists of many different grape species that grow in a range of climatic conditions. In the past few years, several studies have generated functional genomic information on different Vitis species and cultivars, including the European grape vine, Vitis vinifera. Our goal is to develop a comprehensive web data source for Vitaceae. Description VitisExpDB is an online MySQL-PHP driven relational database that houses annotated EST and gene expression data for V. vinifera and non-vinifera grape species and varieties. Currently, the database stores ~320,000 EST sequences derived from 8 species/hybrids, their annotation (BLAST top match) details and Gene Ontology based structured vocabulary. Putative homologs for each EST in other species and varieties along with information on their percent nucleotide identities, phylogenetic relationship and common primers can be retrieved. The database also includes information on probe sequence and annotation features of the high density 60-mer gene expression chip consisting of ~20,000 non-redundant set of ESTs. Finally, the database includes 14 processed global microarray expression profile sets. Data from 12 of these expression profile sets have been mapped onto metabolic pathways. A user-friendly web interface with multiple search indices and extensively hyperlinked result features that permit efficient data retrieval has been developed. Several online bioinformatics tools that interact with the database along with other sequence analysis tools have been added. In addition, users can submit their ESTs to the database. Conclusion The developed database provides genomic resource to grape community for functional analysis of genes in the collection and for the grape genome annotation and gene function identification. The VitisExpDB database is available through our website . PMID:18307813

HNdb: an integrated database of gene and protein information on head and neck squamous cell carcinoma

PubMed Central

Henrique, Tiago; José Freitas da Silveira, Nelson; Henrique Cunha Volpato, Arthur; Mioto, Mayra Mataruco; Carolina Buzzo Stefanini, Ana; Bachir Fares, Adil; Gustavo da Silva Castro Andrade, João; Masson, Carolina; Verónica Mendoza López, Rossana; Daumas Nunes, Fabio; Paulo Kowalski, Luis; Severino, Patricia; Tajara, Eloiza Helena

2016-01-01

The total amount of scientific literature has grown rapidly in recent years. Specifically, there are several million citations in the field of cancer. This makes it difficult, if not impossible, to manually retrieve relevant information on the mechanisms that govern tumor behavior or the neoplastic process. Furthermore, cancer is a complex disease or, more accurately, a set of diseases. The heterogeneity that permeates many tumors is particularly evident in head and neck (HN) cancer, one of the most common types of cancer worldwide. In this study, we present HNdb, a free database that aims to provide a unified and comprehensive resource of information on genes and proteins involved in HN squamous cell carcinoma, covering data on genomics, transcriptomics, proteomics, literature citations and also cross-references of external databases. Different literature searches of MEDLINE abstracts were performed using specific Medical Subject Headings (MeSH terms) for oral, oropharyngeal, hypopharyngeal and laryngeal squamous cell carcinomas. A curated gene-to-publication assignment yielded a total of 1370 genes related to HN cancer. The diversity of results allowed identifying novel and mostly unexplored gene associations, revealing, for example, that processes linked to response to steroid hormone stimulus are significantly enriched in genes related to HN carcinomas. Thus, our database expands the possibilities for gene networks investigation, providing potential hypothesis to be tested. Database URL: http://www.gencapo.famerp.br/hndb PMID:27013077

Kinase Pathway Database: An Integrated Protein-Kinase and NLP-Based Protein-Interaction Resource

PubMed Central

Koike, Asako; Kobayashi, Yoshiyuki; Takagi, Toshihisa

2003-01-01

Protein kinases play a crucial role in the regulation of cellular functions. Various kinds of information about these molecules are important for understanding signaling pathways and organism characteristics. We have developed the Kinase Pathway Database, an integrated database involving major completely sequenced eukaryotes. It contains the classification of protein kinases and their functional conservation, ortholog tables among species, protein–protein, protein–gene, and protein–compound interaction data, domain information, and structural information. It also provides an automatic pathway graphic image interface. The protein, gene, and compound interactions are automatically extracted from abstracts for all genes and proteins by natural-language processing (NLP).The method of automatic extraction uses phrase patterns and the GENA protein, gene, and compound name dictionary, which was developed by our group. With this database, pathways are easily compared among species using data with more than 47,000 protein interactions and protein kinase ortholog tables. The database is available for querying and browsing at http://kinasedb.ontology.ims.u-tokyo.ac.jp/. PMID:12799355

Piece2.0: an update for the pant gene structure comparison and evolution database

USDA-ARS?s Scientific Manuscript database

PIECE (Plant Intron Exon Comparison and Evolution) is a web-accessible database that houses intron and exon information of plant genes. PIECE serves as a resource for biologists interested in comparing intron–exon organization and provides valuable insights into the evolution of gene structure in pl...

rrndb: the Ribosomal RNA Operon Copy Number Database

PubMed Central

Klappenbach, Joel A.; Saxman, Paul R.; Cole, James R.; Schmidt, Thomas M.

2001-01-01

The Ribosomal RNA Operon Copy Number Database (rrndb) is an Internet-accessible database containing annotated information on rRNA operon copy number among prokaryotes. Gene redundancy is uncommon in prokaryotic genomes, yet the rRNA genes can vary from one to as many as 15 copies. Despite the widespread use of 16S rRNA gene sequences for identification of prokaryotes, information on the number and sequence of individual rRNA genes in a genome is not readily accessible. In an attempt to understand the evolutionary implications of rRNA operon redundancy, we have created a phylogenetically arranged report on rRNA gene copy number for a diverse collection of prokaryotic microorganisms. Each entry (organism) in the rrndb contains detailed information linked directly to external websites including the Ribosomal Database Project, GenBank, PubMed and several culture collections. Data contained in the rrndb will be valuable to researchers investigating microbial ecology and evolution using 16S rRNA gene sequences. The rrndb web site is directly accessible on the WWW at http://rrndb.cme.msu.edu. PMID:11125085

Functional Categorization of Transcriptome in the Species Symphysodon aequifasciatus Pellegrin 1904 (Perciformes: Cichlidae) Exposed to Benzo[a]pyrene and Phenanthrene

PubMed Central

Lemgruber, Renato de Souza Pinto; Marshall, Nislanha Ana dos Anjos; Ghelfi, Andrea; Fagundes, Daniel Barros; Val, Adalberto Luis

2013-01-01

This study aims to evaluate the transcriptome alterations, through cDNA libraries, associated with the combined effects of two PAHs, benzo[a]pyrene (0.5 µg/L) and phenanthrene (50 µg/L), present in crude oil, on specimens of Symphysodon aequifasciatus (discus fish) after 48 h of exposure. The cDNA libraries were constructed according to the SOLiD™ SAGE™ protocol for sequencing in the SOLiD v.3 Plus sequencer. The results were analyzed by bioinformatics and differentially expressed genes were categorized using the gene ontology program. The functional categories (terms) found in the gene ontology and the gene network generated using STRING software were used to predict the adverse effects of benzo[a]pyrene and phenanthrene in the liver. In the present study, 27,127 genes (compared to Danio rerio database) were identified. Considering only those genes with a p-value less than or equal to 0.05 and greater than or equal to two-fold change in expression across libraries, we found 804 genes, 438 down-regulated (54%) and 366 up-regulated (46%), in the experimental group compared to the control. Out of this total, 327 genes were successfully categorized, 174 down-regulated and 153 up-regulated, using gene ontology. Using String, the gene network was composed by 199 nodes, 124 of them resulting in 274 interactions. The results showed that even an acute exposure of 48 h caused metabolic change in response to environmental contaminants, resulting in changes of cell integrity, in oxidation-reduction processes, in the immune response and disturbances of intracellular signaling of discus fish. Also the gene network has showed no central interplay cluster, exhibiting instead interconnected clusters interactions and connected sub-networks. These findings highlight that even an acute sublethal exposure of PAHs can cause metabolism changes that may affect survival of discus. Our findings using SOLiD coupled with SAGE-method resulted in a powerful and reliable means for gene expression analysis in discus, a non-model Amazonian fish. PMID:24312524

Discovery and Complete Genome Sequence of a Bacteriophage from an Obligate Intracellular Symbiont of a Cellulolytic Protist in the Termite Gut

PubMed Central

Pramono, Ajeng K.; Kuwahara, Hirokazu; Itoh, Takehiko; Toyoda, Atsushi; Yamada, Akinori; Hongoh, Yuichi

2017-01-01

Termites depend nutritionally on their gut microbes, and protistan, bacterial, and archaeal gut communities have been extensively studied. However, limited information is available on viruses in the termite gut. We herein report the complete genome sequence (99,517 bp) of a phage obtained during a genome analysis of “Candidatus Azobacteroides pseudotrichonymphae” phylotype ProJPt-1, which is an obligate intracellular symbiont of the cellulolytic protist Pseudotrichonympha sp. in the gut of the termite Prorhinotermes japonicus. The genome of the phage, designated ProJPt-Bp1, was circular or circularly permuted, and was not integrated into the two circular chromosomes or five circular plasmids composing the host ProJPt-1 genome. The phage was putatively affiliated with the order Caudovirales based on sequence similarities with several phage-related genes; however, most of the 52 protein-coding sequences had no significant homology to sequences in the databases. The phage genome contained a tRNA-Gln (CAG) gene, which showed the highest sequence similarity to the tRNA-Gln (CAA) gene of the host “Ca. A. pseudotrichonymphae” phylotype ProJPt-1. Since the host genome lacked a tRNA-Gln (CAG) gene, the phage tRNA gene may compensate for differences in codon usage bias between the phage and host genomes. The phage genome also contained a non-coding region with high nucleotide sequence similarity to a region in one of the host plasmids. No other phage-related sequences were found in the host ProJPt-1 genome. To the best of our knowledge, this is the first report of a phage from an obligate, mutualistic endosymbiont permanently associated with eukaryotic cells. PMID:28321010

Expressed sequence tag (EST) analysis of two subspecies of Metarhizium anisopliae reveals a plethora of secreted proteins with potential activity in insect hosts.

PubMed

Freimoser, Florian M; Screen, Steven; Bagga, Savita; Hu, Gang; St Leger, Raymond J

2003-01-01

Expressed sequence tag (EST) libraries for Metarhizium anisopliae, the causative agent of green muscardine disease, were developed from the broad host-range pathogen Metarhizium anisopliae sf. anisopliae and the specific grasshopper pathogen, M. anisopliae sf. acridum. Approximately 1,700 5' end sequences from each subspecies were generated from cDNA libraries representing fungi grown under conditions that maximize secretion of cuticle-degrading enzymes. Both subspecies had ESTs for virtually all pathogenicity-related genes cloned to date from M. anisopliae, but many novel genes encoding potential virulence factors were also tagged. Enzymes with potential targets in the insect host included proteases, chitinases, phospholipases, lipases, esterases, phosphatases and enzymes producing toxic secondary metabolites. A diverse array of proteases composed 36 % of all M. anisopliae sf. anisopliae ESTs. Eighty percent of the ESTs that could be clustered into functional groups had significant matches (E<10(-5)) in other ascomycete fungi. These included genes reported to have specific roles in pathogens with plant or vertebrate hosts. Many of the remaining ESTs had their best BLAST match among animal, plant and bacterial sequences. These include genes with plant and microbial counterparts that produce potent antimicrobials. The abundance of transcripts discovered for different functional groups varied between the two subspecies of M. anisopliae in a manner consistent with ecological adaptations of the two pathogens. By hastening gene discovery this project has enhanced development of improved mycoinsecticides. In addition, the M. anisopliae ESTs represent a significant contribution to the extensive database of sequences from ascomycetes that are saprophytes or plant and vertebrate pathogens. Comparative analyses of these sequences is providing important information about the biology and evolutionary history of this clade.

MAGIC database and interfaces: an integrated package for gene discovery and expression.

PubMed

Cordonnier-Pratt, Marie-Michèle; Liang, Chun; Wang, Haiming; Kolychev, Dmitri S; Sun, Feng; Freeman, Robert; Sullivan, Robert; Pratt, Lee H

2004-01-01

The rapidly increasing rate at which biological data is being produced requires a corresponding growth in relational databases and associated tools that can help laboratories contend with that data. With this need in mind, we describe here a Modular Approach to a Genomic, Integrated and Comprehensive (MAGIC) Database. This Oracle 9i database derives from an initial focus in our laboratory on gene discovery via production and analysis of expressed sequence tags (ESTs), and subsequently on gene expression as assessed by both EST clustering and microarrays. The MAGIC Gene Discovery portion of the database focuses on information derived from DNA sequences and on its biological relevance. In addition to MAGIC SEQ-LIMS, which is designed to support activities in the laboratory, it contains several additional subschemas. The latter include MAGIC Admin for database administration, MAGIC Sequence for sequence processing as well as sequence and clone attributes, MAGIC Cluster for the results of EST clustering, MAGIC Polymorphism in support of microsatellite and single-nucleotide-polymorphism discovery, and MAGIC Annotation for electronic annotation by BLAST and BLAT. The MAGIC Microarray portion is a MIAME-compliant database with two components at present. These are MAGIC Array-LIMS, which makes possible remote entry of all information into the database, and MAGIC Array Analysis, which provides data mining and visualization. Because all aspects of interaction with the MAGIC Database are via a web browser, it is ideally suited not only for individual research laboratories but also for core facilities that serve clients at any distance.

Ubiquitous-health (U-Health) monitoring systems for elders and caregivers

NASA Astrophysics Data System (ADS)

Moon, Gyu; Lim, Kyung-won; Yoo, Young-min; An, Hye-min; Lee, Ki Seop; Szu, Harold

2011-06-01

This paper presents two aordable low-tack system for household biomedical wellness monitoring. The rst system, JIKIMI (pronounced caregiver in Korean), is a remote monitoring system that analyzes the behavior patterns of elders that live alone. JIKIMI is composed of an in-house sensing system, a set of wireless sensor nodes containing a pyroelectric infrared sensor to detect the motion of elders, an emergency button and a magnetic sensor that detects the opening and closing of doors. The system is also equipped with a server system, which is comprised of a database and web server. The server provides the mechanism for web-based monitoring to caregivers. The second system, Reader of Bottle Information (ROBI), is an assistant system which advises the contents of bottles for elders. ROBI is composed of bottles that have connected RFID tags and an advice system, which is composed of a wireless RFID reader, a gateway and a remote database server. The RFID tags are connected to the caps of the bottles are used in conjunction with the advice system These systems have been in use for three years and have proven to be useful for caregivers to provide more ecient and eective care services.

Patome: a database server for biological sequence annotation and analysis in issued patents and published patent applications.

PubMed

Lee, Byungwook; Kim, Taehyung; Kim, Seon-Kyu; Lee, Kwang H; Lee, Doheon

2007-01-01

With the advent of automated and high-throughput techniques, the number of patent applications containing biological sequences has been increasing rapidly. However, they have attracted relatively little attention compared to other sequence resources. We have built a database server called Patome, which contains biological sequence data disclosed in patents and published applications, as well as their analysis information. The analysis is divided into two steps. The first is an annotation step in which the disclosed sequences were annotated with RefSeq database. The second is an association step where the sequences were linked to Entrez Gene, OMIM and GO databases, and their results were saved as a gene-patent table. From the analysis, we found that 55% of human genes were associated with patenting. The gene-patent table can be used to identify whether a particular gene or disease is related to patenting. Patome is available at http://www.patome.org/; the information is updated bimonthly.

FARME DB: a functional antibiotic resistance element database

PubMed Central

Wallace, James C.; Port, Jesse A.; Smith, Marissa N.; Faustman, Elaine M.

2017-01-01

Antibiotic resistance (AR) is a major global public health threat but few resources exist that catalog AR genes outside of a clinical context. Current AR sequence databases are assembled almost exclusively from genomic sequences derived from clinical bacterial isolates and thus do not include many microbial sequences derived from environmental samples that confer resistance in functional metagenomic studies. These environmental metagenomic sequences often show little or no similarity to AR sequences from clinical isolates using standard classification criteria. In addition, existing AR databases provide no information about flanking sequences containing regulatory or mobile genetic elements. To help address this issue, we created an annotated database of DNA and protein sequences derived exclusively from environmental metagenomic sequences showing AR in laboratory experiments. Our Functional Antibiotic Resistant Metagenomic Element (FARME) database is a compilation of publically available DNA sequences and predicted protein sequences conferring AR as well as regulatory elements, mobile genetic elements and predicted proteins flanking antibiotic resistant genes. FARME is the first database to focus on functional metagenomic AR gene elements and provides a resource to better understand AR in the 99% of bacteria which cannot be cultured and the relationship between environmental AR sequences and antibiotic resistant genes derived from cultured isolates. Database URL: http://staff.washington.edu/jwallace/farme PMID:28077567

An annotated database of Arabidopsis mutants of acyl lipid metabolism

DOE PAGES

McGlew, Kathleen; Shaw, Vincent; Zhang, Meng; ...

2014-12-10

Mutants have played a fundamental role in gene discovery and in understanding the function of genes involved in plant acyl lipid metabolism. The first mutant in Arabidopsis lipid metabolism ( fad4) was described in 1985. Since that time, characterization of mutants in more than 280 genes associated with acyl lipid metabolism has been reported. This review provides a brief background and history on identification of mutants in acyl lipid metabolism, an analysis of the distribution of mutants in different areas of acyl lipid metabolism and presents an annotated database (ARALIPmutantDB) of these mutants. The database provides information on the phenotypesmore » of mutants, pathways and enzymes/proteins associated with the mutants, and allows rapid access via hyperlinks to summaries of information about each mutant and to literature that provides information on the lipid composition of the mutants. Mutants for at least 30 % of the genes in the database have multiple names, which have been compiled here to reduce ambiguities in searches for information. Furthermore, the database should also provide a tool for exploring the relationships between mutants in acyl lipid-related genes and their lipid phenotypes and point to opportunities for further research.« less

GeneAnalytics: An Integrative Gene Set Analysis Tool for Next Generation Sequencing, RNAseq and Microarray Data.

PubMed

Ben-Ari Fuchs, Shani; Lieder, Iris; Stelzer, Gil; Mazor, Yaron; Buzhor, Ella; Kaplan, Sergey; Bogoch, Yoel; Plaschkes, Inbar; Shitrit, Alina; Rappaport, Noa; Kohn, Asher; Edgar, Ron; Shenhav, Liraz; Safran, Marilyn; Lancet, Doron; Guan-Golan, Yaron; Warshawsky, David; Shtrichman, Ronit

2016-03-01

Postgenomics data are produced in large volumes by life sciences and clinical applications of novel omics diagnostics and therapeutics for precision medicine. To move from "data-to-knowledge-to-innovation," a crucial missing step in the current era is, however, our limited understanding of biological and clinical contexts associated with data. Prominent among the emerging remedies to this challenge are the gene set enrichment tools. This study reports on GeneAnalytics™ ( geneanalytics.genecards.org ), a comprehensive and easy-to-apply gene set analysis tool for rapid contextualization of expression patterns and functional signatures embedded in the postgenomics Big Data domains, such as Next Generation Sequencing (NGS), RNAseq, and microarray experiments. GeneAnalytics' differentiating features include in-depth evidence-based scoring algorithms, an intuitive user interface and proprietary unified data. GeneAnalytics employs the LifeMap Science's GeneCards suite, including the GeneCards®--the human gene database; the MalaCards-the human diseases database; and the PathCards--the biological pathways database. Expression-based analysis in GeneAnalytics relies on the LifeMap Discovery®--the embryonic development and stem cells database, which includes manually curated expression data for normal and diseased tissues, enabling advanced matching algorithm for gene-tissue association. This assists in evaluating differentiation protocols and discovering biomarkers for tissues and cells. Results are directly linked to gene, disease, or cell "cards" in the GeneCards suite. Future developments aim to enhance the GeneAnalytics algorithm as well as visualizations, employing varied graphical display items. Such attributes make GeneAnalytics a broadly applicable postgenomics data analyses and interpretation tool for translation of data to knowledge-based innovation in various Big Data fields such as precision medicine, ecogenomics, nutrigenomics, pharmacogenomics, vaccinomics, and others yet to emerge on the postgenomics horizon.

Clique-based data mining for related genes in a biomedical database.

PubMed

Matsunaga, Tsutomu; Yonemori, Chikara; Tomita, Etsuji; Muramatsu, Masaaki

2009-07-01

Progress in the life sciences cannot be made without integrating biomedical knowledge on numerous genes in order to help formulate hypotheses on the genetic mechanisms behind various biological phenomena, including diseases. There is thus a strong need for a way to automatically and comprehensively search from biomedical databases for related genes, such as genes in the same families and genes encoding components of the same pathways. Here we address the extraction of related genes by searching for densely-connected subgraphs, which are modeled as cliques, in a biomedical relational graph. We constructed a graph whose nodes were gene or disease pages, and edges were the hyperlink connections between those pages in the Online Mendelian Inheritance in Man (OMIM) database. We obtained over 20,000 sets of related genes (called 'gene modules') by enumerating cliques computationally. The modules included genes in the same family, genes for proteins that form a complex, and genes for components of the same signaling pathway. The results of experiments using 'metabolic syndrome'-related gene modules show that the gene modules can be used to get a coherent holistic picture helpful for interpreting relations among genes. We presented a data mining approach extracting related genes by enumerating cliques. The extracted gene sets provide a holistic picture useful for comprehending complex disease mechanisms.

DGIdb 3.0: a redesign and expansion of the drug-gene interaction database.

PubMed

Cotto, Kelsy C; Wagner, Alex H; Feng, Yang-Yang; Kiwala, Susanna; Coffman, Adam C; Spies, Gregory; Wollam, Alex; Spies, Nicholas C; Griffith, Obi L; Griffith, Malachi

2018-01-04

The drug-gene interaction database (DGIdb, www.dgidb.org) consolidates, organizes and presents drug-gene interactions and gene druggability information from papers, databases and web resources. DGIdb normalizes content from 30 disparate sources and allows for user-friendly advanced browsing, searching and filtering for ease of access through an intuitive web user interface, application programming interface (API) and public cloud-based server image. DGIdb v3.0 represents a major update of the database. Nine of the previously included 24 sources were updated. Six new resources were added, bringing the total number of sources to 30. These updates and additions of sources have cumulatively resulted in 56 309 interaction claims. This has also substantially expanded the comprehensive catalogue of druggable genes and anti-neoplastic drug-gene interactions included in the DGIdb. Along with these content updates, v3.0 has received a major overhaul of its codebase, including an updated user interface, preset interaction search filters, consolidation of interaction information into interaction groups, greatly improved search response times and upgrading the underlying web application framework. In addition, the expanded API features new endpoints which allow users to extract more detailed information about queried drugs, genes and drug-gene interactions, including listings of PubMed IDs, interaction type and other interaction metadata.

Phylogenomics databases for facilitating functional genomics in rice.

PubMed

Jung, Ki-Hong; Cao, Peijian; Sharma, Rita; Jain, Rashmi; Ronald, Pamela C

2015-12-01

The completion of whole genome sequence of rice (Oryza sativa) has significantly accelerated functional genomics studies. Prior to the release of the sequence, only a few genes were assigned a function each year. Since sequencing was completed in 2005, the rate has exponentially increased. As of 2014, 1,021 genes have been described and added to the collection at The Overview of functionally characterized Genes in Rice online database (OGRO). Despite this progress, that number is still very low compared with the total number of genes estimated in the rice genome. One limitation to progress is the presence of functional redundancy among members of the same rice gene family, which covers 51.6 % of all non-transposable element-encoding genes. There remain a significant portion or rice genes that are not functionally redundant, as reflected in the recovery of loss-of-function mutants. To more accurately analyze functional redundancy in the rice genome, we have developed a phylogenomics databases for six large gene families in rice, including those for glycosyltransferases, glycoside hydrolases, kinases, transcription factors, transporters, and cytochrome P450 monooxygenases. In this review, we introduce key features and applications of these databases. We expect that they will serve as a very useful guide in the post-genomics era of research.

GEneSTATION 1.0: a synthetic resource of diverse evolutionary and functional genomic data for studying the evolution of pregnancy-associated tissues and phenotypes

PubMed Central

Kim, Mara; Cooper, Brian A.; Venkat, Rohit; Phillips, Julie B.; Eidem, Haley R.; Hirbo, Jibril; Nutakki, Sashank; Williams, Scott M.; Muglia, Louis J.; Capra, J. Anthony; Petren, Kenneth; Abbot, Patrick; Rokas, Antonis; McGary, Kriston L.

2016-01-01

Mammalian gestation and pregnancy are fast evolving processes that involve the interaction of the fetal, maternal and paternal genomes. Version 1.0 of the GEneSTATION database (http://genestation.org) integrates diverse types of omics data across mammals to advance understanding of the genetic basis of gestation and pregnancy-associated phenotypes and to accelerate the translation of discoveries from model organisms to humans. GEneSTATION is built using tools from the Generic Model Organism Database project, including the biology-aware database CHADO, new tools for rapid data integration, and algorithms that streamline synthesis and user access. GEneSTATION contains curated life history information on pregnancy and reproduction from 23 high-quality mammalian genomes. For every human gene, GEneSTATION contains diverse evolutionary (e.g. gene age, population genetic and molecular evolutionary statistics), organismal (e.g. tissue-specific gene and protein expression, differential gene expression, disease phenotype), and molecular data types (e.g. Gene Ontology Annotation, protein interactions), as well as links to many general (e.g. Entrez, PubMed) and pregnancy disease-specific (e.g. PTBgene, dbPTB) databases. By facilitating the synthesis of diverse functional and evolutionary data in pregnancy-associated tissues and phenotypes and enabling their quick, intuitive, accurate and customized meta-analysis, GEneSTATION provides a novel platform for comprehensive investigation of the function and evolution of mammalian pregnancy. PMID:26567549

How Artificial Intelligence Can Improve Our Understanding of the Genes Associated with Endometriosis: Natural Language Processing of the PubMed Database

PubMed Central

Mashiach, R.; Cohen, S.; Kedem, A.; Baron, A.; Zajicek, M.; Feldman, I.; Seidman, D.; Soriano, D.

2018-01-01

Endometriosis is a disease characterized by the development of endometrial tissue outside the uterus, but its cause remains largely unknown. Numerous genes have been studied and proposed to help explain its pathogenesis. However, the large number of these candidate genes has made functional validation through experimental methodologies nearly impossible. Computational methods could provide a useful alternative for prioritizing those most likely to be susceptibility genes. Using artificial intelligence applied to text mining, this study analyzed the genes involved in the pathogenesis, development, and progression of endometriosis. The data extraction by text mining of the endometriosis-related genes in the PubMed database was based on natural language processing, and the data were filtered to remove false positives. Using data from the text mining and gene network information as input for the web-based tool, 15,207 endometriosis-related genes were ranked according to their score in the database. Characterization of the filtered gene set through gene ontology, pathway, and network analysis provided information about the numerous mechanisms hypothesized to be responsible for the establishment of ectopic endometrial tissue, as well as the migration, implantation, survival, and proliferation of ectopic endometrial cells. Finally, the human genome was scanned through various databases using filtered genes as a seed to determine novel genes that might also be involved in the pathogenesis of endometriosis but which have not yet been characterized. These genes could be promising candidates to serve as useful diagnostic biomarkers and therapeutic targets in the management of endometriosis. PMID:29750165

How Artificial Intelligence Can Improve Our Understanding of the Genes Associated with Endometriosis: Natural Language Processing of the PubMed Database.

PubMed

Bouaziz, J; Mashiach, R; Cohen, S; Kedem, A; Baron, A; Zajicek, M; Feldman, I; Seidman, D; Soriano, D

2018-01-01

Endometriosis is a disease characterized by the development of endometrial tissue outside the uterus, but its cause remains largely unknown. Numerous genes have been studied and proposed to help explain its pathogenesis. However, the large number of these candidate genes has made functional validation through experimental methodologies nearly impossible. Computational methods could provide a useful alternative for prioritizing those most likely to be susceptibility genes. Using artificial intelligence applied to text mining, this study analyzed the genes involved in the pathogenesis, development, and progression of endometriosis. The data extraction by text mining of the endometriosis-related genes in the PubMed database was based on natural language processing, and the data were filtered to remove false positives. Using data from the text mining and gene network information as input for the web-based tool, 15,207 endometriosis-related genes were ranked according to their score in the database. Characterization of the filtered gene set through gene ontology, pathway, and network analysis provided information about the numerous mechanisms hypothesized to be responsible for the establishment of ectopic endometrial tissue, as well as the migration, implantation, survival, and proliferation of ectopic endometrial cells. Finally, the human genome was scanned through various databases using filtered genes as a seed to determine novel genes that might also be involved in the pathogenesis of endometriosis but which have not yet been characterized. These genes could be promising candidates to serve as useful diagnostic biomarkers and therapeutic targets in the management of endometriosis.

The National NeuroAIDS Tissue Consortium (NNTC) Database: an integrated database for HIV-related studies

PubMed Central

Cserhati, Matyas F.; Pandey, Sanjit; Beaudoin, James J.; Baccaglini, Lorena; Guda, Chittibabu; Fox, Howard S.

2015-01-01

We herein present the National NeuroAIDS Tissue Consortium-Data Coordinating Center (NNTC-DCC) database, which is the only available database for neuroAIDS studies that contains data in an integrated, standardized form. This database has been created in conjunction with the NNTC, which provides human tissue and biofluid samples to individual researchers to conduct studies focused on neuroAIDS. The database contains experimental datasets from 1206 subjects for the following categories (which are further broken down into subcategories): gene expression, genotype, proteins, endo-exo-chemicals, morphometrics and other (miscellaneous) data. The database also contains a wide variety of downloadable data and metadata for 95 HIV-related studies covering 170 assays from 61 principal investigators. The data represent 76 tissue types, 25 measurement types, and 38 technology types, and reaches a total of 33 017 407 data points. We used the ISA platform to create the database and develop a searchable web interface for querying the data. A gene search tool is also available, which searches for NCBI GEO datasets associated with selected genes. The database is manually curated with many user-friendly features, and is cross-linked to the NCBI, HUGO and PubMed databases. A free registration is required for qualified users to access the database. Database URL: http://nntc-dcc.unmc.edu PMID:26228431

CardioTF, a database of deconstructing transcriptional circuits in the heart system

PubMed Central

2016-01-01

Background: Information on cardiovascular gene transcription is fragmented and far behind the present requirements of the systems biology field. To create a comprehensive source of data for cardiovascular gene regulation and to facilitate a deeper understanding of genomic data, the CardioTF database was constructed. The purpose of this database is to collate information on cardiovascular transcription factors (TFs), position weight matrices (PWMs), and enhancer sequences discovered using the ChIP-seq method. Methods: The Naïve-Bayes algorithm was used to classify literature and identify all PubMed abstracts on cardiovascular development. The natural language learning tool GNAT was then used to identify corresponding gene names embedded within these abstracts. Local Perl scripts were used to integrate and dump data from public databases into the MariaDB management system (MySQL). In-house R scripts were written to analyze and visualize the results. Results: Known cardiovascular TFs from humans and human homologs from fly, Ciona, zebrafish, frog, chicken, and mouse were identified and deposited in the database. PWMs from Jaspar, hPDI, and UniPROBE databases were deposited in the database and can be retrieved using their corresponding TF names. Gene enhancer regions from various sources of ChIP-seq data were deposited into the database and were able to be visualized by graphical output. Besides biocuration, mouse homologs of the 81 core cardiac TFs were selected using a Naïve-Bayes approach and then by intersecting four independent data sources: RNA profiling, expert annotation, PubMed abstracts and phenotype. Discussion: The CardioTF database can be used as a portal to construct transcriptional network of cardiac development. Availability and Implementation: Database URL: http://www.cardiosignal.org/database/cardiotf.html. PMID:27635320

CardioTF, a database of deconstructing transcriptional circuits in the heart system.

PubMed

Zhen, Yisong

2016-01-01

Information on cardiovascular gene transcription is fragmented and far behind the present requirements of the systems biology field. To create a comprehensive source of data for cardiovascular gene regulation and to facilitate a deeper understanding of genomic data, the CardioTF database was constructed. The purpose of this database is to collate information on cardiovascular transcription factors (TFs), position weight matrices (PWMs), and enhancer sequences discovered using the ChIP-seq method. The Naïve-Bayes algorithm was used to classify literature and identify all PubMed abstracts on cardiovascular development. The natural language learning tool GNAT was then used to identify corresponding gene names embedded within these abstracts. Local Perl scripts were used to integrate and dump data from public databases into the MariaDB management system (MySQL). In-house R scripts were written to analyze and visualize the results. Known cardiovascular TFs from humans and human homologs from fly, Ciona, zebrafish, frog, chicken, and mouse were identified and deposited in the database. PWMs from Jaspar, hPDI, and UniPROBE databases were deposited in the database and can be retrieved using their corresponding TF names. Gene enhancer regions from various sources of ChIP-seq data were deposited into the database and were able to be visualized by graphical output. Besides biocuration, mouse homologs of the 81 core cardiac TFs were selected using a Naïve-Bayes approach and then by intersecting four independent data sources: RNA profiling, expert annotation, PubMed abstracts and phenotype. The CardioTF database can be used as a portal to construct transcriptional network of cardiac development. Database URL: http://www.cardiosignal.org/database/cardiotf.html.

The database on transgenic luminescent microorganisms as an instrument of studying a microbial component of closed ecosystems

NASA Astrophysics Data System (ADS)

Boyandin, A. N.; Lankin, Y. P.; Kargatova, T. V.; Popova, L. Y.; Pechurkin, N. S.

Luminescent transgenic microorganisms are widely used for study of microbial communities' functioning including closed ones. Bioluminescence is of high sensitive to effects of different environmental factors. Integration of lux-genes into different metabolic ways allows studying many aspects of microorganisms' life permitting to carry out measurements in situ. There is much information about applications of bioluminescent bacteria in different researches. But for effective using these data their summarizing and accumulation in common source is required. Therefore an information system on characteristics of transgenic microorganisms with cloned lux-genes was created. The database and client software related were developed. A database structure includes information on common characteristics of cloned lux-genes, their sources and properties, on regulation of gene expression in bacterial cells, on dependence of bioluminescence manifestation on biotic, abiotic and anthropogenic environmental factors. The database also can store description of changes in bacterial populations depending on environmental changes. The database created allows storing and using bibliographic information and also links to web sites of world collections of microorganisms. Internet publishing software permitting to open access to the database through the Internet is developed.

Database resources of the National Center for Biotechnology Information

PubMed Central

Sayers, Eric W.; Barrett, Tanya; Benson, Dennis A.; Bolton, Evan; Bryant, Stephen H.; Canese, Kathi; Chetvernin, Vyacheslav; Church, Deanna M.; DiCuccio, Michael; Federhen, Scott; Feolo, Michael; Fingerman, Ian M.; Geer, Lewis Y.; Helmberg, Wolfgang; Kapustin, Yuri; Krasnov, Sergey; Landsman, David; Lipman, David J.; Lu, Zhiyong; Madden, Thomas L.; Madej, Tom; Maglott, Donna R.; Marchler-Bauer, Aron; Miller, Vadim; Karsch-Mizrachi, Ilene; Ostell, James; Panchenko, Anna; Phan, Lon; Pruitt, Kim D.; Schuler, Gregory D.; Sequeira, Edwin; Sherry, Stephen T.; Shumway, Martin; Sirotkin, Karl; Slotta, Douglas; Souvorov, Alexandre; Starchenko, Grigory; Tatusova, Tatiana A.; Wagner, Lukas; Wang, Yanli; Wilbur, W. John; Yaschenko, Eugene; Ye, Jian

2012-01-01

In addition to maintaining the GenBank® nucleic acid sequence database, the National Center for Biotechnology Information (NCBI) provides analysis and retrieval resources for the data in GenBank and other biological data made available through the NCBI Website. NCBI resources include Entrez, the Entrez Programming Utilities, MyNCBI, PubMed, PubMed Central (PMC), Gene, the NCBI Taxonomy Browser, BLAST, BLAST Link (BLink), Primer-BLAST, COBALT, Splign, RefSeq, UniGene, HomoloGene, ProtEST, dbMHC, dbSNP, dbVar, Epigenomics, Genome and related tools, the Map Viewer, Model Maker, Evidence Viewer, Trace Archive, Sequence Read Archive, BioProject, BioSample, Retroviral Genotyping Tools, HIV-1/Human Protein Interaction Database, Gene Expression Omnibus (GEO), Probe, Online Mendelian Inheritance in Animals (OMIA), the Molecular Modeling Database (MMDB), the Conserved Domain Database (CDD), the Conserved Domain Architecture Retrieval Tool (CDART), Biosystems, Protein Clusters and the PubChem suite of small molecule databases. Augmenting many of the Web applications are custom implementations of the BLAST program optimized to search specialized data sets. All of these resources can be accessed through the NCBI home page at www.ncbi.nlm.nih.gov. PMID:22140104

Database resources of the National Center for Biotechnology Information

PubMed Central

2013-01-01

In addition to maintaining the GenBank® nucleic acid sequence database, the National Center for Biotechnology Information (NCBI, http://www.ncbi.nlm.nih.gov) provides analysis and retrieval resources for the data in GenBank and other biological data made available through the NCBI web site. NCBI resources include Entrez, the Entrez Programming Utilities, MyNCBI, PubMed, PubMed Central, Gene, the NCBI Taxonomy Browser, BLAST, BLAST Link (BLink), Primer-BLAST, COBALT, Splign, RefSeq, UniGene, HomoloGene, ProtEST, dbMHC, dbSNP, dbVar, Epigenomics, the Genetic Testing Registry, Genome and related tools, the Map Viewer, Model Maker, Evidence Viewer, Trace Archive, Sequence Read Archive, BioProject, BioSample, Retroviral Genotyping Tools, HIV-1/Human Protein Interaction Database, Gene Expression Omnibus, Probe, Online Mendelian Inheritance in Animals, the Molecular Modeling Database, the Conserved Domain Database, the Conserved Domain Architecture Retrieval Tool, Biosystems, Protein Clusters and the PubChem suite of small molecule databases. Augmenting many of the web applications are custom implementations of the BLAST program optimized to search specialized data sets. All of these resources can be accessed through the NCBI home page. PMID:23193264

Database resources of the National Center for Biotechnology Information.

PubMed

Wheeler, David L; Barrett, Tanya; Benson, Dennis A; Bryant, Stephen H; Canese, Kathi; Chetvernin, Vyacheslav; Church, Deanna M; DiCuccio, Michael; Edgar, Ron; Federhen, Scott; Geer, Lewis Y; Kapustin, Yuri; Khovayko, Oleg; Landsman, David; Lipman, David J; Madden, Thomas L; Maglott, Donna R; Ostell, James; Miller, Vadim; Pruitt, Kim D; Schuler, Gregory D; Sequeira, Edwin; Sherry, Steven T; Sirotkin, Karl; Souvorov, Alexandre; Starchenko, Grigory; Tatusov, Roman L; Tatusova, Tatiana A; Wagner, Lukas; Yaschenko, Eugene

2007-01-01

In addition to maintaining the GenBank nucleic acid sequence database, the National Center for Biotechnology Information (NCBI) provides analysis and retrieval resources for the data in GenBank and other biological data made available through NCBI's Web site. NCBI resources include Entrez, the Entrez Programming Utilities, My NCBI, PubMed, PubMed Central, Entrez Gene, the NCBI Taxonomy Browser, BLAST, BLAST Link(BLink), Electronic PCR, OrfFinder, Spidey, Splign, RefSeq, UniGene, HomoloGene, ProtEST, dbMHC, dbSNP, Cancer Chromosomes, Entrez Genome, Genome Project and related tools, the Trace and Assembly Archives, the Map Viewer, Model Maker, Evidence Viewer, Clusters of Orthologous Groups (COGs), Viral Genotyping Tools, Influenza Viral Resources, HIV-1/Human Protein Interaction Database, Gene Expression Omnibus (GEO), Entrez Probe, GENSAT, Online Mendelian Inheritance in Man (OMIM), Online Mendelian Inheritance in Animals (OMIA), the Molecular Modeling Database (MMDB), the Conserved Domain Database (CDD), the Conserved Domain Architecture Retrieval Tool (CDART) and the PubChem suite of small molecule databases. Augmenting many of the Web applications are custom implementations of the BLAST program optimized to search specialized data sets. These resources can be accessed through the NCBI home page at www.ncbi.nlm.nih.gov.

Database resources of the National Center for Biotechnology Information.

PubMed

Sayers, Eric W; Barrett, Tanya; Benson, Dennis A; Bryant, Stephen H; Canese, Kathi; Chetvernin, Vyacheslav; Church, Deanna M; DiCuccio, Michael; Edgar, Ron; Federhen, Scott; Feolo, Michael; Geer, Lewis Y; Helmberg, Wolfgang; Kapustin, Yuri; Landsman, David; Lipman, David J; Madden, Thomas L; Maglott, Donna R; Miller, Vadim; Mizrachi, Ilene; Ostell, James; Pruitt, Kim D; Schuler, Gregory D; Sequeira, Edwin; Sherry, Stephen T; Shumway, Martin; Sirotkin, Karl; Souvorov, Alexandre; Starchenko, Grigory; Tatusova, Tatiana A; Wagner, Lukas; Yaschenko, Eugene; Ye, Jian

2009-01-01

In addition to maintaining the GenBank nucleic acid sequence database, the National Center for Biotechnology Information (NCBI) provides analysis and retrieval resources for the data in GenBank and other biological data made available through the NCBI web site. NCBI resources include Entrez, the Entrez Programming Utilities, MyNCBI, PubMed, PubMed Central, Entrez Gene, the NCBI Taxonomy Browser, BLAST, BLAST Link (BLink), Electronic PCR, OrfFinder, Spidey, Splign, RefSeq, UniGene, HomoloGene, ProtEST, dbMHC, dbSNP, Cancer Chromosomes, Entrez Genomes and related tools, the Map Viewer, Model Maker, Evidence Viewer, Clusters of Orthologous Groups (COGs), Retroviral Genotyping Tools, HIV-1/Human Protein Interaction Database, Gene Expression Omnibus (GEO), Entrez Probe, GENSAT, Online Mendelian Inheritance in Man (OMIM), Online Mendelian Inheritance in Animals (OMIA), the Molecular Modeling Database (MMDB), the Conserved Domain Database (CDD), the Conserved Domain Architecture Retrieval Tool (CDART) and the PubChem suite of small molecule databases. Augmenting many of the web applications is custom implementation of the BLAST program optimized to search specialized data sets. All of the resources can be accessed through the NCBI home page at www.ncbi.nlm.nih.gov.

Reconstruction of a Functional Human Gene Network, with an Application for Prioritizing Positional Candidate Genes

PubMed Central

Franke, Lude; Bakel, Harm van; Fokkens, Like; de Jong, Edwin D.; Egmont-Petersen, Michael; Wijmenga, Cisca

2006-01-01

Most common genetic disorders have a complex inheritance and may result from variants in many genes, each contributing only weak effects to the disease. Pinpointing these disease genes within the myriad of susceptibility loci identified in linkage studies is difficult because these loci may contain hundreds of genes. However, in any disorder, most of the disease genes will be involved in only a few different molecular pathways. If we know something about the relationships between the genes, we can assess whether some genes (which may reside in different loci) functionally interact with each other, indicating a joint basis for the disease etiology. There are various repositories of information on pathway relationships. To consolidate this information, we developed a functional human gene network that integrates information on genes and the functional relationships between genes, based on data from the Kyoto Encyclopedia of Genes and Genomes, the Biomolecular Interaction Network Database, Reactome, the Human Protein Reference Database, the Gene Ontology database, predicted protein-protein interactions, human yeast two-hybrid interactions, and microarray coexpressions. We applied this network to interrelate positional candidate genes from different disease loci and then tested 96 heritable disorders for which the Online Mendelian Inheritance in Man database reported at least three disease genes. Artificial susceptibility loci, each containing 100 genes, were constructed around each disease gene, and we used the network to rank these genes on the basis of their functional interactions. By following up the top five genes per artificial locus, we were able to detect at least one known disease gene in 54% of the loci studied, representing a 2.8-fold increase over random selection. This suggests that our method can significantly reduce the cost and effort of pinpointing true disease genes in analyses of disorders for which numerous loci have been reported but for which most of the genes are unknown. PMID:16685651

A-WINGS: an integrated genome database for Pleurocybella porrigens (Angel's wing oyster mushroom, Sugihiratake).

PubMed

Yamamoto, Naoki; Suzuki, Tomohiro; Kobayashi, Masaaki; Dohra, Hideo; Sasaki, Yohei; Hirai, Hirofumi; Yokoyama, Koji; Kawagishi, Hirokazu; Yano, Kentaro

2014-12-03

The angel's wing oyster mushroom (Pleurocybella porrigens, Sugihiratake) is a well-known delicacy. However, its potential risk in acute encephalopathy was recently revealed by a food poisoning incident. To disclose the genes underlying the accident and provide mechanistic insight, we seek to develop an information infrastructure containing omics data. In our previous work, we sequenced the genome and transcriptome using next-generation sequencing techniques. The next step in achieving our goal is to develop a web database to facilitate the efficient mining of large-scale omics data and identification of genes specifically expressed in the mushroom. This paper introduces a web database A-WINGS (http://bioinf.mind.meiji.ac.jp/a-wings/) that provides integrated genomic and transcriptomic information for the angel's wing oyster mushroom. The database contains structure and functional annotations of transcripts and gene expressions. Functional annotations contain information on homologous sequences from NCBI nr and UniProt, Gene Ontology, and KEGG Orthology. Digital gene expression profiles were derived from RNA sequencing (RNA-seq) analysis in the fruiting bodies and mycelia. The omics information stored in the database is freely accessible through interactive and graphical interfaces by search functions that include 'GO TREE VIEW' browsing, keyword searches, and BLAST searches. The A-WINGS database will accelerate omics studies on specific aspects of the angel's wing oyster mushroom and the family Tricholomataceae.

BloodSpot: a database of gene expression profiles and transcriptional programs for healthy and malignant haematopoiesis.

PubMed

Bagger, Frederik Otzen; Sasivarevic, Damir; Sohi, Sina Hadi; Laursen, Linea Gøricke; Pundhir, Sachin; Sønderby, Casper Kaae; Winther, Ole; Rapin, Nicolas; Porse, Bo T

2016-01-04

Research on human and murine haematopoiesis has resulted in a vast number of gene-expression data sets that can potentially answer questions regarding normal and aberrant blood formation. To researchers and clinicians with limited bioinformatics experience, these data have remained available, yet largely inaccessible. Current databases provide information about gene-expression but fail to answer key questions regarding co-regulation, genetic programs or effect on patient survival. To address these shortcomings, we present BloodSpot (www.bloodspot.eu), which includes and greatly extends our previously released database HemaExplorer, a database of gene expression profiles from FACS sorted healthy and malignant haematopoietic cells. A revised interactive interface simultaneously provides a plot of gene expression along with a Kaplan-Meier analysis and a hierarchical tree depicting the relationship between different cell types in the database. The database now includes 23 high-quality curated data sets relevant to normal and malignant blood formation and, in addition, we have assembled and built a unique integrated data set, BloodPool. Bloodpool contains more than 2000 samples assembled from six independent studies on acute myeloid leukemia. Furthermore, we have devised a robust sample integration procedure that allows for sensitive comparison of user-supplied patient samples in a well-defined haematopoietic cellular space. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Integrated database for identifying candidate genes for Aspergillus flavus resistance in maize

PubMed Central

2010-01-01

Background Aspergillus flavus Link:Fr, an opportunistic fungus that produces aflatoxin, is pathogenic to maize and other oilseed crops. Aflatoxin is a potent carcinogen, and its presence markedly reduces the value of grain. Understanding and enhancing host resistance to A. flavus infection and/or subsequent aflatoxin accumulation is generally considered an efficient means of reducing grain losses to aflatoxin. Different proteomic, genomic and genetic studies of maize (Zea mays L.) have generated large data sets with the goal of identifying genes responsible for conferring resistance to A. flavus, or aflatoxin. Results In order to maximize the usage of different data sets in new studies, including association mapping, we have constructed a relational database with web interface integrating the results of gene expression, proteomic (both gel-based and shotgun), Quantitative Trait Loci (QTL) genetic mapping studies, and sequence data from the literature to facilitate selection of candidate genes for continued investigation. The Corn Fungal Resistance Associated Sequences Database (CFRAS-DB) (http://agbase.msstate.edu/) was created with the main goal of identifying genes important to aflatoxin resistance. CFRAS-DB is implemented using MySQL as the relational database management system running on a Linux server, using an Apache web server, and Perl CGI scripts as the web interface. The database and the associated web-based interface allow researchers to examine many lines of evidence (e.g. microarray, proteomics, QTL studies, SNP data) to assess the potential role of a gene or group of genes in the response of different maize lines to A. flavus infection and subsequent production of aflatoxin by the fungus. Conclusions CFRAS-DB provides the first opportunity to integrate data pertaining to the problem of A. flavus and aflatoxin resistance in maize in one resource and to support queries across different datasets. The web-based interface gives researchers different query options for mining the database across different types of experiments. The database is publically available at http://agbase.msstate.edu. PMID:20946609

Integrated database for identifying candidate genes for Aspergillus flavus resistance in maize.

PubMed

Kelley, Rowena Y; Gresham, Cathy; Harper, Jonathan; Bridges, Susan M; Warburton, Marilyn L; Hawkins, Leigh K; Pechanova, Olga; Peethambaran, Bela; Pechan, Tibor; Luthe, Dawn S; Mylroie, J E; Ankala, Arunkanth; Ozkan, Seval; Henry, W B; Williams, W P

2010-10-07

Aspergillus flavus Link:Fr, an opportunistic fungus that produces aflatoxin, is pathogenic to maize and other oilseed crops. Aflatoxin is a potent carcinogen, and its presence markedly reduces the value of grain. Understanding and enhancing host resistance to A. flavus infection and/or subsequent aflatoxin accumulation is generally considered an efficient means of reducing grain losses to aflatoxin. Different proteomic, genomic and genetic studies of maize (Zea mays L.) have generated large data sets with the goal of identifying genes responsible for conferring resistance to A. flavus, or aflatoxin. In order to maximize the usage of different data sets in new studies, including association mapping, we have constructed a relational database with web interface integrating the results of gene expression, proteomic (both gel-based and shotgun), Quantitative Trait Loci (QTL) genetic mapping studies, and sequence data from the literature to facilitate selection of candidate genes for continued investigation. The Corn Fungal Resistance Associated Sequences Database (CFRAS-DB) (http://agbase.msstate.edu/) was created with the main goal of identifying genes important to aflatoxin resistance. CFRAS-DB is implemented using MySQL as the relational database management system running on a Linux server, using an Apache web server, and Perl CGI scripts as the web interface. The database and the associated web-based interface allow researchers to examine many lines of evidence (e.g. microarray, proteomics, QTL studies, SNP data) to assess the potential role of a gene or group of genes in the response of different maize lines to A. flavus infection and subsequent production of aflatoxin by the fungus. CFRAS-DB provides the first opportunity to integrate data pertaining to the problem of A. flavus and aflatoxin resistance in maize in one resource and to support queries across different datasets. The web-based interface gives researchers different query options for mining the database across different types of experiments. The database is publically available at http://agbase.msstate.edu.

The YeastGenome app: the Saccharomyces Genome Database at your fingertips.

PubMed

Wong, Edith D; Karra, Kalpana; Hitz, Benjamin C; Hong, Eurie L; Cherry, J Michael

2013-01-01

The Saccharomyces Genome Database (SGD) is a scientific database that provides researchers with high-quality curated data about the genes and gene products of Saccharomyces cerevisiae. To provide instant and easy access to this information on mobile devices, we have developed YeastGenome, a native application for the Apple iPhone and iPad. YeastGenome can be used to quickly find basic information about S. cerevisiae genes and chromosomal features regardless of internet connectivity. With or without network access, you can view basic information and Gene Ontology annotations about a gene of interest by searching gene names and gene descriptions or by browsing the database within the app to find the gene of interest. With internet access, the app provides more detailed information about the gene, including mutant phenotypes, references and protein and genetic interactions, as well as provides hyperlinks to retrieve detailed information by showing SGD pages and views of the genome browser. SGD provides online help describing basic ways to navigate the mobile version of SGD, highlights key features and answers frequently asked questions related to the app. The app is available from iTunes (http://itunes.com/apps/yeastgenome). The YeastGenome app is provided freely as a service to our community, as part of SGD's mission to provide free and open access to all its data and annotations.

pGenN, a Gene Normalization Tool for Plant Genes and Proteins in Scientific Literature

PubMed Central

Ding, Ruoyao; Arighi, Cecilia N.; Lee, Jung-Youn; Wu, Cathy H.; Vijay-Shanker, K.

2015-01-01

Background Automatically detecting gene/protein names in the literature and connecting them to databases records, also known as gene normalization, provides a means to structure the information buried in free-text literature. Gene normalization is critical for improving the coverage of annotation in the databases, and is an essential component of many text mining systems and database curation pipelines. Methods In this manuscript, we describe a gene normalization system specifically tailored for plant species, called pGenN (pivot-based Gene Normalization). The system consists of three steps: dictionary-based gene mention detection, species assignment, and intra species normalization. We have developed new heuristics to improve each of these phases. Results We evaluated the performance of pGenN on an in-house expertly annotated corpus consisting of 104 plant relevant abstracts. Our system achieved an F-value of 88.9% (Precision 90.9% and Recall 87.2%) on this corpus, outperforming state-of-art systems presented in BioCreative III. We have processed over 440,000 plant-related Medline abstracts using pGenN. The gene normalization results are stored in a local database for direct query from the pGenN web interface (proteininformationresource.org/pgenn/). The annotated literature corpus is also publicly available through the PIR text mining portal (proteininformationresource.org/iprolink/). PMID:26258475

The mitochondrial DNA makeup of Romanians: A forensic mtDNA control region database and phylogenetic characterization.

PubMed

Turchi, Chiara; Stanciu, Florin; Paselli, Giorgia; Buscemi, Loredana; Parson, Walther; Tagliabracci, Adriano

2016-09-01

To evaluate the pattern of Romanian population from a mitochondrial perspective and to establish an appropriate mtDNA forensic database, we generated a high-quality mtDNA control region dataset from 407 Romanian subjects belonging to four major historical regions: Moldavia, Transylvania, Wallachia and Dobruja. The entire control region (CR) was analyzed by Sanger-type sequencing assays and the resulting 306 different haplotypes were classified into haplogroups according to the most updated mtDNA phylogeny. The Romanian gene pool is mainly composed of West Eurasian lineages H (31.7%), U (12.8%), J (10.8%), R (10.1%), T (9.1%), N (8.1%), HV (5.4%),K (3.7%), HV0 (4.2%), with exceptions of East Asian haplogroup M (3.4%) and African haplogroup L (0.7%). The pattern of mtDNA variation observed in this study indicates that the mitochondrial DNA pool is geographically homogeneous across Romania and that the haplogroup composition reveals signals of admixture of populations of different origin. The PCA scatterplot supported this scenario, with Romania located in southeastern Europe area, close to Bulgaria and Hungary, and as a borderland with respect to east Mediterranean and other eastern European countries. High haplotype diversity (0.993) and nucleotide diversity indices (0.00838±0.00426), together with low random match probability (0.0087) suggest the usefulness of this control region dataset as a forensic database in routine forensic mtDNA analysis and in the investigation of maternal genetic lineages in the Romanian population. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

CoReCG: a comprehensive database of genes associated with colon-rectal cancer

PubMed Central

Agarwal, Rahul; Kumar, Binayak; Jayadev, Msk; Raghav, Dhwani; Singh, Ashutosh

2016-01-01

Cancer of large intestine is commonly referred as colorectal cancer, which is also the third most frequently prevailing neoplasm across the globe. Though, much of work is being carried out to understand the mechanism of carcinogenesis and advancement of this disease but, fewer studies has been performed to collate the scattered information of alterations in tumorigenic cells like genes, mutations, expression changes, epigenetic alteration or post translation modification, genetic heterogeneity. Earlier findings were mostly focused on understanding etiology of colorectal carcinogenesis but less emphasis were given for the comprehensive review of the existing findings of individual studies which can provide better diagnostics based on the suggested markers in discrete studies. Colon Rectal Cancer Gene Database (CoReCG), contains 2056 colon-rectal cancer genes information involved in distinct colorectal cancer stages sourced from published literature with an effective knowledge based information retrieval system. Additionally, interactive web interface enriched with various browsing sections, augmented with advance search facility for querying the database is provided for user friendly browsing, online tools for sequence similarity searches and knowledge based schema ensures a researcher friendly information retrieval mechanism. Colorectal cancer gene database (CoReCG) is expected to be a single point source for identification of colorectal cancer-related genes, thereby helping with the improvement of classification, diagnosis and treatment of human cancers. Database URL: lms.snu.edu.in/corecg PMID:27114494

Ontology-oriented retrieval of putative microRNAs in Vitis vinifera via GrapeMiRNA: a web database of de novo predicted grape microRNAs.

PubMed

Lazzari, Barbara; Caprera, Andrea; Cestaro, Alessandro; Merelli, Ivan; Del Corvo, Marcello; Fontana, Paolo; Milanesi, Luciano; Velasco, Riccardo; Stella, Alessandra

2009-06-29

Two complete genome sequences are available for Vitis vinifera Pinot noir. Based on the sequence and gene predictions produced by the IASMA, we performed an in silico detection of putative microRNA genes and of their targets, and collected the most reliable microRNA predictions in a web database. The application is available at http://www.itb.cnr.it/ptp/grapemirna/. The program FindMiRNA was used to detect putative microRNA genes in the grape genome. A very high number of predictions was retrieved, calling for validation. Nine parameters were calculated and, based on the grape microRNAs dataset available at miRBase, thresholds were defined and applied to FindMiRNA predictions having targets in gene exons. In the resulting subset, predictions were ranked according to precursor positions and sequence similarity, and to target identity. To further validate FindMiRNA predictions, comparisons to the Arabidopsis genome, to the grape Genoscope genome, and to the grape EST collection were performed. Results were stored in a MySQL database and a web interface was prepared to query the database and retrieve predictions of interest. The GrapeMiRNA database encompasses 5,778 microRNA predictions spanning the whole grape genome. Predictions are integrated with information that can be of use in selection procedures. Tools added in the web interface also allow to inspect predictions according to gene ontology classes and metabolic pathways of targets. The GrapeMiRNA database can be of help in selecting candidate microRNA genes to be validated.

Update of the androgen receptor gene mutations database.

PubMed

Gottlieb, B; Beitel, L K; Lumbroso, R; Pinsky, L; Trifiro, M

1999-01-01

The current version of the androgen receptor (AR) gene mutations database is described. The total number of reported mutations has risen from 309 to 374 during the past year. We have expanded the database by adding information on AR-interacting proteins; and we have improved the database by identifying those mutation entries that have been updated. Mutations of unknown significance have now been reported in both the 5' and 3' untranslated regions of the AR gene, and in individuals who are somatic mosaics constitutionally. In addition, single nucleotide polymorphisms, including silent mutations, have been discovered in normal individuals and in individuals with male infertility. A mutation hotspot associated with prostatic cancer has been identified in exon 5. The database is available on the internet (http://www.mcgill.ca/androgendb/), from EMBL-European Bioinformatics Institute (ftp.ebi.ac.uk/pub/databases/androgen), or as a Macintosh FilemakerPro or Word file (MC33@musica.mcgill.ca). Copyright 1999 Wiley-Liss, Inc.

Database resources of the National Center for Biotechnology Information: 2002 update

PubMed Central

Wheeler, David L.; Church, Deanna M.; Lash, Alex E.; Leipe, Detlef D.; Madden, Thomas L.; Pontius, Joan U.; Schuler, Gregory D.; Schriml, Lynn M.; Tatusova, Tatiana A.; Wagner, Lukas; Rapp, Barbara A.

2002-01-01

In addition to maintaining the GenBank nucleic acid sequence database, the National Center for Biotechnology Information (NCBI) provides data analysis and retrieval resources that operate on the data in GenBank and a variety of other biological data made available through NCBI’s web site. NCBI data retrieval resources include Entrez, PubMed, LocusLink and the Taxonomy Browser. Data analysis resources include BLAST, Electronic PCR, OrfFinder, RefSeq, UniGene, HomoloGene, Database of Single Nucleotide Polymorphisms (dbSNP), Human Genome Sequencing, Human MapViewer, Human¡VMouse Homology Map, Cancer Chromosome Aberration Project (CCAP), Entrez Genomes, Clusters of Orthologous Groups (COGs) database, Retroviral Genotyping Tools, SAGEmap, Gene Expression Omnibus (GEO), Online Mendelian Inheritance in Man (OMIM), the Molecular Modeling Database (MMDB) and the Conserved Domain Database (CDD). Augmenting many of the web applications are custom implementations of the BLAST program optimized to search specialized data sets. All of the resources can be accessed through the NCBI home page at http://www.ncbi.nlm.nih.gov. PMID:11752242

The National NeuroAIDS Tissue Consortium (NNTC) Database: an integrated database for HIV-related studies.

PubMed

Cserhati, Matyas F; Pandey, Sanjit; Beaudoin, James J; Baccaglini, Lorena; Guda, Chittibabu; Fox, Howard S

2015-01-01

We herein present the National NeuroAIDS Tissue Consortium-Data Coordinating Center (NNTC-DCC) database, which is the only available database for neuroAIDS studies that contains data in an integrated, standardized form. This database has been created in conjunction with the NNTC, which provides human tissue and biofluid samples to individual researchers to conduct studies focused on neuroAIDS. The database contains experimental datasets from 1206 subjects for the following categories (which are further broken down into subcategories): gene expression, genotype, proteins, endo-exo-chemicals, morphometrics and other (miscellaneous) data. The database also contains a wide variety of downloadable data and metadata for 95 HIV-related studies covering 170 assays from 61 principal investigators. The data represent 76 tissue types, 25 measurement types, and 38 technology types, and reaches a total of 33,017,407 data points. We used the ISA platform to create the database and develop a searchable web interface for querying the data. A gene search tool is also available, which searches for NCBI GEO datasets associated with selected genes. The database is manually curated with many user-friendly features, and is cross-linked to the NCBI, HUGO and PubMed databases. A free registration is required for qualified users to access the database. © The Author(s) 2015. Published by Oxford University Press.

HAEdb: a novel interactive, locus-specific mutation database for the C1 inhibitor gene.

PubMed

Kalmár, Lajos; Hegedüs, Tamás; Farkas, Henriette; Nagy, Melinda; Tordai, Attila

2005-01-01

Hereditary angioneurotic edema (HAE) is an autosomal dominant disorder characterized by episodic local subcutaneous and submucosal edema and is caused by the deficiency of the activated C1 esterase inhibitor protein (C1-INH or C1INH; approved gene symbol SERPING1). Published C1-INH mutations are represented in large universal databases (e.g., OMIM, HGMD), but these databases update their data rather infrequently, they are not interactive, and they do not allow searches according to different criteria. The HAEdb, a C1-INH gene mutation database (http://hae.biomembrane.hu) was created to contribute to the following expectations: 1) help the comprehensive collection of information on genetic alterations of the C1-INH gene; 2) create a database in which data can be searched and compared according to several flexible criteria; and 3) provide additional help in new mutation identification. The website uses MySQL, an open-source, multithreaded, relational database management system. The user-friendly graphical interface was written in the PHP web programming language. The website consists of two main parts, the freely browsable search function, and the password-protected data deposition function. Mutations of the C1-INH gene are divided in two parts: gross mutations involving DNA fragments >1 kb, and micro mutations encompassing all non-gross mutations. Several attributes (e.g., affected exon, molecular consequence, family history) are collected for each mutation in a standardized form. This database may facilitate future comprehensive analyses of C1-INH mutations and also provide regular help for molecular diagnostic testing of HAE patients in different centers.

The University of Minnesota Biocatalysis/Biodegradation Database: specialized metabolism for functional genomics.

PubMed Central

Ellis, L B; Hershberger, C D; Wackett, L P

1999-01-01

The University of Minnesota Biocatalysis/Biodegradation Database (UM-BBD, http://www.labmed.umn.edu/umbbd/i nde x.html) first became available on the web in 1995 to provide information on microbial biocatalytic reactions of, and biodegradation pathways for, organic chemical compounds, especially those produced by man. Its goal is to become a representative database of biodegradation, spanning the diversity of known microbial metabolic routes, organic functional groups, and environmental conditions under which biodegradation occurs. The database can be used to enhance understanding of basic biochemistry, biocatalysis leading to speciality chemical manufacture, and biodegradation of environmental pollutants. It is also a resource for functional genomics, since it contains information on enzymes and genes involved in specialized metabolism not found in intermediary metabolism databases, and thus can assist in assigning functions to genes homologous to such less common genes. With information on >400 reactions and compounds, it is poised to become a resource for prediction of microbial biodegradation pathways for compounds it does not contain, a process complementary to predicting the functions of new classes of microbial genes. PMID:9847233

The Innate Immune Database (IIDB)

PubMed Central

Korb, Martin; Rust, Aistair G; Thorsson, Vesteinn; Battail, Christophe; Li, Bin; Hwang, Daehee; Kennedy, Kathleen A; Roach, Jared C; Rosenberger, Carrie M; Gilchrist, Mark; Zak, Daniel; Johnson, Carrie; Marzolf, Bruz; Aderem, Alan; Shmulevich, Ilya; Bolouri, Hamid

2008-01-01

Background As part of a National Institute of Allergy and Infectious Diseases funded collaborative project, we have performed over 150 microarray experiments measuring the response of C57/BL6 mouse bone marrow macrophages to toll-like receptor stimuli. These microarray expression profiles are available freely from our project web site . Here, we report the development of a database of computationally predicted transcription factor binding sites and related genomic features for a set of over 2000 murine immune genes of interest. Our database, which includes microarray co-expression clusters and a host of web-based query, analysis and visualization facilities, is available freely via the internet. It provides a broad resource to the research community, and a stepping stone towards the delineation of the network of transcriptional regulatory interactions underlying the integrated response of macrophages to pathogens. Description We constructed a database indexed on genes and annotations of the immediate surrounding genomic regions. To facilitate both gene-specific and systems biology oriented research, our database provides the means to analyze individual genes or an entire genomic locus. Although our focus to-date has been on mammalian toll-like receptor signaling pathways, our database structure is not limited to this subject, and is intended to be broadly applicable to immunology. By focusing on selected immune-active genes, we were able to perform computationally intensive expression and sequence analyses that would currently be prohibitive if applied to the entire genome. Using six complementary computational algorithms and methodologies, we identified transcription factor binding sites based on the Position Weight Matrices available in TRANSFAC. For one example transcription factor (ATF3) for which experimental data is available, over 50% of our predicted binding sites coincide with genome-wide chromatin immnuopreciptation (ChIP-chip) results. Our database can be interrogated via a web interface. Genomic annotations and binding site predictions can be automatically viewed with a customized version of the Argo genome browser. Conclusion We present the Innate Immune Database (IIDB) as a community resource for immunologists interested in gene regulatory systems underlying innate responses to pathogens. The database website can be freely accessed at . PMID:18321385

PRGdb: a bioinformatics platform for plant resistance gene analysis

PubMed Central

Sanseverino, Walter; Roma, Guglielmo; De Simone, Marco; Faino, Luigi; Melito, Sara; Stupka, Elia; Frusciante, Luigi; Ercolano, Maria Raffaella

2010-01-01

PRGdb is a web accessible open-source (http://www.prgdb.org) database that represents the first bioinformatic resource providing a comprehensive overview of resistance genes (R-genes) in plants. PRGdb holds more than 16 000 known and putative R-genes belonging to 192 plant species challenged by 115 different pathogens and linked with useful biological information. The complete database includes a set of 73 manually curated reference R-genes, 6308 putative R-genes collected from NCBI and 10463 computationally predicted putative R-genes. Thanks to a user-friendly interface, data can be examined using different query tools. A home-made prediction pipeline called Disease Resistance Analysis and Gene Orthology (DRAGO), based on reference R-gene sequence data, was developed to search for plant resistance genes in public datasets such as Unigene and Genbank. New putative R-gene classes containing unknown domain combinations were discovered and characterized. The development of the PRG platform represents an important starting point to conduct various experimental tasks. The inferred cross-link between genomic and phenotypic information allows access to a large body of information to find answers to several biological questions. The database structure also permits easy integration with other data types and opens up prospects for future implementations. PMID:19906694

Fastidious Gram-Negatives: Identification by the Vitek 2 Neisseria-Haemophilus Card and by Partial 16S rRNA Gene Sequencing Analysis.

PubMed

Sönksen, Ute Wolff; Christensen, Jens Jørgen; Nielsen, Lisbeth; Hesselbjerg, Annemarie; Hansen, Dennis Schrøder; Bruun, Brita

2010-12-31

Taxonomy and identification of fastidious Gram negatives are evolving and challenging. We compared identifications achieved with the Vitek 2 Neisseria-Haemophilus (NH) card and partial 16S rRNA gene sequence (526 bp stretch) analysis with identifications obtained with extensive phenotypic characterization using 100 fastidious Gram negative bacteria. Seventy-five strains represented 21 of the 26 taxa included in the Vitek 2 NH database and 25 strains represented related species not included in the database. Of the 100 strains, 31 were the type strains of the species. Vitek 2 NH identification results: 48 of 75 database strains were correctly identified, 11 strains gave `low discrimination´, seven strains were unidentified, and nine strains were misidentified. Identification of 25 non-database strains resulted in 14 strains incorrectly identified as belonging to species in the database. Partial 16S rRNA gene sequence analysis results: For 76 strains phenotypic and sequencing identifications were identical, for 23 strains the sequencing identifications were either probable or possible, and for one strain only the genus was confirmed. Thus, the Vitek 2 NH system identifies most of the commonly occurring species included in the database. Some strains of rarely occurring species and strains of non-database species closely related to database species cause problems. Partial 16S rRNA gene sequence analysis performs well, but does not always suffice, additional phenotypical characterization being useful for final identification.

Fastidious Gram-Negatives: Identification by the Vitek 2 Neisseria-Haemophilus Card and by Partial 16S rRNA Gene Sequencing Analysis

PubMed Central

Sönksen, Ute Wolff; Christensen, Jens Jørgen; Nielsen, Lisbeth; Hesselbjerg, Annemarie; Hansen, Dennis Schrøder; Bruun, Brita

2010-01-01

Taxonomy and identification of fastidious Gram negatives are evolving and challenging. We compared identifications achieved with the Vitek 2 Neisseria-Haemophilus (NH) card and partial 16S rRNA gene sequence (526 bp stretch) analysis with identifications obtained with extensive phenotypic characterization using 100 fastidious Gram negative bacteria. Seventy-five strains represented 21 of the 26 taxa included in the Vitek 2 NH database and 25 strains represented related species not included in the database. Of the 100 strains, 31 were the type strains of the species. Vitek 2 NH identification results: 48 of 75 database strains were correctly identified, 11 strains gave `low discrimination´, seven strains were unidentified, and nine strains were misidentified. Identification of 25 non-database strains resulted in 14 strains incorrectly identified as belonging to species in the database. Partial 16S rRNA gene sequence analysis results: For 76 strains phenotypic and sequencing identifications were identical, for 23 strains the sequencing identifications were either probable or possible, and for one strain only the genus was confirmed. Thus, the Vitek 2 NH system identifies most of the commonly occurring species included in the database. Some strains of rarely occurring species and strains of non-database species closely related to database species cause problems. Partial 16S rRNA gene sequence analysis performs well, but does not always suffice, additional phenotypical characterization being useful for final identification. PMID:21347215

Manual Gene Ontology annotation workflow at the Mouse Genome Informatics Database

PubMed Central

Drabkin, Harold J.; Blake, Judith A.

2012-01-01

The Mouse Genome Database, the Gene Expression Database and the Mouse Tumor Biology database are integrated components of the Mouse Genome Informatics (MGI) resource (http://www.informatics.jax.org). The MGI system presents both a consensus view and an experimental view of the knowledge concerning the genetics and genomics of the laboratory mouse. From genotype to phenotype, this information resource integrates information about genes, sequences, maps, expression analyses, alleles, strains and mutant phenotypes. Comparative mammalian data are also presented particularly in regards to the use of the mouse as a model for the investigation of molecular and genetic components of human diseases. These data are collected from literature curation as well as downloads of large datasets (SwissProt, LocusLink, etc.). MGI is one of the founding members of the Gene Ontology (GO) and uses the GO for functional annotation of genes. Here, we discuss the workflow associated with manual GO annotation at MGI, from literature collection to display of the annotations. Peer-reviewed literature is collected mostly from a set of journals available electronically. Selected articles are entered into a master bibliography and indexed to one of eight areas of interest such as ‘GO’ or ‘homology’ or ‘phenotype’. Each article is then either indexed to a gene already contained in the database or funneled through a separate nomenclature database to add genes. The master bibliography and associated indexing provide information for various curator-reports such as ‘papers selected for GO that refer to genes with NO GO annotation’. Once indexed, curators who have expertise in appropriate disciplines enter pertinent information. MGI makes use of several controlled vocabularies that ensure uniform data encoding, enable robust analysis and support the construction of complex queries. These vocabularies range from pick-lists to structured vocabularies such as the GO. All data associations are supported with statements of evidence as well as access to source publications. PMID:23110975

Manual Gene Ontology annotation workflow at the Mouse Genome Informatics Database.

PubMed

Drabkin, Harold J; Blake, Judith A

2012-01-01

The Mouse Genome Database, the Gene Expression Database and the Mouse Tumor Biology database are integrated components of the Mouse Genome Informatics (MGI) resource (http://www.informatics.jax.org). The MGI system presents both a consensus view and an experimental view of the knowledge concerning the genetics and genomics of the laboratory mouse. From genotype to phenotype, this information resource integrates information about genes, sequences, maps, expression analyses, alleles, strains and mutant phenotypes. Comparative mammalian data are also presented particularly in regards to the use of the mouse as a model for the investigation of molecular and genetic components of human diseases. These data are collected from literature curation as well as downloads of large datasets (SwissProt, LocusLink, etc.). MGI is one of the founding members of the Gene Ontology (GO) and uses the GO for functional annotation of genes. Here, we discuss the workflow associated with manual GO annotation at MGI, from literature collection to display of the annotations. Peer-reviewed literature is collected mostly from a set of journals available electronically. Selected articles are entered into a master bibliography and indexed to one of eight areas of interest such as 'GO' or 'homology' or 'phenotype'. Each article is then either indexed to a gene already contained in the database or funneled through a separate nomenclature database to add genes. The master bibliography and associated indexing provide information for various curator-reports such as 'papers selected for GO that refer to genes with NO GO annotation'. Once indexed, curators who have expertise in appropriate disciplines enter pertinent information. MGI makes use of several controlled vocabularies that ensure uniform data encoding, enable robust analysis and support the construction of complex queries. These vocabularies range from pick-lists to structured vocabularies such as the GO. All data associations are supported with statements of evidence as well as access to source publications.

Pan Air Geometry Management System (PAGMS): A data-base management system for PAN AIR geometry data

NASA Technical Reports Server (NTRS)

Hall, J. F.

1981-01-01

A data-base management system called PAGMS was developed to facilitate the data transfer in applications computer programs that create, modify, plot or otherwise manipulate PAN AIR type geometry data in preparation for input to the PAN AIR system of computer programs. PAGMS is composed of a series of FORTRAN callable subroutines which can be accessed directly from applications programs. Currently only a NOS version of PAGMS has been developed.

Comprehensive coverage of cardiovascular disease data in the disease portals at the Rat Genome Database.

PubMed

Wang, Shur-Jen; Laulederkind, Stanley J F; Hayman, G Thomas; Petri, Victoria; Smith, Jennifer R; Tutaj, Marek; Nigam, Rajni; Dwinell, Melinda R; Shimoyama, Mary

2016-08-01

Cardiovascular diseases are complex diseases caused by a combination of genetic and environmental factors. To facilitate progress in complex disease research, the Rat Genome Database (RGD) provides the community with a disease portal where genome objects and biological data related to cardiovascular diseases are systematically organized. The purpose of this study is to present biocuration at RGD, including disease, genetic, and pathway data. The RGD curation team uses controlled vocabularies/ontologies to organize data curated from the published literature or imported from disease and pathway databases. These organized annotations are associated with genes, strains, and quantitative trait loci (QTLs), thus linking functional annotations to genome objects. Screen shots from the web pages are used to demonstrate the organization of annotations at RGD. The human cardiovascular disease genes identified by annotations were grouped according to data sources and their annotation profiles were compared by in-house tools and other enrichment tools available to the public. The analysis results show that the imported cardiovascular disease genes from ClinVar and OMIM are functionally different from the RGD manually curated genes in terms of pathway and Gene Ontology annotations. The inclusion of disease genes from other databases enriches the collection of disease genes not only in quantity but also in quality. Copyright © 2016 the American Physiological Society.

AgeFactDB—the JenAge Ageing Factor Database—towards data integration in ageing research

PubMed Central

Hühne, Rolf; Thalheim, Torsten; Sühnel, Jürgen

2014-01-01

AgeFactDB (http://agefactdb.jenage.de) is a database aimed at the collection and integration of ageing phenotype data including lifespan information. Ageing factors are considered to be genes, chemical compounds or other factors such as dietary restriction, whose action results in a changed lifespan or another ageing phenotype. Any information related to the effects of ageing factors is called an observation and is presented on observation pages. To provide concise access to the complete information for a particular ageing factor, corresponding observations are also summarized on ageing factor pages. In a first step, ageing-related data were primarily taken from existing databases such as the Ageing Gene Database—GenAge, the Lifespan Observations Database and the Dietary Restriction Gene Database—GenDR. In addition, we have started to include new ageing-related information. Based on homology data taken from the HomoloGene Database, AgeFactDB also provides observation and ageing factor pages of genes that are homologous to known ageing-related genes. These homologues are considered as candidate or putative ageing-related genes. AgeFactDB offers a variety of search and browse options, and also allows the download of ageing factor or observation lists in TSV, CSV and XML formats. PMID:24217911

WormQTLHD--a web database for linking human disease to natural variation data in C. elegans.

PubMed

van der Velde, K Joeri; de Haan, Mark; Zych, Konrad; Arends, Danny; Snoek, L Basten; Kammenga, Jan E; Jansen, Ritsert C; Swertz, Morris A; Li, Yang

2014-01-01

Interactions between proteins are highly conserved across species. As a result, the molecular basis of multiple diseases affecting humans can be studied in model organisms that offer many alternative experimental opportunities. One such organism-Caenorhabditis elegans-has been used to produce much molecular quantitative genetics and systems biology data over the past decade. We present WormQTL(HD) (Human Disease), a database that quantitatively and systematically links expression Quantitative Trait Loci (eQTL) findings in C. elegans to gene-disease associations in man. WormQTL(HD), available online at http://www.wormqtl-hd.org, is a user-friendly set of tools to reveal functionally coherent, evolutionary conserved gene networks. These can be used to predict novel gene-to-gene associations and the functions of genes underlying the disease of interest. We created a new database that links C. elegans eQTL data sets to human diseases (34 337 gene-disease associations from OMIM, DGA, GWAS Central and NHGRI GWAS Catalogue) based on overlapping sets of orthologous genes associated to phenotypes in these two species. We utilized QTL results, high-throughput molecular phenotypes, classical phenotypes and genotype data covering different developmental stages and environments from WormQTL database. All software is available as open source, built on MOLGENIS and xQTL workbench.

Mechanisms of the epithelial-to-mesenchymal transition in sea urchin embryos

PubMed Central

Katow, Hideki

2015-01-01

Sea urchin mesenchyme is composed of the large micromere-derived spiculogenetic primary mesenchyme cells (PMC), veg2-tier macromere-derived non-spiculogenetic mesenchyme cells, the small micromere-derived germ cells, and the macro- and mesomere-derived neuronal mesenchyme cells. They are formed through the epithelial-to-mesenchymal transition (EMT) and possess multipotency, except PMCs that solely differentiate larval spicules. The process of EMT is associated with modification of epithelial cell surface property that includes loss of affinity to the apical and basal extracellular matrices, inter-epithelial cell adherens junctions and epithelial cell surface-specific proteins. These cell surface structures and molecules are endocytosed during EMT and utilized as initiators of cytoplasmic signaling pathways that often initiate protein phosphorylation to activate the gene regulatory networks. Acquisition of cell motility after EMT in these mesenchyme cells is associated with the expression of proteins such as Lefty, Snail and Seawi. Structural simplicity and genomic database of this model will further promote detailed EMT research. PMID:26716069

Plant Genome Resources at the National Center for Biotechnology Information

PubMed Central

Wheeler, David L.; Smith-White, Brian; Chetvernin, Vyacheslav; Resenchuk, Sergei; Dombrowski, Susan M.; Pechous, Steven W.; Tatusova, Tatiana; Ostell, James

2005-01-01

The National Center for Biotechnology Information (NCBI) integrates data from more than 20 biological databases through a flexible search and retrieval system called Entrez. A core Entrez database, Entrez Nucleotide, includes GenBank and is tightly linked to the NCBI Taxonomy database, the Entrez Protein database, and the scientific literature in PubMed. A suite of more specialized databases for genomes, genes, gene families, gene expression, gene variation, and protein domains dovetails with the core databases to make Entrez a powerful system for genomic research. Linked to the full range of Entrez databases is the NCBI Map Viewer, which displays aligned genetic, physical, and sequence maps for eukaryotic genomes including those of many plants. A specialized plant query page allow maps from all plant genomes covered by the Map Viewer to be searched in tandem to produce a display of aligned maps from several species. PlantBLAST searches against the sequences shown in the Map Viewer allow BLAST alignments to be viewed within a genomic context. In addition, precomputed sequence similarities, such as those for proteins offered by BLAST Link, enable fluid navigation from unannotated to annotated sequences, quickening the pace of discovery. NCBI Web pages for plants, such as Plant Genome Central, complete the system by providing centralized access to NCBI's genomic resources as well as links to organism-specific Web pages beyond NCBI. PMID:16010002

Construction of a rice glycoside hydrolase phylogenomic database and identification of targets for biofuel research

PubMed Central

Sharma, Rita; Cao, Peijian; Jung, Ki-Hong; Sharma, Manoj K.; Ronald, Pamela C.

2013-01-01

Glycoside hydrolases (GH) catalyze the hydrolysis of glycosidic bonds in cell wall polymers and can have major effects on cell wall architecture. Taking advantage of the massive datasets available in public databases, we have constructed a rice phylogenomic database of GHs (http://ricephylogenomics.ucdavis.edu/cellwalls/gh/). This database integrates multiple data types including the structural features, orthologous relationships, mutant availability, and gene expression patterns for each GH family in a phylogenomic context. The rice genome encodes 437 GH genes classified into 34 families. Based on pairwise comparison with eight dicot and four monocot genomes, we identified 138 GH genes that are highly diverged between monocots and dicots, 57 of which have diverged further in rice as compared with four monocot genomes scanned in this study. Chromosomal localization and expression analysis suggest a role for both whole-genome and localized gene duplications in expansion and diversification of GH families in rice. We examined the meta-profiles of expression patterns of GH genes in twenty different anatomical tissues of rice. Transcripts of 51 genes exhibit tissue or developmental stage-preferential expression, whereas, seventeen other genes preferentially accumulate in actively growing tissues. When queried in RiceNet, a probabilistic functional gene network that facilitates functional gene predictions, nine out of seventeen genes form a regulatory network with the well-characterized genes involved in biosynthesis of cell wall polymers including cellulose synthase and cellulose synthase-like genes of rice. Two-thirds of the GH genes in rice are up regulated in response to biotic and abiotic stress treatments indicating a role in stress adaptation. Our analyses identify potential GH targets for cell wall modification. PMID:23986771

Pithovirus sibericum, a new bona fide member of the "Fourth TRUC" club.

PubMed

Sharma, Vikas; Colson, Philippe; Chabrol, Olivier; Pontarotti, Pierre; Raoult, Didier

2015-01-01

Nucleocytoplasmic large DNA viruses, or representatives of the proposed order Megavirales, include giant viruses of Acanthamoeba that were discovered over the last 12 years and are bona fide microbes. Phylogenies based on a few genes conserved amongst these megaviruses and shared by microbes classified as Eukarya, Bacteria, and Archaea, allowed for delineation of a fourth monophylogenetic group or "TRUC" (Things Resisting Uncompleted Classification) composed of the Megavirales representatives. A new Megavirales member named Pithovirus sibericum was isolated from a >30,000-year-old dated Siberian permafrost sample. This virion is as large as recently described pandoraviruses but has a genome that is approximately three to four times shorter. Our objective was to update the classification of P. sibericum as a new member of the "Fourth TRUC" club. Phylogenetic trees were constructed based on four conserved ancient genes and a phyletic analysis was concurrently conducted based on the presence/absence patterns of a set of informational genes from members of Megavirales, Bacteria, Archaea, and Eukarya. Phylogenetic analyses based on the four conserved genes revealed that P. sibericum is part of the fourth TRUC composed of Megavirales members, and is closely related to the families Marseilleviridae and Ascoviridae/Iridoviridae. Additionally, hierarchical clustering delineated four branches, and showed that P. sibericum is part of this fourth TRUC. Overall, phylogenetic and phyletic analyses using informational genes clearly indicate that P. sibericum is a new bona fide member of the "Fourth TRUC" club composed of representatives of Megavirales, alongside Bacteria, Archaea, and Eukarya.

BIOSPIDA: A Relational Database Translator for NCBI.

PubMed

Hagen, Matthew S; Lee, Eva K

2010-11-13

As the volume and availability of biological databases continue widespread growth, it has become increasingly difficult for research scientists to identify all relevant information for biological entities of interest. Details of nucleotide sequences, gene expression, molecular interactions, and three-dimensional structures are maintained across many different databases. To retrieve all necessary information requires an integrated system that can query multiple databases with minimized overhead. This paper introduces a universal parser and relational schema translator that can be utilized for all NCBI databases in Abstract Syntax Notation (ASN.1). The data models for OMIM, Entrez-Gene, Pubmed, MMDB and GenBank have been successfully converted into relational databases and all are easily linkable helping to answer complex biological questions. These tools facilitate research scientists to locally integrate databases from NCBI without significant workload or development time.

dbCPG: A web resource for cancer predisposition genes.

PubMed

Wei, Ran; Yao, Yao; Yang, Wu; Zheng, Chun-Hou; Zhao, Min; Xia, Junfeng

2016-06-21

Cancer predisposition genes (CPGs) are genes in which inherited mutations confer highly or moderately increased risks of developing cancer. Identification of these genes and understanding the biological mechanisms that underlie them is crucial for the prevention, early diagnosis, and optimized management of cancer. Over the past decades, great efforts have been made to identify CPGs through multiple strategies. However, information on these CPGs and their molecular functions is scattered. To address this issue and provide a comprehensive resource for researchers, we developed the Cancer Predisposition Gene Database (dbCPG, Database URL: http://bioinfo.ahu.edu.cn:8080/dbCPG/index.jsp), the first literature-based gene resource for exploring human CPGs. It contains 827 human (724 protein-coding, 23 non-coding, and 80 unknown type genes), 637 rats, and 658 mouse CPGs. Furthermore, data mining was performed to gain insights into the understanding of the CPGs data, including functional annotation, gene prioritization, network analysis of prioritized genes and overlap analysis across multiple cancer types. A user-friendly web interface with multiple browse, search, and upload functions was also developed to facilitate access to the latest information on CPGs. Taken together, the dbCPG database provides a comprehensive data resource for further studies of cancer predisposition genes.

A novel method to identify pathways associated with renal cell carcinoma based on a gene co-expression network

PubMed Central

RUAN, XIYUN; LI, HONGYUN; LIU, BO; CHEN, JIE; ZHANG, SHIBAO; SUN, ZEQIANG; LIU, SHUANGQING; SUN, FAHAI; LIU, QINGYONG

2015-01-01

The aim of the present study was to develop a novel method for identifying pathways associated with renal cell carcinoma (RCC) based on a gene co-expression network. A framework was established where a co-expression network was derived from the database as well as various co-expression approaches. First, the backbone of the network based on differentially expressed (DE) genes between RCC patients and normal controls was constructed by the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database. The differentially co-expressed links were detected by Pearson’s correlation, the empirical Bayesian (EB) approach and Weighted Gene Co-expression Network Analysis (WGCNA). The co-expressed gene pairs were merged by a rank-based algorithm. We obtained 842; 371; 2,883 and 1,595 co-expressed gene pairs from the co-expression networks of the STRING database, Pearson’s correlation EB method and WGCNA, respectively. Two hundred and eighty-one differentially co-expressed (DC) gene pairs were obtained from the merged network using this novel method. Pathway enrichment analysis based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) database and the network enrichment analysis (NEA) method were performed to verify feasibility of the merged method. Results of the KEGG and NEA pathway analyses showed that the network was associated with RCC. The suggested method was computationally efficient to identify pathways associated with RCC and has been identified as a useful complement to traditional co-expression analysis. PMID:26058425

Database resources of the National Center for Biotechnology Information.

PubMed

Sayers, Eric W; Barrett, Tanya; Benson, Dennis A; Bolton, Evan; Bryant, Stephen H; Canese, Kathi; Chetvernin, Vyacheslav; Church, Deanna M; DiCuccio, Michael; Federhen, Scott; Feolo, Michael; Fingerman, Ian M; Geer, Lewis Y; Helmberg, Wolfgang; Kapustin, Yuri; Landsman, David; Lipman, David J; Lu, Zhiyong; Madden, Thomas L; Madej, Tom; Maglott, Donna R; Marchler-Bauer, Aron; Miller, Vadim; Mizrachi, Ilene; Ostell, James; Panchenko, Anna; Phan, Lon; Pruitt, Kim D; Schuler, Gregory D; Sequeira, Edwin; Sherry, Stephen T; Shumway, Martin; Sirotkin, Karl; Slotta, Douglas; Souvorov, Alexandre; Starchenko, Grigory; Tatusova, Tatiana A; Wagner, Lukas; Wang, Yanli; Wilbur, W John; Yaschenko, Eugene; Ye, Jian

2011-01-01

In addition to maintaining the GenBank® nucleic acid sequence database, the National Center for Biotechnology Information (NCBI) provides analysis and retrieval resources for the data in GenBank and other biological data made available through the NCBI Web site. NCBI resources include Entrez, the Entrez Programming Utilities, MyNCBI, PubMed, PubMed Central (PMC), Entrez Gene, the NCBI Taxonomy Browser, BLAST, BLAST Link (BLink), Primer-BLAST, COBALT, Electronic PCR, OrfFinder, Splign, ProSplign, RefSeq, UniGene, HomoloGene, ProtEST, dbMHC, dbSNP, dbVar, Epigenomics, Cancer Chromosomes, Entrez Genomes and related tools, the Map Viewer, Model Maker, Evidence Viewer, Trace Archive, Sequence Read Archive, Retroviral Genotyping Tools, HIV-1/Human Protein Interaction Database, Gene Expression Omnibus (GEO), Entrez Probe, GENSAT, Online Mendelian Inheritance in Man (OMIM), Online Mendelian Inheritance in Animals (OMIA), the Molecular Modeling Database (MMDB), the Conserved Domain Database (CDD), the Conserved Domain Architecture Retrieval Tool (CDART), IBIS, Biosystems, Peptidome, OMSSA, Protein Clusters and the PubChem suite of small molecule databases. Augmenting many of the Web applications are custom implementations of the BLAST program optimized to search specialized data sets. All of these resources can be accessed through the NCBI home page at www.ncbi.nlm.nih.gov.

miRWalk--database: prediction of possible miRNA binding sites by "walking" the genes of three genomes.

PubMed

Dweep, Harsh; Sticht, Carsten; Pandey, Priyanka; Gretz, Norbert

2011-10-01

MicroRNAs are small, non-coding RNA molecules that can complementarily bind to the mRNA 3'-UTR region to regulate the gene expression by transcriptional repression or induction of mRNA degradation. Increasing evidence suggests a new mechanism by which miRNAs may regulate target gene expression by binding in promoter and amino acid coding regions. Most of the existing databases on miRNAs are restricted to mRNA 3'-UTR region. To address this issue, we present miRWalk, a comprehensive database on miRNAs, which hosts predicted as well as validated miRNA binding sites, information on all known genes of human, mouse and rat. All mRNAs, mitochondrial genes and 10 kb upstream flanking regions of all known genes of human, mouse and rat were analyzed by using a newly developed algorithm named 'miRWalk' as well as with eight already established programs for putative miRNA binding sites. An automated and extensive text-mining search was performed on PubMed database to extract validated information on miRNAs. Combined information was put into a MySQL database. miRWalk presents predicted and validated information on miRNA-target interaction. Such a resource enables researchers to validate new targets of miRNA not only on 3'-UTR, but also on the other regions of all known genes. The 'Validated Target module' is updated every month and the 'Predicted Target module' is updated every 6 months. miRWalk is freely available at http://mirwalk.uni-hd.de/. Copyright © 2011 Elsevier Inc. All rights reserved.

Challenges of the information age: the impact of false discovery on pathway identification.

PubMed

Rog, Colin J; Chekuri, Srinivasa C; Edgerton, Mary E

2012-11-21

Pathways with members that have known relevance to a disease are used to support hypotheses generated from analyses of gene expression and proteomic studies. Using cancer as an example, the pitfalls of searching pathways databases as support for genes and proteins that could represent false discoveries are explored. The frequency with which networks could be generated from 100 instances each of randomly selected five and ten genes sets as input to MetaCore, a commercial pathways database, was measured. A PubMed search enumerated cancer-related literature published for any gene in the networks. Using three, two, and one maximum intervening step between input genes to populate the network, networks were generated with frequencies of 97%, 77%, and 7% using ten gene sets and 73%, 27%, and 1% using five gene sets. PubMed reported an average of 4225 cancer-related articles per network gene. This can be attributed to the richly populated pathways databases and the interest in the molecular basis of cancer. As information sources become enriched, they are more likely to generate plausible mechanisms for false discoveries.

PLEXdb: Gene expression resources for plants and plant pathogens

USDA-ARS?s Scientific Manuscript database

PLEXdb (Plant Expression Database), in partnership with community databases, supports comparisons of gene expression across multiple plant and pathogen species, promoting individuals and/or consortia to upload genome-scale data sets to contrast them to previously archived data. These analyses facili...

Biomine: predicting links between biological entities using network models of heterogeneous databases.

PubMed

Eronen, Lauri; Toivonen, Hannu

2012-06-06

Biological databases contain large amounts of data concerning the functions and associations of genes and proteins. Integration of data from several such databases into a single repository can aid the discovery of previously unknown connections spanning multiple types of relationships and databases. Biomine is a system that integrates cross-references from several biological databases into a graph model with multiple types of edges, such as protein interactions, gene-disease associations and gene ontology annotations. Edges are weighted based on their type, reliability, and informativeness. We present Biomine and evaluate its performance in link prediction, where the goal is to predict pairs of nodes that will be connected in the future, based on current data. In particular, we formulate protein interaction prediction and disease gene prioritization tasks as instances of link prediction. The predictions are based on a proximity measure computed on the integrated graph. We consider and experiment with several such measures, and perform a parameter optimization procedure where different edge types are weighted to optimize link prediction accuracy. We also propose a novel method for disease-gene prioritization, defined as finding a subset of candidate genes that cluster together in the graph. We experimentally evaluate Biomine by predicting future annotations in the source databases and prioritizing lists of putative disease genes. The experimental results show that Biomine has strong potential for predicting links when a set of selected candidate links is available. The predictions obtained using the entire Biomine dataset are shown to clearly outperform ones obtained using any single source of data alone, when different types of links are suitably weighted. In the gene prioritization task, an established reference set of disease-associated genes is useful, but the results show that under favorable conditions, Biomine can also perform well when no such information is available.The Biomine system is a proof of concept. Its current version contains 1.1 million entities and 8.1 million relations between them, with focus on human genetics. Some of its functionalities are available in a public query interface at http://biomine.cs.helsinki.fi, allowing searching for and visualizing connections between given biological entities.

The androgen receptor gene mutations database.

PubMed

Gottlieb, B; Trifiro, M; Lumbroso, R; Pinsky, L

1997-01-01

The current version of the androgen receptor (AR) gene mutations database is described. The total number of reported mutations has risen from 212 to 272. We have expanded the database: (i) by adding a large amount of new data on somatic mutations in prostatic cancer tissue; (ii) by defining a new constitutional phenotype, mild androgen insensitivity (MAI); (iii) by placing additional relevant information on an internet site (http://www.mcgill.ca/androgendb/ ). The database has allowed us to examine the contribution of CpG sites to the multiplicity of reports of the same mutation in different families. The database is also available from EMBL (ftp.ebi.ac.uk/pub/databases/androgen) or as a Macintosh Filemaker Pro or Word file (MC33@musica,mcgill.ca)

The androgen receptor gene mutations database.

PubMed Central

Gottlieb, B; Trifiro, M; Lumbroso, R; Pinsky, L

1997-01-01

The current version of the androgen receptor (AR) gene mutations database is described. The total number of reported mutations has risen from 212 to 272. We have expanded the database: (i) by adding a large amount of new data on somatic mutations in prostatic cancer tissue; (ii) by defining a new constitutional phenotype, mild androgen insensitivity (MAI); (iii) by placing additional relevant information on an internet site (http://www.mcgill.ca/androgendb/ ). The database has allowed us to examine the contribution of CpG sites to the multiplicity of reports of the same mutation in different families. The database is also available from EMBL (ftp.ebi.ac.uk/pub/databases/androgen) or as a Macintosh Filemaker Pro or Word file (MC33@musica,mcgill.ca) PMID:9016528

[Role and management of cancer clinical database in the application of gastric cancer precision medicine].

PubMed

Li, Yuanfang; Zhou, Zhiwei

2016-02-01

Precision medicine is a new medical concept and medical model, which is based on personalized medicine, rapid progress of genome sequencing technology and cross application of biological information and big data science. Precision medicine improves the diagnosis and treatment of gastric cancer to provide more convenience through more profound analyses of characteristics, pathogenesis and other core issues in gastric cancer. Cancer clinical database is important to promote the development of precision medicine. Therefore, it is necessary to pay close attention to the construction and management of the database. The clinical database of Sun Yat-sen University Cancer Center is composed of medical record database, blood specimen bank, tissue bank and medical imaging database. In order to ensure the good quality of the database, the design and management of the database should follow the strict standard operation procedure(SOP) model. Data sharing is an important way to improve medical research in the era of medical big data. The construction and management of clinical database must also be strengthened and innovated.

microRNAs Databases: Developmental Methodologies, Structural and Functional Annotations.

PubMed

Singh, Nagendra Kumar

2017-09-01

microRNA (miRNA) is an endogenous and evolutionary conserved non-coding RNA, involved in post-transcriptional process as gene repressor and mRNA cleavage through RNA-induced silencing complex (RISC) formation. In RISC, miRNA binds in complementary base pair with targeted mRNA along with Argonaut proteins complex, causes gene repression or endonucleolytic cleavage of mRNAs and results in many diseases and syndromes. After the discovery of miRNA lin-4 and let-7, subsequently large numbers of miRNAs were discovered by low-throughput and high-throughput experimental techniques along with computational process in various biological and metabolic processes. The miRNAs are important non-coding RNA for understanding the complex biological phenomena of organism because it controls the gene regulation. This paper reviews miRNA databases with structural and functional annotations developed by various researchers. These databases contain structural and functional information of animal, plant and virus miRNAs including miRNAs-associated diseases, stress resistance in plant, miRNAs take part in various biological processes, effect of miRNAs interaction on drugs and environment, effect of variance on miRNAs, miRNAs gene expression analysis, sequence of miRNAs, structure of miRNAs. This review focuses on the developmental methodology of miRNA databases such as computational tools and methods used for extraction of miRNAs annotation from different resources or through experiment. This study also discusses the efficiency of user interface design of every database along with current entry and annotations of miRNA (pathways, gene ontology, disease ontology, etc.). Here, an integrated schematic diagram of construction process for databases is also drawn along with tabular and graphical comparison of various types of entries in different databases. Aim of this paper is to present the importance of miRNAs-related resources at a single place.

SAMMD: Staphylococcus aureus microarray meta-database.

PubMed

Nagarajan, Vijayaraj; Elasri, Mohamed O

2007-10-02

Staphylococcus aureus is an important human pathogen, causing a wide variety of diseases ranging from superficial skin infections to severe life threatening infections. S. aureus is one of the leading causes of nosocomial infections. Its ability to resist multiple antibiotics poses a growing public health problem. In order to understand the mechanism of pathogenesis of S. aureus, several global expression profiles have been developed. These transcriptional profiles included regulatory mutants of S. aureus and growth of wild type under different growth conditions. The abundance of these profiles has generated a large amount of data without a uniform annotation system to comprehensively examine them. We report the development of the Staphylococcus aureus Microarray meta-database (SAMMD) which includes data from all the published transcriptional profiles. SAMMD is a web-accessible database that helps users to perform a variety of analysis against and within the existing transcriptional profiles. SAMMD is a relational database that uses MySQL as the back end and PHP/JavaScript/DHTML as the front end. The database is normalized and consists of five tables, which holds information about gene annotations, regulated gene lists, experimental details, references, and other details. SAMMD data is collected from the peer-reviewed published articles. Data extraction and conversion was done using perl scripts while data entry was done through phpMyAdmin tool. The database is accessible via a web interface that contains several features such as a simple search by ORF ID, gene name, gene product name, advanced search using gene lists, comparing among datasets, browsing, downloading, statistics, and help. The database is licensed under General Public License (GPL). SAMMD is hosted and available at http://www.bioinformatics.org/sammd/. Currently there are over 9500 entries for regulated genes, from 67 microarray experiments. SAMMD will help staphylococcal scientists to analyze their expression data and understand it at global level. It will also allow scientists to compare and contrast their transcriptome to that of the other published transcriptomes.

RaMP: A Comprehensive Relational Database of Metabolomics Pathways for Pathway Enrichment Analysis of Genes and Metabolites

PubMed Central

Zhang, Bofei; Hu, Senyang; Baskin, Elizabeth; Patt, Andrew; Siddiqui, Jalal K.

2018-01-01

The value of metabolomics in translational research is undeniable, and metabolomics data are increasingly generated in large cohorts. The functional interpretation of disease-associated metabolites though is difficult, and the biological mechanisms that underlie cell type or disease-specific metabolomics profiles are oftentimes unknown. To help fully exploit metabolomics data and to aid in its interpretation, analysis of metabolomics data with other complementary omics data, including transcriptomics, is helpful. To facilitate such analyses at a pathway level, we have developed RaMP (Relational database of Metabolomics Pathways), which combines biological pathways from the Kyoto Encyclopedia of Genes and Genomes (KEGG), Reactome, WikiPathways, and the Human Metabolome DataBase (HMDB). To the best of our knowledge, an off-the-shelf, public database that maps genes and metabolites to biochemical/disease pathways and can readily be integrated into other existing software is currently lacking. For consistent and comprehensive analysis, RaMP enables batch and complex queries (e.g., list all metabolites involved in glycolysis and lung cancer), can readily be integrated into pathway analysis tools, and supports pathway overrepresentation analysis given a list of genes and/or metabolites of interest. For usability, we have developed a RaMP R package (https://github.com/Mathelab/RaMP-DB), including a user-friendly RShiny web application, that supports basic simple and batch queries, pathway overrepresentation analysis given a list of genes or metabolites of interest, and network visualization of gene-metabolite relationships. The package also includes the raw database file (mysql dump), thereby providing a stand-alone downloadable framework for public use and integration with other tools. In addition, the Python code needed to recreate the database on another system is also publicly available (https://github.com/Mathelab/RaMP-BackEnd). Updates for databases in RaMP will be checked multiple times a year and RaMP will be updated accordingly. PMID:29470400

RaMP: A Comprehensive Relational Database of Metabolomics Pathways for Pathway Enrichment Analysis of Genes and Metabolites.

PubMed

Zhang, Bofei; Hu, Senyang; Baskin, Elizabeth; Patt, Andrew; Siddiqui, Jalal K; Mathé, Ewy A

2018-02-22

The value of metabolomics in translational research is undeniable, and metabolomics data are increasingly generated in large cohorts. The functional interpretation of disease-associated metabolites though is difficult, and the biological mechanisms that underlie cell type or disease-specific metabolomics profiles are oftentimes unknown. To help fully exploit metabolomics data and to aid in its interpretation, analysis of metabolomics data with other complementary omics data, including transcriptomics, is helpful. To facilitate such analyses at a pathway level, we have developed RaMP (Relational database of Metabolomics Pathways), which combines biological pathways from the Kyoto Encyclopedia of Genes and Genomes (KEGG), Reactome, WikiPathways, and the Human Metabolome DataBase (HMDB). To the best of our knowledge, an off-the-shelf, public database that maps genes and metabolites to biochemical/disease pathways and can readily be integrated into other existing software is currently lacking. For consistent and comprehensive analysis, RaMP enables batch and complex queries (e.g., list all metabolites involved in glycolysis and lung cancer), can readily be integrated into pathway analysis tools, and supports pathway overrepresentation analysis given a list of genes and/or metabolites of interest. For usability, we have developed a RaMP R package (https://github.com/Mathelab/RaMP-DB), including a user-friendly RShiny web application, that supports basic simple and batch queries, pathway overrepresentation analysis given a list of genes or metabolites of interest, and network visualization of gene-metabolite relationships. The package also includes the raw database file (mysql dump), thereby providing a stand-alone downloadable framework for public use and integration with other tools. In addition, the Python code needed to recreate the database on another system is also publicly available (https://github.com/Mathelab/RaMP-BackEnd). Updates for databases in RaMP will be checked multiple times a year and RaMP will be updated accordingly.

SAMMD: Staphylococcus aureus Microarray Meta-Database

PubMed Central

Nagarajan, Vijayaraj; Elasri, Mohamed O

2007-01-01

Background Staphylococcus aureus is an important human pathogen, causing a wide variety of diseases ranging from superficial skin infections to severe life threatening infections. S. aureus is one of the leading causes of nosocomial infections. Its ability to resist multiple antibiotics poses a growing public health problem. In order to understand the mechanism of pathogenesis of S. aureus, several global expression profiles have been developed. These transcriptional profiles included regulatory mutants of S. aureus and growth of wild type under different growth conditions. The abundance of these profiles has generated a large amount of data without a uniform annotation system to comprehensively examine them. We report the development of the Staphylococcus aureus Microarray meta-database (SAMMD) which includes data from all the published transcriptional profiles. SAMMD is a web-accessible database that helps users to perform a variety of analysis against and within the existing transcriptional profiles. Description SAMMD is a relational database that uses MySQL as the back end and PHP/JavaScript/DHTML as the front end. The database is normalized and consists of five tables, which holds information about gene annotations, regulated gene lists, experimental details, references, and other details. SAMMD data is collected from the peer-reviewed published articles. Data extraction and conversion was done using perl scripts while data entry was done through phpMyAdmin tool. The database is accessible via a web interface that contains several features such as a simple search by ORF ID, gene name, gene product name, advanced search using gene lists, comparing among datasets, browsing, downloading, statistics, and help. The database is licensed under General Public License (GPL). Conclusion SAMMD is hosted and available at . Currently there are over 9500 entries for regulated genes, from 67 microarray experiments. SAMMD will help staphylococcal scientists to analyze their expression data and understand it at global level. It will also allow scientists to compare and contrast their transcriptome to that of the other published transcriptomes. PMID:17910768

TabSQL: a MySQL tool to facilitate mapping user data to public databases.

PubMed

Xia, Xiao-Qin; McClelland, Michael; Wang, Yipeng

2010-06-23

With advances in high-throughput genomics and proteomics, it is challenging for biologists to deal with large data files and to map their data to annotations in public databases. We developed TabSQL, a MySQL-based application tool, for viewing, filtering and querying data files with large numbers of rows. TabSQL provides functions for downloading and installing table files from public databases including the Gene Ontology database (GO), the Ensembl databases, and genome databases from the UCSC genome bioinformatics site. Any other database that provides tab-delimited flat files can also be imported. The downloaded gene annotation tables can be queried together with users' data in TabSQL using either a graphic interface or command line. TabSQL allows queries across the user's data and public databases without programming. It is a convenient tool for biologists to annotate and enrich their data.

TabSQL: a MySQL tool to facilitate mapping user data to public databases

PubMed Central

2010-01-01

Background With advances in high-throughput genomics and proteomics, it is challenging for biologists to deal with large data files and to map their data to annotations in public databases. Results We developed TabSQL, a MySQL-based application tool, for viewing, filtering and querying data files with large numbers of rows. TabSQL provides functions for downloading and installing table files from public databases including the Gene Ontology database (GO), the Ensembl databases, and genome databases from the UCSC genome bioinformatics site. Any other database that provides tab-delimited flat files can also be imported. The downloaded gene annotation tables can be queried together with users' data in TabSQL using either a graphic interface or command line. Conclusions TabSQL allows queries across the user's data and public databases without programming. It is a convenient tool for biologists to annotate and enrich their data. PMID:20573251

NCBI GEO: mining millions of expression profiles--database and tools.

PubMed

Barrett, Tanya; Suzek, Tugba O; Troup, Dennis B; Wilhite, Stephen E; Ngau, Wing-Chi; Ledoux, Pierre; Rudnev, Dmitry; Lash, Alex E; Fujibuchi, Wataru; Edgar, Ron

2005-01-01

The Gene Expression Omnibus (GEO) at the National Center for Biotechnology Information (NCBI) is the largest fully public repository for high-throughput molecular abundance data, primarily gene expression data. The database has a flexible and open design that allows the submission, storage and retrieval of many data types. These data include microarray-based experiments measuring the abundance of mRNA, genomic DNA and protein molecules, as well as non-array-based technologies such as serial analysis of gene expression (SAGE) and mass spectrometry proteomic technology. GEO currently holds over 30,000 submissions representing approximately half a billion individual molecular abundance measurements, for over 100 organisms. Here, we describe recent database developments that facilitate effective mining and visualization of these data. Features are provided to examine data from both experiment- and gene-centric perspectives using user-friendly Web-based interfaces accessible to those without computational or microarray-related analytical expertise. The GEO database is publicly accessible through the World Wide Web at http://www.ncbi.nlm.nih.gov/geo.

PvTFDB: a Phaseolus vulgaris transcription factors database for expediting functional genomics in legumes

PubMed Central

Bhawna; Bonthala, V.S.; Gajula, MNV Prasad

2016-01-01

The common bean [Phaseolus vulgaris (L.)] is one of the essential proteinaceous vegetables grown in developing countries. However, its production is challenged by low yields caused by numerous biotic and abiotic stress conditions. Regulatory transcription factors (TFs) symbolize a key component of the genome and are the most significant targets for producing stress tolerant crop and hence functional genomic studies of these TFs are important. Therefore, here we have constructed a web-accessible TFs database for P. vulgaris, called PvTFDB, which contains 2370 putative TF gene models in 49 TF families. This database provides a comprehensive information for each of the identified TF that includes sequence data, functional annotation, SSRs with their primer sets, protein physical properties, chromosomal location, phylogeny, tissue-specific gene expression data, orthologues, cis-regulatory elements and gene ontology (GO) assignment. Altogether, this information would be used in expediting the functional genomic studies of a specific TF(s) of interest. The objectives of this database are to understand functional genomics study of common bean TFs and recognize the regulatory mechanisms underlying various stress responses to ease breeding strategy for variety production through a couple of search interfaces including gene ID, functional annotation and browsing interfaces including by family and by chromosome. This database will also serve as a promising central repository for researchers as well as breeders who are working towards crop improvement of legume crops. In addition, this database provide the user unrestricted public access and the user can download entire data present in the database freely. Database URL: http://www.multiomics.in/PvTFDB/ PMID:27465131

Detection of alternative splice variants at the proteome level in Aspergillus flavus.

PubMed

Chang, Kung-Yen; Georgianna, D Ryan; Heber, Steffen; Payne, Gary A; Muddiman, David C

2010-03-05

Identification of proteins from proteolytic peptides or intact proteins plays an essential role in proteomics. Researchers use search engines to match the acquired peptide sequences to the target proteins. However, search engines depend on protein databases to provide candidates for consideration. Alternative splicing (AS), the mechanism where the exon of pre-mRNAs can be spliced and rearranged to generate distinct mRNA and therefore protein variants, enable higher eukaryotic organisms, with only a limited number of genes, to have the requisite complexity and diversity at the proteome level. Multiple alternative isoforms from one gene often share common segments of sequences. However, many protein databases only include a limited number of isoforms to keep minimal redundancy. As a result, the database search might not identify a target protein even with high quality tandem MS data and accurate intact precursor ion mass. We computationally predicted an exhaustive list of putative isoforms of Aspergillus flavus proteins from 20 371 expressed sequence tags to investigate whether an alternative splicing protein database can assign a greater proportion of mass spectrometry data. The newly constructed AS database provided 9807 new alternatively spliced variants in addition to 12 832 previously annotated proteins. The searches of the existing tandem MS spectra data set using the AS database identified 29 new proteins encoded by 26 genes. Nine fungal genes appeared to have multiple protein isoforms. In addition to the discovery of splice variants, AS database also showed potential to improve genome annotation. In summary, the introduction of an alternative splicing database helps identify more proteins and unveils more information about a proteome.

RatMap--rat genome tools and data.

PubMed

Petersen, Greta; Johnson, Per; Andersson, Lars; Klinga-Levan, Karin; Gómez-Fabre, Pedro M; Ståhl, Fredrik

2005-01-01

The rat genome database RatMap (http://ratmap.org or http://ratmap.gen.gu.se) has been one of the main resources for rat genome information since 1994. The database is maintained by CMB-Genetics at Goteborg University in Sweden and provides information on rat genes, polymorphic rat DNA-markers and rat quantitative trait loci (QTLs), all curated at RatMap. The database is under the supervision of the Rat Gene and Nomenclature Committee (RGNC); thus much attention is paid to rat gene nomenclature. RatMap presents information on rat idiograms, karyotypes and provides a unified presentation of the rat genome sequence and integrated rat linkage maps. A set of tools is also available to facilitate the identification and characterization of rat QTLs, as well as the estimation of exon/intron number and sizes in individual rat genes. Furthermore, comparative gene maps of rat in regard to mouse and human are provided.

RatMap—rat genome tools and data

PubMed Central

Petersen, Greta; Johnson, Per; Andersson, Lars; Klinga-Levan, Karin; Gómez-Fabre, Pedro M.; Ståhl, Fredrik

2005-01-01

The rat genome database RatMap (http://ratmap.org or http://ratmap.gen.gu.se) has been one of the main resources for rat genome information since 1994. The database is maintained by CMB–Genetics at Göteborg University in Sweden and provides information on rat genes, polymorphic rat DNA-markers and rat quantitative trait loci (QTLs), all curated at RatMap. The database is under the supervision of the Rat Gene and Nomenclature Committee (RGNC); thus much attention is paid to rat gene nomenclature. RatMap presents information on rat idiograms, karyotypes and provides a unified presentation of the rat genome sequence and integrated rat linkage maps. A set of tools is also available to facilitate the identification and characterization of rat QTLs, as well as the estimation of exon/intron number and sizes in individual rat genes. Furthermore, comparative gene maps of rat in regard to mouse and human are provided. PMID:15608244

DroSpeGe: rapid access database for new Drosophila species genomes.

PubMed

Gilbert, Donald G

2007-01-01

The Drosophila species comparative genome database DroSpeGe (http://insects.eugenes.org/DroSpeGe/) provides genome researchers with rapid, usable access to 12 new and old Drosophila genomes, since its inception in 2004. Scientists can use, with minimal computing expertise, the wealth of new genome information for developing new insights into insect evolution. New genome assemblies provided by several sequencing centers have been annotated with known model organism gene homologies and gene predictions to provided basic comparative data. TeraGrid supplies the shared cyberinfrastructure for the primary computations. This genome database includes homologies to Drosophila melanogaster and eight other eukaryote model genomes, and gene predictions from several groups. BLAST searches of the newest assemblies are integrated with genome maps. GBrowse maps provide detailed views of cross-species aligned genomes. BioMart provides for data mining of annotations and sequences. Common chromosome maps identify major synteny among species. Potential gain and loss of genes is suggested by Gene Ontology groupings for genes of the new species. Summaries of essential genome statistics include sizes, genes found and predicted, homology among genomes, phylogenetic trees of species and comparisons of several gene predictions for sensitivity and specificity in finding new and known genes.

TrSDB: a proteome database of transcription factors

PubMed Central

Hermoso, Antoni; Aguilar, Daniel; Aviles, Francesc X.; Querol, Enrique

2004-01-01

TrSDB—TranScout Database—(http://ibb.uab.es/trsdb) is a proteome database of eukaryotic transcription factors based upon predicted motifs by TranScout and data sources such as InterPro and Gene Ontology Annotation. Nine eukaryotic proteomes are included in the current version. Extensive and diverse information for each database entry, different analyses considering TranScout classification and similarity relationships are offered for research on transcription factors or gene expression. PMID:14681387

The Clinical Next-Generation Sequencing Database: A Tool for the Unified Management of Clinical Information and Genetic Variants to Accelerate Variant Pathogenicity Classification.

PubMed

Nishio, Shin-Ya; Usami, Shin-Ichi

2017-03-01

Recent advances in next-generation sequencing (NGS) have given rise to new challenges due to the difficulties in variant pathogenicity interpretation and large dataset management, including many kinds of public population databases as well as public or commercial disease-specific databases. Here, we report a new database development tool, named the "Clinical NGS Database," for improving clinical NGS workflow through the unified management of variant information and clinical information. This database software offers a two-feature approach to variant pathogenicity classification. The first of these approaches is a phenotype similarity-based approach. This database allows the easy comparison of the detailed phenotype of each patient with the average phenotype of the same gene mutation at the variant or gene level. It is also possible to browse patients with the same gene mutation quickly. The other approach is a statistical approach to variant pathogenicity classification based on the use of the odds ratio for comparisons between the case and the control for each inheritance mode (families with apparently autosomal dominant inheritance vs. control, and families with apparently autosomal recessive inheritance vs. control). A number of case studies are also presented to illustrate the utility of this database. © 2016 The Authors. **Human Mutation published by Wiley Periodicals, Inc.

Analysis of the Genome and Chromium Metabolism-Related Genes of Serratia sp. S2.

PubMed

Dong, Lanlan; Zhou, Simin; He, Yuan; Jia, Yan; Bai, Qunhua; Deng, Peng; Gao, Jieying; Li, Yingli; Xiao, Hong

2018-05-01

This study is to investigate the genome sequence of Serratia sp. S2. The genomic DNA of Serratia sp. S2 was extracted and the sequencing library was constructed. The sequencing was carried out by Illumina 2000 and complete genomic sequences were obtained. Gene function annotation and bioinformatics analysis were performed by comparing with the known databases. The genome size of Serratia sp. S2 was 5,604,115 bp and the G+C content was 57.61%. There were 5373 protein coding genes, and 3732, 3614, and 3942 genes were respectively annotated into the GO, KEGG, and COG databases. There were 12 genes related to chromium metabolism in the Serratia sp. S2 genome. The whole genome sequence of Serratia sp. S2 is submitted to the GenBank database with gene accession number of LNRP00000000. Our findings may provide theoretical basis for the subsequent development of new biotechnology to repair environmental chromium pollution.

Mining biological databases for candidate disease genes

NASA Astrophysics Data System (ADS)

Braun, Terry A.; Scheetz, Todd; Webster, Gregg L.; Casavant, Thomas L.

2001-07-01

The publicly-funded effort to sequence the complete nucleotide sequence of the human genome, the Human Genome Project (HGP), has currently produced more than 93% of the 3 billion nucleotides of the human genome into a preliminary `draft' format. In addition, several valuable sources of information have been developed as direct and indirect results of the HGP. These include the sequencing of model organisms (rat, mouse, fly, and others), gene discovery projects (ESTs and full-length), and new technologies such as expression analysis and resources (micro-arrays or gene chips). These resources are invaluable for the researchers identifying the functional genes of the genome that transcribe and translate into the transcriptome and proteome, both of which potentially contain orders of magnitude more complexity than the genome itself. Preliminary analyses of this data identified approximately 30,000 - 40,000 human `genes.' However, the bulk of the effort still remains -- to identify the functional and structural elements contained within the transcriptome and proteome, and to associate function in the transcriptome and proteome to genes. A fortuitous consequence of the HGP is the existence of hundreds of databases containing biological information that may contain relevant data pertaining to the identification of disease-causing genes. The task of mining these databases for information on candidate genes is a commercial application of enormous potential. We are developing a system to acquire and mine data from specific databases to aid our efforts to identify disease genes. A high speed cluster of Linux of workstations is used to analyze sequence and perform distributed sequence alignments as part of our data mining and processing. This system has been used to mine GeneMap99 sequences within specific genomic intervals to identify potential candidate disease genes associated with Bardet-Biedle Syndrome (BBS).

HuMiChip: Development of a Functional Gene Array for the Study of Human Microbiomes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tu, Q.; Deng, Ye; Lin, Lu

Microbiomes play very important roles in terms of nutrition, health and disease by interacting with their hosts. Based on sequence data currently available in public domains, we have developed a functional gene array to monitor both organismal and functional gene profiles of normal microbiota in human and mouse hosts, and such an array is called human and mouse microbiota array, HMM-Chip. First, seed sequences were identified from KEGG databases, and used to construct a seed database (seedDB) containing 136 gene families in 19 metabolic pathways closely related to human and mouse microbiomes. Second, a mother database (motherDB) was constructed withmore » 81 genomes of bacterial strains with 54 from gut and 27 from oral environments, and 16 metagenomes, and used for selection of genes and probe design. Gene prediction was performed by Glimmer3 for bacterial genomes, and by the Metagene program for metagenomes. In total, 228,240 and 801,599 genes were identified for bacterial genomes and metagenomes, respectively. Then the motherDB was searched against the seedDB using the HMMer program, and gene sequences in the motherDB that were highly homologous with seed sequences in the seedDB were used for probe design by the CommOligo software. Different degrees of specific probes, including gene-specific, inclusive and exclusive group-specific probes were selected. All candidate probes were checked against the motherDB and NCBI databases for specificity. Finally, 7,763 probes covering 91.2percent (12,601 out of 13,814) HMMer confirmed sequences from 75 bacterial genomes and 16 metagenomes were selected. This developed HMM-Chip is able to detect the diversity and abundance of functional genes, the gene expression of microbial communities, and potentially, the interactions of microorganisms and their hosts.« less

Gene Discovery in the Apicomplexa as Revealed by EST Sequencing and Assembly of a Comparative Gene Database

PubMed Central

Li, Li; Brunk, Brian P.; Kissinger, Jessica C.; Pape, Deana; Tang, Keliang; Cole, Robert H.; Martin, John; Wylie, Todd; Dante, Mike; Fogarty, Steven J.; Howe, Daniel K.; Liberator, Paul; Diaz, Carmen; Anderson, Jennifer; White, Michael; Jerome, Maria E.; Johnson, Emily A.; Radke, Jay A.; Stoeckert, Christian J.; Waterston, Robert H.; Clifton, Sandra W.; Roos, David S.; Sibley, L. David

2003-01-01

Large-scale EST sequencing projects for several important parasites within the phylum Apicomplexa were undertaken for the purpose of gene discovery. Included were several parasites of medical importance (Plasmodium falciparum, Toxoplasma gondii) and others of veterinary importance (Eimeria tenella, Sarcocystis neurona, and Neospora caninum). A total of 55,192 ESTs, deposited into dbEST/GenBank, were included in the analyses. The resulting sequences have been clustered into nonredundant gene assemblies and deposited into a relational database that supports a variety of sequence and text searches. This database has been used to compare the gene assemblies using BLAST similarity comparisons to the public protein databases to identify putative genes. Of these new entries, ∼15%–20% represent putative homologs with a conservative cutoff of p < 10−9, thus identifying many conserved genes that are likely to share common functions with other well-studied organisms. Gene assemblies were also used to identify strain polymorphisms, examine stage-specific expression, and identify gene families. An interesting class of genes that are confined to members of this phylum and not shared by plants, animals, or fungi, was identified. These genes likely mediate the novel biological features of members of the Apicomplexa and hence offer great potential for biological investigation and as possible therapeutic targets. [The sequence data from this study have been submitted to dbEST division of GenBank under accession nos.: Toxoplasma gondii: –, –, –, –, – , –, –, –, –. Plasmodium falciparum: –, –, –, –. Sarcocystis neurona: , , , , , , , , , , , , , –, –, –, –, –. Eimeria tenella: –, –, –, –, –, –, –, –, – , –, –, –, –, –, –, –, –, –, –, –. Neospora caninum: –, –, , – , –, –.] PMID:12618375

BIOSPIDA: A Relational Database Translator for NCBI

PubMed Central

Hagen, Matthew S.; Lee, Eva K.

2010-01-01

As the volume and availability of biological databases continue widespread growth, it has become increasingly difficult for research scientists to identify all relevant information for biological entities of interest. Details of nucleotide sequences, gene expression, molecular interactions, and three-dimensional structures are maintained across many different databases. To retrieve all necessary information requires an integrated system that can query multiple databases with minimized overhead. This paper introduces a universal parser and relational schema translator that can be utilized for all NCBI databases in Abstract Syntax Notation (ASN.1). The data models for OMIM, Entrez-Gene, Pubmed, MMDB and GenBank have been successfully converted into relational databases and all are easily linkable helping to answer complex biological questions. These tools facilitate research scientists to locally integrate databases from NCBI without significant workload or development time. PMID:21347013

A compatible exon-exon junction database for the identification of exon skipping events using tandem mass spectrum data.

PubMed

Mo, Fan; Hong, Xu; Gao, Feng; Du, Lin; Wang, Jun; Omenn, Gilbert S; Lin, Biaoyang

2008-12-16

Alternative splicing is an important gene regulation mechanism. It is estimated that about 74% of multi-exon human genes have alternative splicing. High throughput tandem (MS/MS) mass spectrometry provides valuable information for rapidly identifying potentially novel alternatively-spliced protein products from experimental datasets. However, the ability to identify alternative splicing events through tandem mass spectrometry depends on the database against which the spectra are searched. We wrote scripts in perl, Bioperl, mysql and Ensembl API and built a theoretical exon-exon junction protein database to account for all possible combinations of exons for a gene while keeping the frame of translation (i.e., keeping only in-phase exon-exon combinations) from the Ensembl Core Database. Using our liver cancer MS/MS dataset, we identified a total of 488 non-redundant peptides that represent putative exon skipping events. Our exon-exon junction database provides the scientific community with an efficient means to identify novel alternatively spliced (exon skipping) protein isoforms using mass spectrometry data. This database will be useful in annotating genome structures using rapidly accumulating proteomics data.

Database resources of the National Center for Biotechnology

PubMed Central

Wheeler, David L.; Church, Deanna M.; Federhen, Scott; Lash, Alex E.; Madden, Thomas L.; Pontius, Joan U.; Schuler, Gregory D.; Schriml, Lynn M.; Sequeira, Edwin; Tatusova, Tatiana A.; Wagner, Lukas

2003-01-01

In addition to maintaining the GenBank(R) nucleic acid sequence database, the National Center for Biotechnology Information (NCBI) provides data analysis and retrieval resources for the data in GenBank and other biological data made available through NCBI's Web site. NCBI resources include Entrez, PubMed, PubMed Central (PMC), LocusLink, the NCBITaxonomy Browser, BLAST, BLAST Link (BLink), Electronic PCR (e-PCR), Open Reading Frame (ORF) Finder, References Sequence (RefSeq), UniGene, HomoloGene, ProtEST, Database of Single Nucleotide Polymorphisms (dbSNP), Human/Mouse Homology Map, Cancer Chromosome Aberration Project (CCAP), Entrez Genomes and related tools, the Map Viewer, Model Maker (MM), Evidence Viewer (EV), Clusters of Orthologous Groups (COGs) database, Retroviral Genotyping Tools, SAGEmap, Gene Expression Omnibus (GEO), Online Mendelian Inheritance in Man (OMIM), the Molecular Modeling Database (MMDB), the Conserved Domain Database (CDD), and the Conserved Domain Architecture Retrieval Tool (CDART). Augmenting many of the Web applications are custom implementations of the BLAST program optimized to search specialized data sets. All of the resources can be accessed through the NCBI home page at: http://www.ncbi.nlm.nih.gov. PMID:12519941

Eukaryotic and prokaryotic promoter databases as valuable tools in exploring the regulation of gene transcription: a comprehensive overview.

PubMed

Majewska, Małgorzata; Wysokińska, Halina; Kuźma, Łukasz; Szymczyk, Piotr

2018-02-20

The complete exploration of the regulation of gene expression remains one of the top-priority goals for researchers. As the regulation is mainly controlled at the level of transcription by promoters, study on promoters and findings are of great importance. This review summarizes forty selected databases that centralize experimental and theoretical knowledge regarding the organization of promoters, interacting transcription factors (TFs) and microRNAs (miRNAs) in many eukaryotic and prokaryotic species. The presented databases offer researchers valuable support in elucidating the regulation of gene transcription. Copyright © 2017 Elsevier B.V. All rights reserved.

ImmunemiR - A Database of Prioritized Immune miRNA Disease Associations and its Interactome.

PubMed

Prabahar, Archana; Natarajan, Jeyakumar

2017-01-01

MicroRNAs are the key regulators of gene expression and their abnormal expression in the immune system may be associated with several human diseases such as inflammation, cancer and autoimmune diseases. Elucidation of miRNA disease association through the interactome will deepen the understanding of its disease mechanisms. A specialized database for immune miRNAs is highly desirable to demonstrate the immune miRNA disease associations in the interactome. miRNAs specific to immune related diseases were retrieved from curated databases such as HMDD, miR2disease and PubMed literature based on MeSH classification of immune system diseases. The additional data such as miRNA target genes, genes coding protein-protein interaction information were compiled from related resources. Further, miRNAs were prioritized to specific immune diseases using random walk ranking algorithm. In total 245 immune miRNAs associated with 92 OMIM disease categories were identified from external databases. The resultant data were compiled as ImmunemiR, a database of prioritized immune miRNA disease associations. This database provides both text based annotation information and network visualization of its interactome. To our knowledge, ImmunemiR is the first available database to provide a comprehensive repository of human immune disease associated miRNAs with network visualization options of its target genes, protein-protein interactions (PPI) and its disease associations. It is freely available at http://www.biominingbu.org/immunemir/. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Suitability of partial 16S ribosomal RNA gene sequence analysis for the identification of dangerous bacterial pathogens.

PubMed

Ruppitsch, W; Stöger, A; Indra, A; Grif, K; Schabereiter-Gurtner, C; Hirschl, A; Allerberger, F

2007-03-01

In a bioterrorism event a rapid tool is needed to identify relevant dangerous bacteria. The aim of the study was to assess the usefulness of partial 16S rRNA gene sequence analysis and the suitability of diverse databases for identifying dangerous bacterial pathogens. For rapid identification purposes a 500-bp fragment of the 16S rRNA gene of 28 isolates comprising Bacillus anthracis, Brucella melitensis, Burkholderia mallei, Burkholderia pseudomallei, Francisella tularensis, Yersinia pestis, and eight genus-related and unrelated control strains was amplified and sequenced. The obtained sequence data were submitted to three public and two commercial sequence databases for species identification. The most frequent reason for incorrect identification was the lack of the respective 16S rRNA gene sequences in the database. Sequence analysis of a 500-bp 16S rDNA fragment allows the rapid identification of dangerous bacterial species. However, for discrimination of closely related species sequencing of the entire 16S rRNA gene, additional sequencing of the 23S rRNA gene or sequencing of the 16S-23S rRNA intergenic spacer is essential. This work provides comprehensive information on the suitability of partial 16S rDNA analysis and diverse databases for rapid and accurate identification of dangerous bacterial pathogens.

Redundancy control in pathway databases (ReCiPa): an application for improving gene-set enrichment analysis in Omics studies and "Big data" biology.

PubMed

Vivar, Juan C; Pemu, Priscilla; McPherson, Ruth; Ghosh, Sujoy

2013-08-01

Abstract Unparalleled technological advances have fueled an explosive growth in the scope and scale of biological data and have propelled life sciences into the realm of "Big Data" that cannot be managed or analyzed by conventional approaches. Big Data in the life sciences are driven primarily via a diverse collection of 'omics'-based technologies, including genomics, proteomics, metabolomics, transcriptomics, metagenomics, and lipidomics. Gene-set enrichment analysis is a powerful approach for interrogating large 'omics' datasets, leading to the identification of biological mechanisms associated with observed outcomes. While several factors influence the results from such analysis, the impact from the contents of pathway databases is often under-appreciated. Pathway databases often contain variously named pathways that overlap with one another to varying degrees. Ignoring such redundancies during pathway analysis can lead to the designation of several pathways as being significant due to high content-similarity, rather than truly independent biological mechanisms. Statistically, such dependencies also result in correlated p values and overdispersion, leading to biased results. We investigated the level of redundancies in multiple pathway databases and observed large discrepancies in the nature and extent of pathway overlap. This prompted us to develop the application, ReCiPa (Redundancy Control in Pathway Databases), to control redundancies in pathway databases based on user-defined thresholds. Analysis of genomic and genetic datasets, using ReCiPa-generated overlap-controlled versions of KEGG and Reactome pathways, led to a reduction in redundancy among the top-scoring gene-sets and allowed for the inclusion of additional gene-sets representing possibly novel biological mechanisms. Using obesity as an example, bioinformatic analysis further demonstrated that gene-sets identified from overlap-controlled pathway databases show stronger evidence of prior association to obesity compared to pathways identified from the original databases.

RefPrimeCouch—a reference gene primer CouchApp

PubMed Central

Silbermann, Jascha; Wernicke, Catrin; Pospisil, Heike; Frohme, Marcus

2013-01-01

To support a quantitative real-time polymerase chain reaction standardization project, a new reference gene database application was required. The new database application was built with the explicit goal of simplifying not only the development process but also making the user interface more responsive and intuitive. To this end, CouchDB was used as the backend with a lightweight dynamic user interface implemented client-side as a one-page web application. Data entry and curation processes were streamlined using an OpenRefine-based workflow. The new RefPrimeCouch database application provides its data online under an Open Database License. Database URL: http://hpclife.th-wildau.de:5984/rpc/_design/rpc/view.html PMID:24368831

RefPrimeCouch--a reference gene primer CouchApp.

PubMed

Silbermann, Jascha; Wernicke, Catrin; Pospisil, Heike; Frohme, Marcus

2013-01-01

To support a quantitative real-time polymerase chain reaction standardization project, a new reference gene database application was required. The new database application was built with the explicit goal of simplifying not only the development process but also making the user interface more responsive and intuitive. To this end, CouchDB was used as the backend with a lightweight dynamic user interface implemented client-side as a one-page web application. Data entry and curation processes were streamlined using an OpenRefine-based workflow. The new RefPrimeCouch database application provides its data online under an Open Database License. Database URL: http://hpclife.th-wildau.de:5984/rpc/_design/rpc/view.html.

Polymorphisms in interleukins 17A and 17F genes and periodontitis: results from a meta-analysis.

PubMed

da Silva, Felipe Rodolfo Pereira; Pessoa, Larissa Dos Santos; Vasconcelos, Any Carolina Cardoso Guimarães; de Aquino Lima, Weberson; Alves, Even Herlany Pereira; Vasconcelos, Daniel Fernando Pereira

2017-12-01

Polymorphisms in inflammatory genes such as interleukins 17A and 17F are associated with the risk of development of periodontitis, although the results remain contradictory. Hence, the aim of this study was perform a meta-analysis focusing on two polymorphisms (rs2275913 and rs763780) in interleukins 17A and 17F genes, respectively, in both chronic (CP) and aggressive periodontitis (AgP). A review in literature was performed in several databases for studies published before 25, September 2016. The meta-analysis was obtained through the review manager statistical software (version 5.2) with odds ratio (OR) calculation and funnel plot (P < 0.05) for heterogeneity, as well as the comprehensive meta-analysis software (version 3.3.070) for the assessment of publication bias. Seven articles with 1540 participants composed the results in which the mutant allele in the rs2275913 polymorphism did not present significant association with the risk of CP or AgP (OR 1.56, 95% CI 0.77, 3.15, P = 0.21; OR 1.12, 95% CI 0.05, 23.44, P = 0.94, respectively) nor was the mutant allele in rs763780 associated with the risk of CP (OR 1.19, 95% CI 0.80, 1.76, P = 0.39) or AgP (OR 1.07, 95% CI 0.63, 1.84, P = 0.79). No bias of publication was observed by Egger's and Begg's tests in any allelic evaluation. This meta-analysis showed a non-significant association between the polymorphisms rs2275913 and rs763780 in interleukins 17A and 17F genes and chronic and aggressive periodontitis in the allelic evaluation.

Exploring Transcription Factors-microRNAs Co-regulation Networks in Schizophrenia.

PubMed

Xu, Yong; Yue, Weihua; Yao Shugart, Yin; Li, Sheng; Cai, Lei; Li, Qiang; Cheng, Zaohuo; Wang, Guoqiang; Zhou, Zhenhe; Jin, Chunhui; Yuan, Jianmin; Tian, Lin; Wang, Jun; Zhang, Kai; Zhang, Kerang; Liu, Sha; Song, Yuqing; Zhang, Fuquan

2016-07-01

Transcriptional factors (TFs) and microRNAs (miRNAs) have been recognized as 2 classes of principal gene regulators that may be responsible for genome coexpression changes observed in schizophrenia (SZ). This study aims to (1) identify differentially coexpressed genes (DCGs) in 3 mRNA expression microarray datasets; (2) explore potential interactions among the DCGs, and differentially expressed miRNAs identified in our dataset composed of early-onset SZ patients and healthy controls; (3) validate expression levels of some key transcripts; and (4) explore the druggability of DCGs using the curated database. We detected a differential coexpression network associated with SZ and found that 9 out of the 12 regulators were replicated in either of the 2 other datasets. Leveraging the differentially expressed miRNAs identified in our previous dataset, we constructed a miRNA-TF-gene network relevant to SZ, including an EGR1-miR-124-3p-SKIL feed-forward loop. Our real-time quantitative PCR analysis indicated the overexpression of miR-124-3p, the under expression of SKIL and EGR1 in the blood of SZ patients compared with controls, and the direction of change of miR-124-3p and SKIL mRNA levels in SZ cases were reversed after a 12-week treatment cycle. Our druggability analysis revealed that many of these genes have the potential to be drug targets. Together, our results suggest that coexpression network abnormalities driven by combinatorial and interactive action from TFs and miRNAs may contribute to the development of SZ and be relevant to the clinical treatment of the disease. © The Author 2015. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Exploring Transcription Factors-microRNAs Co-regulation Networks in Schizophrenia

PubMed Central

Xu, Yong; Yue, Weihua; Yao Shugart, Yin; Li, Sheng; Cai, Lei; Li, Qiang; Cheng, Zaohuo; Wang, Guoqiang; Zhou, Zhenhe; Jin, Chunhui; Yuan, Jianmin; Tian, Lin; Wang, Jun; Zhang, Kai; Zhang, Kerang; Liu, Sha; Song, Yuqing; Zhang, Fuquan

2016-01-01

Background: Transcriptional factors (TFs) and microRNAs (miRNAs) have been recognized as 2 classes of principal gene regulators that may be responsible for genome coexpression changes observed in schizophrenia (SZ). Methods: This study aims to (1) identify differentially coexpressed genes (DCGs) in 3 mRNA expression microarray datasets; (2) explore potential interactions among the DCGs, and differentially expressed miRNAs identified in our dataset composed of early-onset SZ patients and healthy controls; (3) validate expression levels of some key transcripts; and (4) explore the druggability of DCGs using the curated database. Results: We detected a differential coexpression network associated with SZ and found that 9 out of the 12 regulators were replicated in either of the 2 other datasets. Leveraging the differentially expressed miRNAs identified in our previous dataset, we constructed a miRNA–TF–gene network relevant to SZ, including an EGR1–miR-124-3p–SKIL feed-forward loop. Our real-time quantitative PCR analysis indicated the overexpression of miR-124-3p, the under expression of SKIL and EGR1 in the blood of SZ patients compared with controls, and the direction of change of miR-124-3p and SKIL mRNA levels in SZ cases were reversed after a 12-week treatment cycle. Our druggability analysis revealed that many of these genes have the potential to be drug targets. Conclusions: Together, our results suggest that coexpression network abnormalities driven by combinatorial and interactive action from TFs and miRNAs may contribute to the development of SZ and be relevant to the clinical treatment of the disease. PMID:26609121

Phenotypic evaluation and genetic dissection of resistance to Phytophthora sojae in the Chinese soybean mini core collection.

PubMed

Huang, Jing; Guo, Na; Li, Yinghui; Sun, Jutao; Hu, Guanjun; Zhang, Haipeng; Li, Yanfei; Zhang, Xing; Zhao, Jinming; Xing, Han; Qiu, Lijuan

2016-06-18

Phytophthora root and stem rot (PRR) caused by Phytophthora sojae is one of the most serious diseases affecting soybean (Glycine max (L.) Merr.) production all over the world. The most economical and environmentally-friendly way to control the disease is the exploration and utilization of resistant varieties. We screened a soybean mini core collection composed of 224 germplasm accessions for resistance against eleven P. sojae isolates. Soybean accessions from the Southern and Huanghuai regions, especially the Hubei, Jiangsu, Sichuan and Fujian provinces, had the most varied and broadest spectrum of resistance. Based on gene postulation, Rps1b, Rps1c, Rps4, Rps7 and novel resistance genes were identified in resistant accessions. Consequently, association mapping of resistance to each isolate was performed with 1,645 single nucleotide polymorphism (SNP) markers. A total of 14 marker-trait associations for Phytophthora resistance were identified. Among them, four were located in known PRR resistance loci intervals, five were located in other disease resistance quantitative trait locus (QTL) regions, and five associations unmasked novel loci for PRR resistance. In addition, we also identified candidate genes related to resistance. This is the first P. sojae resistance evaluation conducted using the Chinese soybean mini core collection, which is a representative sample of Chinese soybean cultivars. The resistance reaction analyses provided an excellent database of resistant resources and genetic variations for future breeding programs. The SNP markers associated with resistance will facilitate marker-assisted selection (MAS) in breeding programs for resistance to PRR, and the candidate genes may be useful for exploring the mechanism underlying P. sojae resistance.

NovelFam3000 – Uncharacterized human protein domains conserved across model organisms

PubMed Central

Kemmer, Danielle; Podowski, Raf M; Arenillas, David; Lim, Jonathan; Hodges, Emily; Roth, Peggy; Sonnhammer, Erik LL; Höög, Christer; Wasserman, Wyeth W

2006-01-01

Background Despite significant efforts from the research community, an extensive portion of the proteins encoded by human genes lack an assigned cellular function. Most metazoan proteins are composed of structural and/or functional domains, of which many appear in multiple proteins. Once a domain is characterized in one protein, the presence of a similar sequence in an uncharacterized protein serves as a basis for inference of function. Thus knowledge of a domain's function, or the protein within which it arises, can facilitate the analysis of an entire set of proteins. Description From the Pfam domain database, we extracted uncharacterized protein domains represented in proteins from humans, worms, and flies. A data centre was created to facilitate the analysis of the uncharacterized domain-containing proteins. The centre both provides researchers with links to dispersed internet resources containing gene-specific experimental data and enables them to post relevant experimental results or comments. For each human gene in the system, a characterization score is posted, allowing users to track the progress of characterization over time or to identify for study uncharacterized domains in well-characterized genes. As a test of the system, a subset of 39 domains was selected for analysis and the experimental results posted to the NovelFam3000 system. For 25 human protein members of these 39 domain families, detailed sub-cellular localizations were determined. Specific observations are presented based on the analysis of the integrated information provided through the online NovelFam3000 system. Conclusion Consistent experimental results between multiple members of a domain family allow for inferences of the domain's functional role. We unite bioinformatics resources and experimental data in order to accelerate the functional characterization of scarcely annotated domain families. PMID:16533400

The PathoYeastract database: an information system for the analysis of gene and genomic transcription regulation in pathogenic yeasts.

PubMed

Monteiro, Pedro Tiago; Pais, Pedro; Costa, Catarina; Manna, Sauvagya; Sá-Correia, Isabel; Teixeira, Miguel Cacho

2017-01-04

We present the PATHOgenic YEAst Search for Transcriptional Regulators And Consensus Tracking (PathoYeastract - http://pathoyeastract.org) database, a tool for the analysis and prediction of transcription regulatory associations at the gene and genomic levels in the pathogenic yeasts Candida albicans and C. glabrata Upon data retrieval from hundreds of publications, followed by curation, the database currently includes 28 000 unique documented regulatory associations between transcription factors (TF) and target genes and 107 DNA binding sites, considering 134 TFs in both species. Following the structure used for the YEASTRACT database, PathoYeastract makes available bioinformatics tools that enable the user to exploit the existing information to predict the TFs involved in the regulation of a gene or genome-wide transcriptional response, while ranking those TFs in order of their relative importance. Each search can be filtered based on the selection of specific environmental conditions, experimental evidence or positive/negative regulatory effect. Promoter analysis tools and interactive visualization tools for the representation of TF regulatory networks are also provided. The PathoYeastract database further provides simple tools for the prediction of gene and genomic regulation based on orthologous regulatory associations described for other yeast species, a comparative genomics setup for the study of cross-species evolution of regulatory networks. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

'RetinoGenetics': a comprehensive mutation database for genes related to inherited retinal degeneration.

PubMed

Ran, Xia; Cai, Wei-Jun; Huang, Xiu-Feng; Liu, Qi; Lu, Fan; Qu, Jia; Wu, Jinyu; Jin, Zi-Bing

2014-01-01

Inherited retinal degeneration (IRD), a leading cause of human blindness worldwide, is exceptionally heterogeneous with clinical heterogeneity and genetic variety. During the past decades, tremendous efforts have been made to explore the complex heterogeneity, and massive mutations have been identified in different genes underlying IRD with the significant advancement of sequencing technology. In this study, we developed a comprehensive database, 'RetinoGenetics', which contains informative knowledge about all known IRD-related genes and mutations for IRD. 'RetinoGenetics' currently contains 4270 mutations in 186 genes, with detailed information associated with 164 phenotypes from 934 publications and various types of functional annotations. Then extensive annotations were performed to each gene using various resources, including Gene Ontology, KEGG pathways, protein-protein interaction, mutational annotations and gene-disease network. Furthermore, by using the search functions, convenient browsing ways and intuitive graphical displays, 'RetinoGenetics' could serve as a valuable resource for unveiling the genetic basis of IRD. Taken together, 'RetinoGenetics' is an integrative, informative and updatable resource for IRD-related genetic predispositions. Database URL: http://www.retinogenetics.org/. © The Author(s) 2014. Published by Oxford University Press.

[Genome-wide identification and expression analysis of auxin-related gene families in grape].

PubMed

Yuan, Hua-zhao; Zhao, Mi-zhen; Wu, Wei-min; Yu, Hong-Mei; Qian, Ya-ming; Wang, Zhuang-wei; Wang, Xi-cheng

2015-07-01

The auxin response gene family adjusts the auxin balance and the growth hormone signaling pathways in plants. Using bioinformatics methods, the auxin-response genes from the grape genome database are identified and their chromosomal location, gene collinearity and phylogenetic analysis are performed. Probable genes include 25 AUX_IAA, 19 ARF, 9 GH3 and 42 LBD genes, which are unevenly distributed on all 19 chromosomes and some of them formed distinct tandem duplicate gene clusters. The available grape microarray databases show that all of the auxin-response genes are expressed in fruit and leaf buds, and significant overexpressed during fruit color-changing, bud break and bud dormancy periods. This paper provides a resource for functional studies of auxin-response genes in grape leaf and fruit development.

The androgen receptor gene mutations database.

PubMed

Patterson, M N; Hughes, I A; Gottlieb, B; Pinsky, L

1994-09-01

The androgen receptor gene mutations database is a comprehensive listing of mutations published in journals and meetings proceedings. The majority of mutations are point mutations identified in patients with androgen insensitivity syndrome. Information is included regarding the phenotype, the nature and location of the mutations, as well as the effects of the mutations on the androgen binding activity of the receptor. The current version of the database contains 149 entries, of which 114 are unique mutations. The database is available from EMBL (NetServ@EMBL-Heidelberg.DE) or as a Macintosh Filemaker file (mc33001@musica.mcgill.ca).

CicerTransDB 1.0: a resource for expression and functional study of chickpea transcription factors.

PubMed

Gayali, Saurabh; Acharya, Shankar; Lande, Nilesh Vikram; Pandey, Aarti; Chakraborty, Subhra; Chakraborty, Niranjan

2016-07-29

Transcription factor (TF) databases are major resource for systematic studies of TFs in specific species as well as related family members. Even though there are several publicly available multi-species databases, the information on the amount and diversity of TFs within individual species is fragmented, especially for newly sequenced genomes of non-model species of agricultural significance. We constructed CicerTransDB (Cicer Transcription Factor Database), the first database of its kind, which would provide a centralized putatively complete list of TFs in a food legume, chickpea. CicerTransDB, available at www.cicertransdb.esy.es , is based on chickpea (Cicer arietinum L.) annotation v 1.0. The database is an outcome of genome-wide domain study and manual classification of TF families. This database not only provides information of the gene, but also gene ontology, domain and motif architecture. CicerTransDB v 1.0 comprises information of 1124 genes of chickpea and enables the user to not only search, browse and download sequences but also retrieve sequence features. CicerTransDB also provides several single click interfaces, transconnecting to various other databases to ease further analysis. Several webAPI(s) integrated in the database allow end-users direct access of data. A critical comparison of CicerTransDB with PlantTFDB (Plant Transcription Factor Database) revealed 68 novel TFs in the chickpea genome, hitherto unexplored. Database URL: http://www.cicertransdb.esy.es.

UMD-USHbases: a comprehensive set of databases to record and analyse pathogenic mutations and unclassified variants in seven Usher syndrome causing genes.

PubMed

Baux, David; Faugère, Valérie; Larrieu, Lise; Le Guédard-Méreuze, Sandie; Hamroun, Dalil; Béroud, Christophe; Malcolm, Sue; Claustres, Mireille; Roux, Anne-Françoise

2008-08-01

Using the Universal Mutation Database (UMD) software, we have constructed "UMD-USHbases", a set of relational databases of nucleotide variations for seven genes involved in Usher syndrome (MYO7A, CDH23, PCDH15, USH1C, USH1G, USH3A and USH2A). Mutations in the Usher syndrome type I causing genes are also recorded in non-syndromic hearing loss cases and mutations in USH2A in non-syndromic retinitis pigmentosa. Usher syndrome provides a particular challenge for molecular diagnostics because of the clinical and molecular heterogeneity. As many mutations are missense changes, and all the genes also contain apparently non-pathogenic polymorphisms, well-curated databases are crucial for accurate interpretation of pathogenicity. Tools are provided to assess the pathogenicity of mutations, including conservation of amino acids and analysis of splice-sites. Reference amino acid alignments are provided. Apparently non-pathogenic variants in patients with Usher syndrome, at both the nucleotide and amino acid level, are included. The UMD-USHbases currently contain more than 2,830 entries including disease causing mutations, unclassified variants or non-pathogenic polymorphisms identified in over 938 patients. In addition to data collected from 89 publications, 15 novel mutations identified in our laboratory are recorded in MYO7A (6), CDH23 (8), or PCDH15 (1) genes. Information is given on the relative involvement of the seven genes, the number and distribution of variants in each gene. UMD-USHbases give access to a software package that provides specific routines and optimized multicriteria research and sorting tools. These databases should assist clinicians and geneticists seeking information about mutations responsible for Usher syndrome.

ClusterMine360: a database of microbial PKS/NRPS biosynthesis

PubMed Central

Conway, Kyle R.; Boddy, Christopher N.

2013-01-01

ClusterMine360 (http://www.clustermine360.ca/) is a database of microbial polyketide and non-ribosomal peptide gene clusters. It takes advantage of crowd-sourcing by allowing members of the community to make contributions while automation is used to help achieve high data consistency and quality. The database currently has >200 gene clusters from >185 compound families. It also features a unique sequence repository containing >10 000 polyketide synthase/non-ribosomal peptide synthetase domains. The sequences are filterable and downloadable as individual or multiple sequence FASTA files. We are confident that this database will be a useful resource for members of the polyketide synthases/non-ribosomal peptide synthetases research community, enabling them to keep up with the growing number of sequenced gene clusters and rapidly mine these clusters for functional information. PMID:23104377

Mycobacteriophage genome database.

PubMed

Joseph, Jerrine; Rajendran, Vasanthi; Hassan, Sameer; Kumar, Vanaja

2011-01-01

Mycobacteriophage genome database (MGDB) is an exclusive repository of the 64 completely sequenced mycobacteriophages with annotated information. It is a comprehensive compilation of the various gene parameters captured from several databases pooled together to empower mycobacteriophage researchers. The MGDB (Version No.1.0) comprises of 6086 genes from 64 mycobacteriophages classified into 72 families based on ACLAME database. Manual curation was aided by information available from public databases which was enriched further by analysis. Its web interface allows browsing as well as querying the classification. The main objective is to collect and organize the complexity inherent to mycobacteriophage protein classification in a rational way. The other objective is to browse the existing and new genomes and describe their functional annotation. The database is available for free at http://mpgdb.ibioinformatics.org/mpgdb.php.

Tcof1-Related Molecular Networks in Treacher Collins Syndrome.

PubMed

Dai, Jiewen; Si, Jiawen; Wang, Minjiao; Huang, Li; Fang, Bing; Shi, Jun; Wang, Xudong; Shen, Guofang

2016-09-01

Treacher Collins syndrome (TCS) is a rare, autosomal-dominant disorder characterized by craniofacial deformities, and is primarily caused by mutations in the Tcof1 gene. This article was aimed to perform a comprehensive literature review and systematic bioinformatic analysis of Tcof1-related molecular networks in TCS. First, the up- and down-regulated genes in Tcof1 heterozygous haploinsufficient mutant mice embryos and Tcof1 knockdown and Tcof1 over-expressed neuroblastoma N1E-115 cells were obtained from the Gene Expression Omnibus database. The GeneDecks database was used to calculate the 500 genes most closely related to Tcof1. Then, the relationships between 4 gene sets (a predicted set and sets comparing the wildtype with the 3 Gene Expression Omnibus datasets) were analyzed using the DAVID, GeneMANIA and STRING databases. The analysis results showed that the Tcof1-related genes were enriched in various biological processes, including cell proliferation, apoptosis, cell cycle, differentiation, and migration. They were also enriched in several signaling pathways, such as the ribosome, p53, cell cycle, and WNT signaling pathways. Additionally, these genes clearly had direct or indirect interactions with Tcof1 and between each other. Literature review and bioinformatic analysis finds imply that special attention should be given to these pathways, as they may offer target points for TCS therapies.

dbCPG: A web resource for cancer predisposition genes

PubMed Central

Wei, Ran; Yao, Yao; Yang, Wu; Zheng, Chun-Hou; Zhao, Min; Xia, Junfeng

2016-01-01

Cancer predisposition genes (CPGs) are genes in which inherited mutations confer highly or moderately increased risks of developing cancer. Identification of these genes and understanding the biological mechanisms that underlie them is crucial for the prevention, early diagnosis, and optimized management of cancer. Over the past decades, great efforts have been made to identify CPGs through multiple strategies. However, information on these CPGs and their molecular functions is scattered. To address this issue and provide a comprehensive resource for researchers, we developed the Cancer Predisposition Gene Database (dbCPG, Database URL: http://bioinfo.ahu.edu.cn:8080/dbCPG/index.jsp), the first literature-based gene resource for exploring human CPGs. It contains 827 human (724 protein-coding, 23 non-coding, and 80 unknown type genes), 637 rats, and 658 mouse CPGs. Furthermore, data mining was performed to gain insights into the understanding of the CPGs data, including functional annotation, gene prioritization, network analysis of prioritized genes and overlap analysis across multiple cancer types. A user-friendly web interface with multiple browse, search, and upload functions was also developed to facilitate access to the latest information on CPGs. Taken together, the dbCPG database provides a comprehensive data resource for further studies of cancer predisposition genes. PMID:27192119

Arabidopsis Hormone Database: a comprehensive genetic and phenotypic information database for plant hormone research in Arabidopsis

PubMed Central

Peng, Zhi-yu; Zhou, Xin; Li, Linchuan; Yu, Xiangchun; Li, Hongjiang; Jiang, Zhiqiang; Cao, Guangyu; Bai, Mingyi; Wang, Xingchun; Jiang, Caifu; Lu, Haibin; Hou, Xianhui; Qu, Lijia; Wang, Zhiyong; Zuo, Jianru; Fu, Xiangdong; Su, Zhen; Li, Songgang; Guo, Hongwei

2009-01-01

Plant hormones are small organic molecules that influence almost every aspect of plant growth and development. Genetic and molecular studies have revealed a large number of genes that are involved in responses to numerous plant hormones, including auxin, gibberellin, cytokinin, abscisic acid, ethylene, jasmonic acid, salicylic acid, and brassinosteroid. Here, we develop an Arabidopsis hormone database, which aims to provide a systematic and comprehensive view of genes participating in plant hormonal regulation, as well as morphological phenotypes controlled by plant hormones. Based on data from mutant studies, transgenic analysis and gene ontology (GO) annotation, we have identified a total of 1026 genes in the Arabidopsis genome that participate in plant hormone functions. Meanwhile, a phenotype ontology is developed to precisely describe myriad hormone-regulated morphological processes with standardized vocabularies. A web interface (http://ahd.cbi.pku.edu.cn) would allow users to quickly get access to information about these hormone-related genes, including sequences, functional category, mutant information, phenotypic description, microarray data and linked publications. Several applications of this database in studying plant hormonal regulation and hormone cross-talk will be presented and discussed. PMID:19015126

Arabidopsis Hormone Database: a comprehensive genetic and phenotypic information database for plant hormone research in Arabidopsis.

PubMed

Peng, Zhi-yu; Zhou, Xin; Li, Linchuan; Yu, Xiangchun; Li, Hongjiang; Jiang, Zhiqiang; Cao, Guangyu; Bai, Mingyi; Wang, Xingchun; Jiang, Caifu; Lu, Haibin; Hou, Xianhui; Qu, Lijia; Wang, Zhiyong; Zuo, Jianru; Fu, Xiangdong; Su, Zhen; Li, Songgang; Guo, Hongwei

2009-01-01

Plant hormones are small organic molecules that influence almost every aspect of plant growth and development. Genetic and molecular studies have revealed a large number of genes that are involved in responses to numerous plant hormones, including auxin, gibberellin, cytokinin, abscisic acid, ethylene, jasmonic acid, salicylic acid, and brassinosteroid. Here, we develop an Arabidopsis hormone database, which aims to provide a systematic and comprehensive view of genes participating in plant hormonal regulation, as well as morphological phenotypes controlled by plant hormones. Based on data from mutant studies, transgenic analysis and gene ontology (GO) annotation, we have identified a total of 1026 genes in the Arabidopsis genome that participate in plant hormone functions. Meanwhile, a phenotype ontology is developed to precisely describe myriad hormone-regulated morphological processes with standardized vocabularies. A web interface (http://ahd.cbi.pku.edu.cn) would allow users to quickly get access to information about these hormone-related genes, including sequences, functional category, mutant information, phenotypic description, microarray data and linked publications. Several applications of this database in studying plant hormonal regulation and hormone cross-talk will be presented and discussed.

CellLineNavigator: a workbench for cancer cell line analysis

PubMed Central

Krupp, Markus; Itzel, Timo; Maass, Thorsten; Hildebrandt, Andreas; Galle, Peter R.; Teufel, Andreas

2013-01-01

The CellLineNavigator database, freely available at http://www.medicalgenomics.org/celllinenavigator, is a web-based workbench for large scale comparisons of a large collection of diverse cell lines. It aims to support experimental design in the fields of genomics, systems biology and translational biomedical research. Currently, this compendium holds genome wide expression profiles of 317 different cancer cell lines, categorized into 57 different pathological states and 28 individual tissues. To enlarge the scope of CellLineNavigator, the database was furthermore closely linked to commonly used bioinformatics databases and knowledge repositories. To ensure easy data access and search ability, a simple data and an intuitive querying interface were implemented. It allows the user to explore and filter gene expression, focusing on pathological or physiological conditions. For a more complex search, the advanced query interface may be used to query for (i) differentially expressed genes; (ii) pathological or physiological conditions; or (iii) gene names or functional attributes, such as Kyoto Encyclopaedia of Genes and Genomes pathway maps. These queries may also be combined. Finally, CellLineNavigator allows additional advanced analysis of differentially regulated genes by a direct link to the Database for Annotation, Visualization and Integrated Discovery (DAVID) Bioinformatics Resources. PMID:23118487

CyanoBase: the cyanobacteria genome database update 2010.

PubMed

Nakao, Mitsuteru; Okamoto, Shinobu; Kohara, Mitsuyo; Fujishiro, Tsunakazu; Fujisawa, Takatomo; Sato, Shusei; Tabata, Satoshi; Kaneko, Takakazu; Nakamura, Yasukazu

2010-01-01

CyanoBase (http://genome.kazusa.or.jp/cyanobase) is the genome database for cyanobacteria, which are model organisms for photosynthesis. The database houses cyanobacteria species information, complete genome sequences, genome-scale experiment data, gene information, gene annotations and mutant information. In this version, we updated these datasets and improved the navigation and the visual display of the data views. In addition, a web service API now enables users to retrieve the data in various formats with other tools, seamlessly.

The UMD-p53 database: new mutations and analysis tools.

PubMed

Béroud, Christophe; Soussi, Thierry

2003-03-01

The tumor suppressor gene TP53 (p53) is the most extensively studied gene involved in human cancers. More than 1,400 publications have reported mutations of this gene in 150 cancer types for a total of 14,971 mutations. To exploit this huge bulk of data, specific analytic tools were highly warranted. We therefore developed a locus-specific database software called UMD-p53. This database compiles all somatic and germline mutations as well as polymorphisms of the TP53 gene which have been reported in the published literature since 1989, or unpublished data submitted to the database curators. The database is available at www.umd.necker.fr or at http://p53.curie.fr/. In this paper, we describe recent developments of the UMD-p53 database. These developments include new fields and routines. For example, the analysis of putative acceptor or donor splice sites is now automated and gives new insight for the causal role of "silent mutations." Other routines have also been created such as the prescreening module, the UV module, and the cancer distribution module. These new improvements will help users not only for molecular epidemiology and pharmacogenetic studies but also for patient-based studies. To achieve theses purposes we have designed a procedure to check and validate data in order to reach the highest quality data. Copyright 2003 Wiley-Liss, Inc.

GEM-TREND: a web tool for gene expression data mining toward relevant network discovery

PubMed Central

Feng, Chunlai; Araki, Michihiro; Kunimoto, Ryo; Tamon, Akiko; Makiguchi, Hiroki; Niijima, Satoshi; Tsujimoto, Gozoh; Okuno, Yasushi

2009-01-01

Background DNA microarray technology provides us with a first step toward the goal of uncovering gene functions on a genomic scale. In recent years, vast amounts of gene expression data have been collected, much of which are available in public databases, such as the Gene Expression Omnibus (GEO). To date, most researchers have been manually retrieving data from databases through web browsers using accession numbers (IDs) or keywords, but gene-expression patterns are not considered when retrieving such data. The Connectivity Map was recently introduced to compare gene expression data by introducing gene-expression signatures (represented by a set of genes with up- or down-regulated labels according to their biological states) and is available as a web tool for detecting similar gene-expression signatures from a limited data set (approximately 7,000 expression profiles representing 1,309 compounds). In order to support researchers to utilize the public gene expression data more effectively, we developed a web tool for finding similar gene expression data and generating its co-expression networks from a publicly available database. Results GEM-TREND, a web tool for searching gene expression data, allows users to search data from GEO using gene-expression signatures or gene expression ratio data as a query and retrieve gene expression data by comparing gene-expression pattern between the query and GEO gene expression data. The comparison methods are based on the nonparametric, rank-based pattern matching approach of Lamb et al. (Science 2006) with the additional calculation of statistical significance. The web tool was tested using gene expression ratio data randomly extracted from the GEO and with in-house microarray data, respectively. The results validated the ability of GEM-TREND to retrieve gene expression entries biologically related to a query from GEO. For further analysis, a network visualization interface is also provided, whereby genes and gene annotations are dynamically linked to external data repositories. Conclusion GEM-TREND was developed to retrieve gene expression data by comparing query gene-expression pattern with those of GEO gene expression data. It could be a very useful resource for finding similar gene expression profiles and constructing its gene co-expression networks from a publicly available database. GEM-TREND was designed to be user-friendly and is expected to support knowledge discovery. GEM-TREND is freely available at . PMID:19728865

GEM-TREND: a web tool for gene expression data mining toward relevant network discovery.

PubMed

Feng, Chunlai; Araki, Michihiro; Kunimoto, Ryo; Tamon, Akiko; Makiguchi, Hiroki; Niijima, Satoshi; Tsujimoto, Gozoh; Okuno, Yasushi

2009-09-03

DNA microarray technology provides us with a first step toward the goal of uncovering gene functions on a genomic scale. In recent years, vast amounts of gene expression data have been collected, much of which are available in public databases, such as the Gene Expression Omnibus (GEO). To date, most researchers have been manually retrieving data from databases through web browsers using accession numbers (IDs) or keywords, but gene-expression patterns are not considered when retrieving such data. The Connectivity Map was recently introduced to compare gene expression data by introducing gene-expression signatures (represented by a set of genes with up- or down-regulated labels according to their biological states) and is available as a web tool for detecting similar gene-expression signatures from a limited data set (approximately 7,000 expression profiles representing 1,309 compounds). In order to support researchers to utilize the public gene expression data more effectively, we developed a web tool for finding similar gene expression data and generating its co-expression networks from a publicly available database. GEM-TREND, a web tool for searching gene expression data, allows users to search data from GEO using gene-expression signatures or gene expression ratio data as a query and retrieve gene expression data by comparing gene-expression pattern between the query and GEO gene expression data. The comparison methods are based on the nonparametric, rank-based pattern matching approach of Lamb et al. (Science 2006) with the additional calculation of statistical significance. The web tool was tested using gene expression ratio data randomly extracted from the GEO and with in-house microarray data, respectively. The results validated the ability of GEM-TREND to retrieve gene expression entries biologically related to a query from GEO. For further analysis, a network visualization interface is also provided, whereby genes and gene annotations are dynamically linked to external data repositories. GEM-TREND was developed to retrieve gene expression data by comparing query gene-expression pattern with those of GEO gene expression data. It could be a very useful resource for finding similar gene expression profiles and constructing its gene co-expression networks from a publicly available database. GEM-TREND was designed to be user-friendly and is expected to support knowledge discovery. GEM-TREND is freely available at http://cgs.pharm.kyoto-u.ac.jp/services/network.

Recognition of chimeric small-subunit ribosomal DNAs composed of genes from uncultivated microorganisms

NASA Technical Reports Server (NTRS)

Kopczynski, E. D.; Bateson, M. M.; Ward, D. M.

1994-01-01

When PCR was used to recover small-subunit (SSU) rRNA genes from a hot spring cyanobacterial mat community, chimeric SSU rRNA sequences which exhibited little or no secondary structural abnormality were recovered. They were revealed as chimeras of SSU rRNA genes of uncultivated species through separate phylogenetic analysis of short sequence domains.

1-CMDb: A Curated Database of Genomic Variations of the One-Carbon Metabolism Pathway.

PubMed

Bhat, Manoj K; Gadekar, Veerendra P; Jain, Aditya; Paul, Bobby; Rai, Padmalatha S; Satyamoorthy, Kapaettu

2017-01-01

The one-carbon metabolism pathway is vital in maintaining tissue homeostasis by driving the critical reactions of folate and methionine cycles. A myriad of genetic and epigenetic events mark the rate of reactions in a tissue-specific manner. Integration of these to predict and provide personalized health management requires robust computational tools that can process multiomics data. The DNA sequences that may determine the chain of biological events and the endpoint reactions within one-carbon metabolism genes remain to be comprehensively recorded. Hence, we designed the one-carbon metabolism database (1-CMDb) as a platform to interrogate its association with a host of human disorders. DNA sequence and network information of a total of 48 genes were extracted from a literature survey and KEGG pathway that are involved in the one-carbon folate-mediated pathway. The information generated, collected, and compiled for all these genes from the UCSC genome browser included the single nucleotide polymorphisms (SNPs), CpGs, copy number variations (CNVs), and miRNAs, and a comprehensive database was created. Furthermore, a significant correlation analysis was performed for SNPs in the pathway genes. Detailed data of SNPs, CNVs, CpG islands, and miRNAs for 48 folate pathway genes were compiled. The SNPs in CNVs (9670), CpGs (984), and miRNAs (14) were also compiled for all pathway genes. The SIFT score, the prediction and PolyPhen score, as well as the prediction for each of the SNPs were tabulated and represented for folate pathway genes. Also included in the database for folate pathway genes were the links to 124 various phenotypes and disease associations as reported in the literature and from publicly available information. A comprehensive database was generated consisting of genomic elements within and among SNPs, CNVs, CpGs, and miRNAs of one-carbon metabolism pathways to facilitate (a) single source of information and (b) integration into large-genome scale network analysis to be developed in the future by the scientific community. The database can be accessed at http://slsdb.manipal.edu/ocm/. © 2017 S. Karger AG, Basel.

PTGBase: an integrated database to study tandem duplicated genes in plants.

PubMed

Yu, Jingyin; Ke, Tao; Tehrim, Sadia; Sun, Fengming; Liao, Boshou; Hua, Wei

2015-01-01

Tandem duplication is a wide-spread phenomenon in plant genomes and plays significant roles in evolution and adaptation to changing environments. Tandem duplicated genes related to certain functions will lead to the expansion of gene families and bring increase of gene dosage in the form of gene cluster arrays. Many tandem duplication events have been studied in plant genomes; yet, there is a surprising shortage of efforts to systematically present the integration of large amounts of information about publicly deposited tandem duplicated gene data across the plant kingdom. To address this shortcoming, we developed the first plant tandem duplicated genes database, PTGBase. It delivers the most comprehensive resource available to date, spanning 39 plant genomes, including model species and newly sequenced species alike. Across these genomes, 54 130 tandem duplicated gene clusters (129 652 genes) are presented in the database. Each tandem array, as well as its member genes, is characterized in complete detail. Tandem duplicated genes in PTGBase can be explored through browsing or searching by identifiers or keywords of functional annotation and sequence similarity. Users can download tandem duplicated gene arrays easily to any scale, up to the complete annotation data set for an entire plant genome. PTGBase will be updated regularly with newly sequenced plant species as they become available. © The Author(s) 2015. Published by Oxford University Press.

Genome-wide identification and evolution of the PIN-FORMED (PIN) gene family in Glycine max.

PubMed

Liu, Yuan; Wei, Haichao

2017-07-01

Soybean (Glycine max) is one of the most important crop plants. Wild and cultivated soybean varieties have significant differences worth further investigation, such as plant morphology, seed size, and seed coat development; these characters may be related to auxin biology. The PIN gene family encodes essential transport proteins in cell-to-cell auxin transport, but little research on soybean PIN genes (GmPIN genes) has been done, especially with respect to the evolution and differences between wild and cultivated soybean. In this study, we retrieved 23 GmPIN genes from the latest updated G. max genome database; six GmPIN protein sequences were changed compared with the previous database. Based on the Plant Genome Duplication Database, 18 GmPIN genes have been involved in segment duplication. Three pairs of GmPIN genes arose after the second soybean genome duplication, and six occurred after the first genome duplication. The duplicated GmPIN genes retained similar expression patterns. All the duplicated GmPIN genes experienced purifying selection (K a /K s < 1) to prevent accumulation of non-synonymous mutations and thus remained more similar. In addition, we also focused on the artificial selection of the soybean PIN genes. Five artificially selected GmPIN genes were identified by comparing the genome sequence of 17 wild and 14 cultivated soybean varieties. Our research provides useful and comprehensive basic information for understanding GmPIN genes.

GeneSCF: a real-time based functional enrichment tool with support for multiple organisms.

PubMed

Subhash, Santhilal; Kanduri, Chandrasekhar

2016-09-13

High-throughput technologies such as ChIP-sequencing, RNA-sequencing, DNA sequencing and quantitative metabolomics generate a huge volume of data. Researchers often rely on functional enrichment tools to interpret the biological significance of the affected genes from these high-throughput studies. However, currently available functional enrichment tools need to be updated frequently to adapt to new entries from the functional database repositories. Hence there is a need for a simplified tool that can perform functional enrichment analysis by using updated information directly from the source databases such as KEGG, Reactome or Gene Ontology etc. In this study, we focused on designing a command-line tool called GeneSCF (Gene Set Clustering based on Functional annotations), that can predict the functionally relevant biological information for a set of genes in a real-time updated manner. It is designed to handle information from more than 4000 organisms from freely available prominent functional databases like KEGG, Reactome and Gene Ontology. We successfully employed our tool on two of published datasets to predict the biologically relevant functional information. The core features of this tool were tested on Linux machines without the need for installation of more dependencies. GeneSCF is more reliable compared to other enrichment tools because of its ability to use reference functional databases in real-time to perform enrichment analysis. It is an easy-to-integrate tool with other pipelines available for downstream analysis of high-throughput data. More importantly, GeneSCF can run multiple gene lists simultaneously on different organisms thereby saving time for the users. Since the tool is designed to be ready-to-use, there is no need for any complex compilation and installation procedures.

Regulators of Androgen Action Resource: a one-stop shop for the comprehensive study of androgen receptor action.

PubMed

DePriest, Adam D; Fiandalo, Michael V; Schlanger, Simon; Heemers, Frederike; Mohler, James L; Liu, Song; Heemers, Hannelore V

2016-01-01

Androgen receptor (AR) is a ligand-activated transcription factor that is the main target for treatment of non-organ-confined prostate cancer (CaP). Failure of life-prolonging AR-targeting androgen deprivation therapy is due to flexibility in steroidogenic pathways that control intracrine androgen levels and variability in the AR transcriptional output. Androgen biosynthesis enzymes, androgen transporters and AR-associated coregulators are attractive novel CaP treatment targets. These proteins, however, are characterized by multiple transcript variants and isoforms, are subject to genomic alterations, and are differentially expressed among CaPs. Determining their therapeutic potential requires evaluation of extensive, diverse datasets that are dispersed over multiple databases, websites and literature reports. Mining and integrating these datasets are cumbersome, time-consuming tasks and provide only snapshots of relevant information. To overcome this impediment to effective, efficient study of AR and potential drug targets, we developed the Regulators of Androgen Action Resource (RAAR), a non-redundant, curated and user-friendly searchable web interface. RAAR centralizes information on gene function, clinical relevance, and resources for 55 genes that encode proteins involved in biosynthesis, metabolism and transport of androgens and for 274 AR-associated coregulator genes. Data in RAAR are organized in two levels: (i) Information pertaining to production of androgens is contained in a 'pre-receptor level' database, and coregulator gene information is provided in a 'post-receptor level' database, and (ii) an 'other resources' database contains links to additional databases that are complementary to and useful to pursue further the information provided in RAAR. For each of its 329 entries, RAAR provides access to more than 20 well-curated publicly available databases, and thus, access to thousands of data points. Hyperlinks provide direct access to gene-specific entries in the respective database(s). RAAR is a novel, freely available resource that provides fast, reliable and easy access to integrated information that is needed to develop alternative CaP therapies. Database URL: http://www.lerner.ccf.org/cancerbio/heemers/RAAR/search/. © The Author(s) 2016. Published by Oxford University Press.

VTCdb: a gene co-expression database for the crop species Vitis vinifera (grapevine).

PubMed

Wong, Darren C J; Sweetman, Crystal; Drew, Damian P; Ford, Christopher M

2013-12-16

Gene expression datasets in model plants such as Arabidopsis have contributed to our understanding of gene function and how a single underlying biological process can be governed by a diverse network of genes. The accumulation of publicly available microarray data encompassing a wide range of biological and environmental conditions has enabled the development of additional capabilities including gene co-expression analysis (GCA). GCA is based on the understanding that genes encoding proteins involved in similar and/or related biological processes may exhibit comparable expression patterns over a range of experimental conditions, developmental stages and tissues. We present an open access database for the investigation of gene co-expression networks within the cultivated grapevine, Vitis vinifera. The new gene co-expression database, VTCdb (http://vtcdb.adelaide.edu.au/Home.aspx), offers an online platform for transcriptional regulatory inference in the cultivated grapevine. Using condition-independent and condition-dependent approaches, grapevine co-expression networks were constructed using the latest publicly available microarray datasets from diverse experimental series, utilising the Affymetrix Vitis vinifera GeneChip (16 K) and the NimbleGen Grape Whole-genome microarray chip (29 K), thus making it possible to profile approximately 29,000 genes (95% of the predicted grapevine transcriptome). Applications available with the online platform include the use of gene names, probesets, modules or biological processes to query the co-expression networks, with the option to choose between Affymetrix or Nimblegen datasets and between multiple co-expression measures. Alternatively, the user can browse existing network modules using interactive network visualisation and analysis via CytoscapeWeb. To demonstrate the utility of the database, we present examples from three fundamental biological processes (berry development, photosynthesis and flavonoid biosynthesis) whereby the recovered sub-networks reconfirm established plant gene functions and also identify novel associations. Together, we present valuable insights into grapevine transcriptional regulation by developing network models applicable to researchers in their prioritisation of gene candidates, for on-going study of biological processes related to grapevine development, metabolism and stress responses.

PvTFDB: a Phaseolus vulgaris transcription factors database for expediting functional genomics in legumes.

PubMed

Bhawna; Bonthala, V S; Gajula, Mnv Prasad

2016-01-01

The common bean [Phaseolus vulgaris (L.)] is one of the essential proteinaceous vegetables grown in developing countries. However, its production is challenged by low yields caused by numerous biotic and abiotic stress conditions. Regulatory transcription factors (TFs) symbolize a key component of the genome and are the most significant targets for producing stress tolerant crop and hence functional genomic studies of these TFs are important. Therefore, here we have constructed a web-accessible TFs database for P. vulgaris, called PvTFDB, which contains 2370 putative TF gene models in 49 TF families. This database provides a comprehensive information for each of the identified TF that includes sequence data, functional annotation, SSRs with their primer sets, protein physical properties, chromosomal location, phylogeny, tissue-specific gene expression data, orthologues, cis-regulatory elements and gene ontology (GO) assignment. Altogether, this information would be used in expediting the functional genomic studies of a specific TF(s) of interest. The objectives of this database are to understand functional genomics study of common bean TFs and recognize the regulatory mechanisms underlying various stress responses to ease breeding strategy for variety production through a couple of search interfaces including gene ID, functional annotation and browsing interfaces including by family and by chromosome. This database will also serve as a promising central repository for researchers as well as breeders who are working towards crop improvement of legume crops. In addition, this database provide the user unrestricted public access and the user can download entire data present in the database freely.Database URL: http://www.multiomics.in/PvTFDB/. © The Author(s) 2016. Published by Oxford University Press.

Distribution and linkage disequilibrium analysis of polymorphisms of GH1 gene in different populations of pigs associated with body size.

PubMed

Cheng, Yunyun; Liu, Songcai; Su, Dan; Lu, Chao; Zhang, Xin; Wu, Qingyan; Li, Siming; Fu, Haoyu; Yu, Hao; Hao, Linlin

2016-03-01

Growth hormone (GH) has been considered as a candidate gene for growth and body size in pigs. In this study, polymorphisms of the GH1 gene were evaluated for associations with body size traits in 190 pig individuals. Seventeen single-nucleotide polymorphisms (SNPs) were identified in GH1 gene of the large pig breeds and miniature pig breeds using direct sequencing and genotyped by allele-specific PCR approach. Notably, six (g.237A>G, g.283T>C, g.309A>G, g.318A>G, g.540A>G and g.544A>G) of them were significantly associated with body size, of which three loci (g.283T>C, g.309A>G, g.318A>G) located in the signal-peptide coding region of GH1 gene compose a CGG haplotype for large pigs and TAA haplotype for miniature pigs (P <0.001), two loci (g.540A>G and g.544A>G) located in the second intron of GH1 gene compose a GG haplotype for large pigs and AA haplotype for miniature pigs (P < 0.001). Our results demonstrate that these SNPs in GH1 gene are associated with the body size of pigs providing genetic basis for pig breeding with the improved economic benefits.

Viral Genome DataBase: storing and analyzing genes and proteins from complete viral genomes.

PubMed

Hiscock, D; Upton, C

2000-05-01

The Viral Genome DataBase (VGDB) contains detailed information of the genes and predicted protein sequences from 15 completely sequenced genomes of large (&100 kb) viruses (2847 genes). The data that is stored includes DNA sequence, protein sequence, GenBank and user-entered notes, molecular weight (MW), isoelectric point (pI), amino acid content, A + T%, nucleotide frequency, dinucleotide frequency and codon use. The VGDB is a mySQL database with a user-friendly JAVA GUI. Results of queries can be easily sorted by any of the individual parameters. The software and additional figures and information are available at http://athena.bioc.uvic.ca/genomes/index.html .

The Effect of Different Materials on the Accuracy of the HYDRA Optical-Fiber-Coupled Coherent Range/Pressure Measurement System and the Development of the Health Care Database System at Old Dominion University

NASA Technical Reports Server (NTRS)

Johnson, Kimberly D.

1995-01-01

The objective of the first project involving the HYDRA laser system was to determine what effects, if any, could been seen in the system's measurements when testing was done with objects composed of different materials. Ideally we would like to have seen that the range of measurements were all within the accepted 0.4 millimeter accuracy of the system. Unfortunately our results were not as we had hoped, and there did appear to be some significant difference in the measurements made on objects composed of different materials. The second project is a continuing project at Old Dominion University. The ultimate goal is to develop a medical database that allows a doctor or hospital to keep medical records on line. The current data of the system consisted of one patient whose medical data had been hard coded to allow for a demonstration of the potentials of the system. The short term goal for this summer was to add additional patients to the system for testing, and to eliminate the hard coding of data by creating a database where data could be stored and queried to produce the results seen in the current state.

PAGER 2.0: an update to the pathway, annotated-list and gene-signature electronic repository for Human Network Biology

PubMed Central

Yue, Zongliang; Zheng, Qi; Neylon, Michael T; Yoo, Minjae; Shin, Jimin; Zhao, Zhiying; Tan, Aik Choon

2018-01-01

Abstract Integrative Gene-set, Network and Pathway Analysis (GNPA) is a powerful data analysis approach developed to help interpret high-throughput omics data. In PAGER 1.0, we demonstrated that researchers can gain unbiased and reproducible biological insights with the introduction of PAGs (Pathways, Annotated-lists and Gene-signatures) as the basic data representation elements. In PAGER 2.0, we improve the utility of integrative GNPA by significantly expanding the coverage of PAGs and PAG-to-PAG relationships in the database, defining a new metric to quantify PAG data qualities, and developing new software features to simplify online integrative GNPA. Specifically, we included 84 282 PAGs spanning 24 different data sources that cover human diseases, published gene-expression signatures, drug–gene, miRNA–gene interactions, pathways and tissue-specific gene expressions. We introduced a new normalized Cohesion Coefficient (nCoCo) score to assess the biological relevance of genes inside a PAG, and RP-score to rank genes and assign gene-specific weights inside a PAG. The companion web interface contains numerous features to help users query and navigate the database content. The database content can be freely downloaded and is compatible with third-party Gene Set Enrichment Analysis tools. We expect PAGER 2.0 to become a major resource in integrative GNPA. PAGER 2.0 is available at http://discovery.informatics.uab.edu/PAGER/. PMID:29126216

neXtA5: accelerating annotation of articles via automated approaches in neXtProt.

PubMed

Mottin, Luc; Gobeill, Julien; Pasche, Emilie; Michel, Pierre-André; Cusin, Isabelle; Gaudet, Pascale; Ruch, Patrick

2016-01-01

The rapid increase in the number of published articles poses a challenge for curated databases to remain up-to-date. To help the scientific community and database curators deal with this issue, we have developed an application, neXtA5, which prioritizes the literature for specific curation requirements. Our system, neXtA5, is a curation service composed of three main elements. The first component is a named-entity recognition module, which annotates MEDLINE over some predefined axes. This report focuses on three axes: Diseases, the Molecular Function and Biological Process sub-ontologies of the Gene Ontology (GO). The automatic annotations are then stored in a local database, BioMed, for each annotation axis. Additional entities such as species and chemical compounds are also identified. The second component is an existing search engine, which retrieves the most relevant MEDLINE records for any given query. The third component uses the content of BioMed to generate an axis-specific ranking, which takes into account the density of named-entities as stored in the Biomed database. The two ranked lists are ultimately merged using a linear combination, which has been specifically tuned to support the annotation of each axis. The fine-tuning of the coefficients is formally reported for each axis-driven search. Compared with PubMed, which is the system used by most curators, the improvement is the following: +231% for Diseases, +236% for Molecular Functions and +3153% for Biological Process when measuring the precision of the top-returned PMID (P0 or mean reciprocal rank). The current search methods significantly improve the search effectiveness of curators for three important curation axes. Further experiments are being performed to extend the curation types, in particular protein-protein interactions, which require specific relationship extraction capabilities. In parallel, user-friendly interfaces powered with a set of JSON web services are currently being implemented into the neXtProt annotation pipeline.Available on: http://babar.unige.ch:8082/neXtA5Database URL: http://babar.unige.ch:8082/neXtA5/fetcher.jsp. © The Author(s) 2016. Published by Oxford University Press.

neXtA5: accelerating annotation of articles via automated approaches in neXtProt

PubMed Central

Mottin, Luc; Gobeill, Julien; Pasche, Emilie; Michel, Pierre-André; Cusin, Isabelle; Gaudet, Pascale; Ruch, Patrick

2016-01-01

The rapid increase in the number of published articles poses a challenge for curated databases to remain up-to-date. To help the scientific community and database curators deal with this issue, we have developed an application, neXtA5, which prioritizes the literature for specific curation requirements. Our system, neXtA5, is a curation service composed of three main elements. The first component is a named-entity recognition module, which annotates MEDLINE over some predefined axes. This report focuses on three axes: Diseases, the Molecular Function and Biological Process sub-ontologies of the Gene Ontology (GO). The automatic annotations are then stored in a local database, BioMed, for each annotation axis. Additional entities such as species and chemical compounds are also identified. The second component is an existing search engine, which retrieves the most relevant MEDLINE records for any given query. The third component uses the content of BioMed to generate an axis-specific ranking, which takes into account the density of named-entities as stored in the Biomed database. The two ranked lists are ultimately merged using a linear combination, which has been specifically tuned to support the annotation of each axis. The fine-tuning of the coefficients is formally reported for each axis-driven search. Compared with PubMed, which is the system used by most curators, the improvement is the following: +231% for Diseases, +236% for Molecular Functions and +3153% for Biological Process when measuring the precision of the top-returned PMID (P0 or mean reciprocal rank). The current search methods significantly improve the search effectiveness of curators for three important curation axes. Further experiments are being performed to extend the curation types, in particular protein–protein interactions, which require specific relationship extraction capabilities. In parallel, user-friendly interfaces powered with a set of JSON web services are currently being implemented into the neXtProt annotation pipeline. Available on: http://babar.unige.ch:8082/neXtA5 Database URL: http://babar.unige.ch:8082/neXtA5/fetcher.jsp PMID:27374119

iMETHYL: an integrative database of human DNA methylation, gene expression, and genomic variation.

PubMed

Komaki, Shohei; Shiwa, Yuh; Furukawa, Ryohei; Hachiya, Tsuyoshi; Ohmomo, Hideki; Otomo, Ryo; Satoh, Mamoru; Hitomi, Jiro; Sobue, Kenji; Sasaki, Makoto; Shimizu, Atsushi

2018-01-01

We launched an integrative multi-omics database, iMETHYL (http://imethyl.iwate-megabank.org). iMETHYL provides whole-DNA methylation (~24 million autosomal CpG sites), whole-genome (~9 million single-nucleotide variants), and whole-transcriptome (>14 000 genes) data for CD4 + T-lymphocytes, monocytes, and neutrophils collected from approximately 100 subjects. These data were obtained from whole-genome bisulfite sequencing, whole-genome sequencing, and whole-transcriptome sequencing, making iMETHYL a comprehensive database.

A 5.8S nuclear ribosomal RNA gene sequence database: applications to ecology and evolution

NASA Technical Reports Server (NTRS)

Cullings, K. W.; Vogler, D. R.

1998-01-01

We complied a 5.8S nuclear ribosomal gene sequence database for animals, plants, and fungi using both newly generated and GenBank sequences. We demonstrate the utility of this database as an internal check to determine whether the target organism and not a contaminant has been sequenced, as a diagnostic tool for ecologists and evolutionary biologists to determine the placement of asexual fungi within larger taxonomic groups, and as a tool to help identify fungi that form ectomycorrhizae.

CyanoBase: the cyanobacteria genome database update 2010

PubMed Central

Nakao, Mitsuteru; Okamoto, Shinobu; Kohara, Mitsuyo; Fujishiro, Tsunakazu; Fujisawa, Takatomo; Sato, Shusei; Tabata, Satoshi; Kaneko, Takakazu; Nakamura, Yasukazu

2010-01-01

CyanoBase (http://genome.kazusa.or.jp/cyanobase) is the genome database for cyanobacteria, which are model organisms for photosynthesis. The database houses cyanobacteria species information, complete genome sequences, genome-scale experiment data, gene information, gene annotations and mutant information. In this version, we updated these datasets and improved the navigation and the visual display of the data views. In addition, a web service API now enables users to retrieve the data in various formats with other tools, seamlessly. PMID:19880388

The androgen receptor gene mutations database.

PubMed

Gottlieb, B; Trifiro, M; Lumbroso, R; Vasiliou, D M; Pinsky, L

1996-01-01

The current version of the androgen receptor (AR) gene mutations database is described. We have added (if available) data on the androgen binding phenotype of the mutant AR, the clinical phenotype of the affected persons, the family history and whether the pathogenicity of a mutation has been proven. Exonic mutations are now listed in 5'-->3' sequence regardless of type and single base pair changes are presented in codon context. Splice site and intronic mutations are listed separately. The database has allowed us to substantiate and amplify the observation of mutational hot spots within exons encoding the AR androgen binding domain. The database is available from EML (ftp://www.ebi.ac.uk/pub/databases/androgen) or as a Macintosh Filemaker file (MC33@musica.mcgill.ca).

PAMDB: a comprehensive Pseudomonas aeruginosa metabolome database.

PubMed

Huang, Weiliang; Brewer, Luke K; Jones, Jace W; Nguyen, Angela T; Marcu, Ana; Wishart, David S; Oglesby-Sherrouse, Amanda G; Kane, Maureen A; Wilks, Angela

2018-01-04

The Pseudomonas aeruginosaMetabolome Database (PAMDB, http://pseudomonas.umaryland.edu) is a searchable, richly annotated metabolite database specific to P. aeruginosa. P. aeruginosa is a soil organism and significant opportunistic pathogen that adapts to its environment through a versatile energy metabolism network. Furthermore, P. aeruginosa is a model organism for the study of biofilm formation, quorum sensing, and bioremediation processes, each of which are dependent on unique pathways and metabolites. The PAMDB is modelled on the Escherichia coli (ECMDB), yeast (YMDB) and human (HMDB) metabolome databases and contains >4370 metabolites and 938 pathways with links to over 1260 genes and proteins. The database information was compiled from electronic databases, journal articles and mass spectrometry (MS) metabolomic data obtained in our laboratories. For each metabolite entered, we provide detailed compound descriptions, names and synonyms, structural and physiochemical information, nuclear magnetic resonance (NMR) and MS spectra, enzymes and pathway information, as well as gene and protein sequences. The database allows extensive searching via chemical names, structure and molecular weight, together with gene, protein and pathway relationships. The PAMBD and its future iterations will provide a valuable resource to biologists, natural product chemists and clinicians in identifying active compounds, potential biomarkers and clinical diagnostics. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

RARGE II: an integrated phenotype database of Arabidopsis mutant traits using a controlled vocabulary.

PubMed

Akiyama, Kenji; Kurotani, Atsushi; Iida, Kei; Kuromori, Takashi; Shinozaki, Kazuo; Sakurai, Tetsuya

2014-01-01

Arabidopsis thaliana is one of the most popular experimental plants. However, only 40% of its genes have at least one experimental Gene Ontology (GO) annotation assigned. Systematic observation of mutant phenotypes is an important technique for elucidating gene functions. Indeed, several large-scale phenotypic analyses have been performed and have generated phenotypic data sets from many Arabidopsis mutant lines and overexpressing lines, which are freely available online. Since each Arabidopsis mutant line database uses individual phenotype expression, the differences in the structured term sets used by each database make it difficult to compare data sets and make it impossible to search across databases. Therefore, we obtained publicly available information for a total of 66,209 Arabidopsis mutant lines, including loss-of-function (RATM and TARAPPER) and gain-of-function (AtFOX and OsFOX) lines, and integrated the phenotype data by mapping the descriptions onto Plant Ontology (PO) and Phenotypic Quality Ontology (PATO) terms. This approach made it possible to manage the four different phenotype databases as one large data set. Here, we report a publicly accessible web-based database, the RIKEN Arabidopsis Genome Encyclopedia II (RARGE II; http://rarge-v2.psc.riken.jp/), in which all of the data described in this study are included. Using the database, we demonstrated consistency (in terms of protein function) with a previous study and identified the presumed function of an unknown gene. We provide examples of AT1G21600, which is a subunit in the plastid-encoded RNA polymerase complex, and AT5G56980, which is related to the jasmonic acid signaling pathway.

RCDB: Renal Cancer Gene Database.

PubMed

Ramana, Jayashree

2012-05-18

Renal cell carcinoma or RCC is one of the common and most lethal urological cancers, with 40% of the patients succumbing to death because of metastatic progression of the disease. Treatment of metastatic RCC remains highly challenging because of its resistance to chemotherapy as well as radiotherapy, besides surgical resection. Whereas RCC comprises tumors with differing histological types, clear cell RCC remains the most common. A major problem in the clinical management of patients presenting with localized ccRCC is the inability to determine tumor aggressiveness and accurately predict the risk of metastasis following surgery. As a measure to improve the diagnosis and prognosis of RCC, researchers have identified several molecular markers through a number of techniques. However the wealth of information available is scattered in literature and not easily amenable to data-mining. To reduce this gap, this work describes a comprehensive repository called Renal Cancer Gene Database, as an integrated gateway to study renal cancer related data. Renal Cancer Gene Database is a manually curated compendium of 240 protein-coding and 269 miRNA genes contributing to the etiology and pathogenesis of various forms of renal cell carcinomas. The protein coding genes have been classified according to the kind of gene alteration observed in RCC. RCDB also includes the miRNAsdysregulated in RCC, along with the corresponding information regarding the type of RCC and/or metastatic or prognostic significance. While some of the miRNA genes showed an association with other types of cancers few were unique to RCC. Users can query the database using keywords, category and chromosomal location of the genes. The knowledgebase can be freely accessed via a user-friendly web interface at http://www.juit.ac.in/attachments/jsr/rcdb/homenew.html. It is hoped that this database would serve as a useful complement to the existing public resources and as a good starting point for researchers and physicians interested in RCC genetics.

The barley EST DNA Replication and Repair Database (bEST-DRRD) as a tool for the identification of the genes involved in DNA replication and repair.

PubMed

Gruszka, Damian; Marzec, Marek; Szarejko, Iwona

2012-06-14

The high level of conservation of genes that regulate DNA replication and repair indicates that they may serve as a source of information on the origin and evolution of the species and makes them a reliable system for the identification of cross-species homologs. Studies that had been conducted to date shed light on the processes of DNA replication and repair in bacteria, yeast and mammals. However, there is still much to be learned about the process of DNA damage repair in plants. These studies, which were conducted mainly using bioinformatics tools, enabled the list of genes that participate in various pathways of DNA repair in Arabidopsis thaliana (L.) Heynh to be outlined; however, information regarding these mechanisms in crop plants is still very limited. A similar, functional approach is particularly difficult for a species whose complete genomic sequences are still unavailable. One of the solutions is to apply ESTs (Expressed Sequence Tags) as the basis for gene identification. For the construction of the barley EST DNA Replication and Repair Database (bEST-DRRD), presented here, the Arabidopsis nucleotide and protein sequences involved in DNA replication and repair were used to browse for and retrieve the deposited sequences, derived from four barley (Hordeum vulgare L.) sequence databases, including the "Barley Genome version 0.05" database (encompassing ca. 90% of barley coding sequences) and from two databases covering the complete genomes of two monocot models: Oryza sativa L. and Brachypodium distachyon L. in order to identify homologous genes. Sequences of the categorised Arabidopsis queries are used for browsing the repositories, which are located on the ViroBLAST platform. The bEST-DRRD is currently used in our project during the identification and validation of the barley genes involved in DNA repair. The presented database provides information about the Arabidopsis genes involved in DNA replication and repair, their expression patterns and models of protein interactions. It was designed and established to provide an open-access tool for the identification of monocot homologs of known Arabidopsis genes that are responsible for DNA-related processes. The barley genes identified in the project are currently being analysed to validate their function.

rSNPBase 3.0: an updated database of SNP-related regulatory elements, element-gene pairs and SNP-based gene regulatory networks.

PubMed

Guo, Liyuan; Wang, Jing

2018-01-04

Here, we present the updated rSNPBase 3.0 database (http://rsnp3.psych.ac.cn), which provides human SNP-related regulatory elements, element-gene pairs and SNP-based regulatory networks. This database is the updated version of the SNP regulatory annotation database rSNPBase and rVarBase. In comparison to the last two versions, there are both structural and data adjustments in rSNPBase 3.0: (i) The most significant new feature is the expansion of analysis scope from SNP-related regulatory elements to include regulatory element-target gene pairs (E-G pairs), therefore it can provide SNP-based gene regulatory networks. (ii) Web function was modified according to data content and a new network search module is provided in the rSNPBase 3.0 in addition to the previous regulatory SNP (rSNP) search module. The two search modules support data query for detailed information (related-elements, element-gene pairs, and other extended annotations) on specific SNPs and SNP-related graphic networks constructed by interacting transcription factors (TFs), miRNAs and genes. (3) The type of regulatory elements was modified and enriched. To our best knowledge, the updated rSNPBase 3.0 is the first data tool supports SNP functional analysis from a regulatory network prospective, it will provide both a comprehensive understanding and concrete guidance for SNP-related regulatory studies. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

rSNPBase 3.0: an updated database of SNP-related regulatory elements, element-gene pairs and SNP-based gene regulatory networks

PubMed Central

2018-01-01

Abstract Here, we present the updated rSNPBase 3.0 database (http://rsnp3.psych.ac.cn), which provides human SNP-related regulatory elements, element-gene pairs and SNP-based regulatory networks. This database is the updated version of the SNP regulatory annotation database rSNPBase and rVarBase. In comparison to the last two versions, there are both structural and data adjustments in rSNPBase 3.0: (i) The most significant new feature is the expansion of analysis scope from SNP-related regulatory elements to include regulatory element–target gene pairs (E–G pairs), therefore it can provide SNP-based gene regulatory networks. (ii) Web function was modified according to data content and a new network search module is provided in the rSNPBase 3.0 in addition to the previous regulatory SNP (rSNP) search module. The two search modules support data query for detailed information (related-elements, element-gene pairs, and other extended annotations) on specific SNPs and SNP-related graphic networks constructed by interacting transcription factors (TFs), miRNAs and genes. (3) The type of regulatory elements was modified and enriched. To our best knowledge, the updated rSNPBase 3.0 is the first data tool supports SNP functional analysis from a regulatory network prospective, it will provide both a comprehensive understanding and concrete guidance for SNP-related regulatory studies. PMID:29140525

HOWDY: an integrated database system for human genome research

PubMed Central

Hirakawa, Mika

2002-01-01

HOWDY is an integrated database system for accessing and analyzing human genomic information (http://www-alis.tokyo.jst.go.jp/HOWDY/). HOWDY stores information about relationships between genetic objects and the data extracted from a number of databases. HOWDY consists of an Internet accessible user interface that allows thorough searching of the human genomic databases using the gene symbols and their aliases. It also permits flexible editing of the sequence data. The database can be searched using simple words and the search can be restricted to a specific cytogenetic location. Linear maps displaying markers and genes on contig sequences are available, from which an object can be chosen. Any search starting point identifies all the information matching the query. HOWDY provides a convenient search environment of human genomic data for scientists unsure which database is most appropriate for their search. PMID:11752279

Novel primers for complete mitochondrial cytochrome b genesequencing in mammals

USGS Publications Warehouse

Naidu, Ashwin; Fitak, Robert R.; Munguia-Vega, Adrian; Culver, Melanie

2011-01-01

Sequence-based species identification relies on the extent and integrity of sequence data available in online databases such as GenBank. When identifying species from a sample of unknown origin, partial DNA sequences obtained from the sample are aligned against existing sequences in databases. When the sequence from the matching species is not present in the database, high-scoring alignments with closely related sequences might produce unreliable results on species identity. For species identification in mammals, the cytochrome b (cyt b) gene has been identified to be highly informative; thus, large amounts of reference sequence data from the cyt b gene are much needed. To enhance availability of cyt b gene sequence data on a large number of mammalian species in GenBank and other such publicly accessible online databases, we identified a primer pair for complete cyt b gene sequencing in mammals. Using this primer pair, we successfully PCR amplified and sequenced the complete cyt b gene from 40 of 44 mammalian species representing 10 orders of mammals. We submitted 40 complete, correctly annotated, cyt b protein coding sequences to GenBank. To our knowledge, this is the first single primer pair to amplify the complete cyt b gene in a broad range of mammalian species. This primer pair can be used for the addition of new cyt b gene sequences and to enhance data available on species represented in GenBank. The availability of novel and complete gene sequences as high-quality reference data can improve the reliability of sequence-based species identification.

Inferring gene and protein interactions using PubMed citations and consensus Bayesian networks.

PubMed

Deeter, Anthony; Dalman, Mark; Haddad, Joseph; Duan, Zhong-Hui

2017-01-01

The PubMed database offers an extensive set of publication data that can be useful, yet inherently complex to use without automated computational techniques. Data repositories such as the Genomic Data Commons (GDC) and the Gene Expression Omnibus (GEO) offer experimental data storage and retrieval as well as curated gene expression profiles. Genetic interaction databases, including Reactome and Ingenuity Pathway Analysis, offer pathway and experiment data analysis using data curated from these publications and data repositories. We have created a method to generate and analyze consensus networks, inferring potential gene interactions, using large numbers of Bayesian networks generated by data mining publications in the PubMed database. Through the concept of network resolution, these consensus networks can be tailored to represent possible genetic interactions. We designed a set of experiments to confirm that our method is stable across variation in both sample and topological input sizes. Using gene product interactions from the KEGG pathway database and data mining PubMed publication abstracts, we verify that regardless of the network resolution or the inferred consensus network, our method is capable of inferring meaningful gene interactions through consensus Bayesian network generation with multiple, randomized topological orderings. Our method can not only confirm the existence of currently accepted interactions, but has the potential to hypothesize new ones as well. We show our method confirms the existence of known gene interactions such as JAK-STAT-PI3K-AKT-mTOR, infers novel gene interactions such as RAS- Bcl-2 and RAS-AKT, and found significant pathway-pathway interactions between the JAK-STAT signaling and Cardiac Muscle Contraction KEGG pathways.

Development of a DNA microarray to detect antimicrobial resistance genes identified in the national center for biotechnology information database

USDA-ARS?s Scientific Manuscript database

High density genotyping techniques are needed for investigating antimicrobial resistance especially in the case of multi-drug resistant (MDR) isolates. To achieve this all antimicrobial resistance genes in the NCBI Genbank database were identified by key word searches of sequence annotations and the...

Biochemical, transcriptomic and proteomic analyses of digestion in the scorpion Tityus serrulatus: insights into function and evolution of digestion in an ancient arthropod.

PubMed

Fuzita, Felipe J; Pinkse, Martijn W H; Patane, José S L; Juliano, Maria A; Verhaert, Peter D E M; Lopes, Adriana R

2015-01-01

Scorpions are among the oldest terrestrial arthropods and they have passed through small morphological changes during their evolutionary history on land. They are efficient predators capable of capturing and consuming large preys and due to envenomation these animals can become a human health challenge. Understanding the physiology of scorpions can not only lead to evolutionary insights but also is a crucial step in the development of control strategies. However, the digestive process in scorpions has been scarcely studied. In this work, we describe the combinatory use of next generation sequencing, proteomic analysis and biochemical assays in order to investigate the digestive process in the yellow scorpion Tityus serrulatus, mainly focusing in the initial protein digestion. The transcriptome generated database allowed the quantitative identification by mass spectrometry of different enzymes and proteins involved in digestion. All the results suggested that cysteine cathepsins play an important role in protein digestion. Two digestive cysteine cathepsins were isolated and characterized presenting acidic characteristics (pH optima and stability), zymogen conversion to the mature form after acidic activation and a cross-class inhibition by pepstatin. A more elucidative picture of the molecular mechanism of digestion in a scorpion was proposed based on our results from Tityus serrulatus. The midgut and midgut glands (MMG) are composed by secretory and digestive cells. In fasting animals, the secretory granules are ready for the next predation event, containing enzymes needed for alkaline extra-oral digestion which will compose the digestive fluid, such as trypsins, astacins and chitinase. The digestive vacuoles are filled with an acidic proteolytic cocktail to the intracellular digestion composed by cathepsins L, B, F, D and legumain. Other proteins as lipases, carbohydrases, ctenitoxins and a chitolectin with a perithrophin domain were also detected. Evolutionarily, a large gene duplication of cathepsin L occurred in Arachnida with the sequences from ticks being completely divergent from other arachnids probably due to the particular selective pressures over this group.

An ensemble rank learning approach for gene prioritization.

PubMed

Lee, Po-Feng; Soo, Von-Wun

2013-01-01

Several different computational approaches have been developed to solve the gene prioritization problem. We intend to use the ensemble boosting learning techniques to combine variant computational approaches for gene prioritization in order to improve the overall performance. In particular we add a heuristic weighting function to the Rankboost algorithm according to: 1) the absolute ranks generated by the adopted methods for a certain gene, and 2) the ranking relationship between all gene-pairs from each prioritization result. We select 13 known prostate cancer genes in OMIM database as training set and protein coding gene data in HGNC database as test set. We adopt the leave-one-out strategy for the ensemble rank boosting learning. The experimental results show that our ensemble learning approach outperforms the four gene-prioritization methods in ToppGene suite in the ranking results of the 13 known genes in terms of mean average precision, ROC and AUC measures.

PANTHER: a browsable database of gene products organized by biological function, using curated protein family and subfamily classification.

PubMed

Thomas, Paul D; Kejariwal, Anish; Campbell, Michael J; Mi, Huaiyu; Diemer, Karen; Guo, Nan; Ladunga, Istvan; Ulitsky-Lazareva, Betty; Muruganujan, Anushya; Rabkin, Steven; Vandergriff, Jody A; Doremieux, Olivier

2003-01-01

The PANTHER database was designed for high-throughput analysis of protein sequences. One of the key features is a simplified ontology of protein function, which allows browsing of the database by biological functions. Biologist curators have associated the ontology terms with groups of protein sequences rather than individual sequences. Statistical models (Hidden Markov Models, or HMMs) are built from each of these groups. The advantage of this approach is that new sequences can be automatically classified as they become available. To ensure accurate functional classification, HMMs are constructed not only for families, but also for functionally distinct subfamilies. Multiple sequence alignments and phylogenetic trees, including curator-assigned information, are available for each family. The current version of the PANTHER database includes training sequences from all organisms in the GenBank non-redundant protein database, and the HMMs have been used to classify gene products across the entire genomes of human, and Drosophila melanogaster. The ontology terms and protein families and subfamilies, as well as Drosophila gene c;assifications, can be browsed and searched for free. Due to outstanding contractual obligations, access to human gene classifications and to protein family trees and multiple sequence alignments will temporarily require a nominal registration fee. PANTHER is publicly available on the web at http://panther.celera.com.

yStreX: yeast stress expression database

PubMed Central

Wanichthanarak, Kwanjeera; Nookaew, Intawat; Petranovic, Dina

2014-01-01

Over the past decade genome-wide expression analyses have been often used to study how expression of genes changes in response to various environmental stresses. Many of these studies (such as effects of oxygen concentration, temperature stress, low pH stress, osmotic stress, depletion or limitation of nutrients, addition of different chemical compounds, etc.) have been conducted in the unicellular Eukaryal model, yeast Saccharomyces cerevisiae. However, the lack of a unifying or integrated, bioinformatics platform that would permit efficient and rapid use of all these existing data remain an important issue. To facilitate research by exploiting existing transcription data in the field of yeast physiology, we have developed the yStreX database. It is an online repository of analyzed gene expression data from curated data sets from different studies that capture genome-wide transcriptional changes in response to diverse environmental transitions. The first aim of this online database is to facilitate comparison of cross-platform and cross-laboratory gene expression data. Additionally, we performed different expression analyses, meta-analyses and gene set enrichment analyses; and the results are also deposited in this database. Lastly, we constructed a user-friendly Web interface with interactive visualization to provide intuitive access and to display the queried data for users with no background in bioinformatics. Database URL: http://www.ystrexdb.com PMID:25024351

A database for the analysis of immunity genes in Drosophila: PADMA database.

PubMed

Lee, Mark J; Mondal, Ariful; Small, Chiyedza; Paddibhatla, Indira; Kawaguchi, Akira; Govind, Shubha

2011-01-01

While microarray experiments generate voluminous data, discerning trends that support an existing or alternative paradigm is challenging. To synergize hypothesis building and testing, we designed the Pathogen Associated Drosophila MicroArray (PADMA) database for easy retrieval and comparison of microarray results from immunity-related experiments (www.padmadatabase.org). PADMA also allows biologists to upload their microarray-results and compare it with datasets housed within PADMA. We tested PADMA using a preliminary dataset from Ganaspis xanthopoda-infected fly larvae, and uncovered unexpected trends in gene expression, reshaping our hypothesis. Thus, the PADMA database will be a useful resource to fly researchers to evaluate, revise, and refine hypotheses.

HbVar: A relational database of human hemoglobin variants and thalassemia mutations at the globin gene server.

PubMed

Hardison, Ross C; Chui, David H K; Giardine, Belinda; Riemer, Cathy; Patrinos, George P; Anagnou, Nicholas; Miller, Webb; Wajcman, Henri

2002-03-01

We have constructed a relational database of hemoglobin variants and thalassemia mutations, called HbVar, which can be accessed on the web at http://globin.cse.psu.edu. Extensive information is recorded for each variant and mutation, including a description of the variant and associated pathology, hematology, electrophoretic mobility, methods of isolation, stability information, ethnic occurrence, structure studies, functional studies, and references. The initial information was derived from books by Dr. Titus Huisman and colleagues [Huisman et al., 1996, 1997, 1998]. The current database is updated regularly with the addition of new data and corrections to previous data. Queries can be formulated based on fields in the database. Tables of common categories of variants, such as all those involving the alpha1-globin gene (HBA1) or all those that result in high oxygen affinity, are maintained by automated queries on the database. Users can formulate more precise queries, such as identifying "all beta-globin variants associated with instability and found in Scottish populations." This new database should be useful for clinical diagnosis as well as in fundamental studies of hemoglobin biochemistry, globin gene regulation, and human sequence variation at these loci. Copyright 2002 Wiley-Liss, Inc.

GMDD: a database of GMO detection methods.

PubMed

Dong, Wei; Yang, Litao; Shen, Kailin; Kim, Banghyun; Kleter, Gijs A; Marvin, Hans J P; Guo, Rong; Liang, Wanqi; Zhang, Dabing

2008-06-04

Since more than one hundred events of genetically modified organisms (GMOs) have been developed and approved for commercialization in global area, the GMO analysis methods are essential for the enforcement of GMO labelling regulations. Protein and nucleic acid-based detection techniques have been developed and utilized for GMOs identification and quantification. However, the information for harmonization and standardization of GMO analysis methods at global level is needed. GMO Detection method Database (GMDD) has collected almost all the previous developed and reported GMOs detection methods, which have been grouped by different strategies (screen-, gene-, construct-, and event-specific), and also provide a user-friendly search service of the detection methods by GMO event name, exogenous gene, or protein information, etc. In this database, users can obtain the sequences of exogenous integration, which will facilitate PCR primers and probes design. Also the information on endogenous genes, certified reference materials, reference molecules, and the validation status of developed methods is included in this database. Furthermore, registered users can also submit new detection methods and sequences to this database, and the newly submitted information will be released soon after being checked. GMDD contains comprehensive information of GMO detection methods. The database will make the GMOs analysis much easier.

SpliceDisease database: linking RNA splicing and disease.

PubMed

Wang, Juan; Zhang, Jie; Li, Kaibo; Zhao, Wei; Cui, Qinghua

2012-01-01

RNA splicing is an important aspect of gene regulation in many organisms. Splicing of RNA is regulated by complicated mechanisms involving numerous RNA-binding proteins and the intricate network of interactions among them. Mutations in cis-acting splicing elements or its regulatory proteins have been shown to be involved in human diseases. Defects in pre-mRNA splicing process have emerged as a common disease-causing mechanism. Therefore, a database integrating RNA splicing and disease associations would be helpful for understanding not only the RNA splicing but also its contribution to disease. In SpliceDisease database, we manually curated 2337 splicing mutation disease entries involving 303 genes and 370 diseases, which have been supported experimentally in 898 publications. The SpliceDisease database provides information including the change of the nucleotide in the sequence, the location of the mutation on the gene, the reference Pubmed ID and detailed description for the relationship among gene mutations, splicing defects and diseases. We standardized the names of the diseases and genes and provided links for these genes to NCBI and UCSC genome browser for further annotation and genomic sequences. For the location of the mutation, we give direct links of the entry to the respective position/region in the genome browser. The users can freely browse, search and download the data in SpliceDisease at http://cmbi.bjmu.edu.cn/sdisease.

GETPrime: a gene- or transcript-specific primer database for quantitative real-time PCR.

PubMed

Gubelmann, Carine; Gattiker, Alexandre; Massouras, Andreas; Hens, Korneel; David, Fabrice; Decouttere, Frederik; Rougemont, Jacques; Deplancke, Bart

2011-01-01

The vast majority of genes in humans and other organisms undergo alternative splicing, yet the biological function of splice variants is still very poorly understood in large part because of the lack of simple tools that can map the expression profiles and patterns of these variants with high sensitivity. High-throughput quantitative real-time polymerase chain reaction (qPCR) is an ideal technique to accurately quantify nucleic acid sequences including splice variants. However, currently available primer design programs do not distinguish between splice variants and also differ substantially in overall quality, functionality or throughput mode. Here, we present GETPrime, a primer database supported by a novel platform that uniquely combines and automates several features critical for optimal qPCR primer design. These include the consideration of all gene splice variants to enable either gene-specific (covering the majority of splice variants) or transcript-specific (covering one splice variant) expression profiling, primer specificity validation, automated best primer pair selection according to strict criteria and graphical visualization of the latter primer pairs within their genomic context. GETPrime primers have been extensively validated experimentally, demonstrating high transcript specificity in complex samples. Thus, the free-access, user-friendly GETPrime database allows fast primer retrieval and visualization for genes or groups of genes of most common model organisms, and is available at http://updepla1srv1.epfl.ch/getprime/. Database URL: http://deplanckelab.epfl.ch.

pseudoMap: an innovative and comprehensive resource for identification of siRNA-mediated mechanisms in human transcribed pseudogenes.

PubMed

Chan, Wen-Ling; Yang, Wen-Kuang; Huang, Hsien-Da; Chang, Jan-Gowth

2013-01-01

RNA interference (RNAi) is a gene silencing process within living cells, which is controlled by the RNA-induced silencing complex with a sequence-specific manner. In flies and mice, the pseudogene transcripts can be processed into short interfering RNAs (siRNAs) that regulate protein-coding genes through the RNAi pathway. Following these findings, we construct an innovative and comprehensive database to elucidate siRNA-mediated mechanism in human transcribed pseudogenes (TPGs). To investigate TPG producing siRNAs that regulate protein-coding genes, we mapped the TPGs to small RNAs (sRNAs) that were supported by publicly deep sequencing data from various sRNA libraries and constructed the TPG-derived siRNA-target interactions. In addition, we also presented that TPGs can act as a target for miRNAs that actually regulate the parental gene. To enable the systematic compilation and updating of these results and additional information, we have developed a database, pseudoMap, capturing various types of information, including sequence data, TPG and cognate annotation, deep sequencing data, RNA-folding structure, gene expression profiles, miRNA annotation and target prediction. As our knowledge, pseudoMap is the first database to demonstrate two mechanisms of human TPGs: encoding siRNAs and decoying miRNAs that target the parental gene. pseudoMap is freely accessible at http://pseudomap.mbc.nctu.edu.tw/. Database URL: http://pseudomap.mbc.nctu.edu.tw/

GETPrime: a gene- or transcript-specific primer database for quantitative real-time PCR

PubMed Central

Gubelmann, Carine; Gattiker, Alexandre; Massouras, Andreas; Hens, Korneel; David, Fabrice; Decouttere, Frederik; Rougemont, Jacques; Deplancke, Bart

2011-01-01

The vast majority of genes in humans and other organisms undergo alternative splicing, yet the biological function of splice variants is still very poorly understood in large part because of the lack of simple tools that can map the expression profiles and patterns of these variants with high sensitivity. High-throughput quantitative real-time polymerase chain reaction (qPCR) is an ideal technique to accurately quantify nucleic acid sequences including splice variants. However, currently available primer design programs do not distinguish between splice variants and also differ substantially in overall quality, functionality or throughput mode. Here, we present GETPrime, a primer database supported by a novel platform that uniquely combines and automates several features critical for optimal qPCR primer design. These include the consideration of all gene splice variants to enable either gene-specific (covering the majority of splice variants) or transcript-specific (covering one splice variant) expression profiling, primer specificity validation, automated best primer pair selection according to strict criteria and graphical visualization of the latter primer pairs within their genomic context. GETPrime primers have been extensively validated experimentally, demonstrating high transcript specificity in complex samples. Thus, the free-access, user-friendly GETPrime database allows fast primer retrieval and visualization for genes or groups of genes of most common model organisms, and is available at http://updepla1srv1.epfl.ch/getprime/. Database URL: http://deplanckelab.epfl.ch. PMID:21917859

MIRNA-DISTILLER: A Stand-Alone Application to Compile microRNA Data from Databases.

PubMed

Rieger, Jessica K; Bodan, Denis A; Zanger, Ulrich M

2011-01-01

MicroRNAs (miRNA) are small non-coding RNA molecules of ∼22 nucleotides which regulate large numbers of genes by binding to seed sequences at the 3'-untranslated region of target gene transcripts. The target mRNA is then usually degraded or translation is inhibited, although thus resulting in posttranscriptional down regulation of gene expression at the mRNA and/or protein level. Due to the bioinformatic difficulties in predicting functional miRNA binding sites, several publically available databases have been developed that predict miRNA binding sites based on different algorithms. The parallel use of different databases is currently indispensable, but highly uncomfortable and time consuming, especially when working with numerous genes of interest. We have therefore developed a new stand-alone program, termed MIRNA-DISTILLER, which allows to compile miRNA data for given target genes from public databases. Currently implemented are TargetScan, microCosm, and miRDB, which may be queried independently, pairwise, or together to calculate the respective intersections. Data are stored locally for application of further analysis tools including freely definable biological parameter filters, customized output-lists for both miRNAs and target genes, and various graphical facilities. The software, a data example file and a tutorial are freely available at http://www.ikp-stuttgart.de/content/language1/html/10415.asp.

MIRNA-DISTILLER: A Stand-Alone Application to Compile microRNA Data from Databases

PubMed Central

Rieger, Jessica K.; Bodan, Denis A.; Zanger, Ulrich M.

2011-01-01

MicroRNAs (miRNA) are small non-coding RNA molecules of ∼22 nucleotides which regulate large numbers of genes by binding to seed sequences at the 3′-untranslated region of target gene transcripts. The target mRNA is then usually degraded or translation is inhibited, although thus resulting in posttranscriptional down regulation of gene expression at the mRNA and/or protein level. Due to the bioinformatic difficulties in predicting functional miRNA binding sites, several publically available databases have been developed that predict miRNA binding sites based on different algorithms. The parallel use of different databases is currently indispensable, but highly uncomfortable and time consuming, especially when working with numerous genes of interest. We have therefore developed a new stand-alone program, termed MIRNA-DISTILLER, which allows to compile miRNA data for given target genes from public databases. Currently implemented are TargetScan, microCosm, and miRDB, which may be queried independently, pairwise, or together to calculate the respective intersections. Data are stored locally for application of further analysis tools including freely definable biological parameter filters, customized output-lists for both miRNAs and target genes, and various graphical facilities. The software, a data example file and a tutorial are freely available at http://www.ikp-stuttgart.de/content/language1/html/10415.asp PMID:22303335

MalaCards: an integrated compendium for diseases and their annotation

PubMed Central

Rappaport, Noa; Nativ, Noam; Stelzer, Gil; Twik, Michal; Guan-Golan, Yaron; Iny Stein, Tsippi; Bahir, Iris; Belinky, Frida; Morrey, C. Paul; Safran, Marilyn; Lancet, Doron

2013-01-01

Comprehensive disease classification, integration and annotation are crucial for biomedical discovery. At present, disease compilation is incomplete, heterogeneous and often lacking systematic inquiry mechanisms. We introduce MalaCards, an integrated database of human maladies and their annotations, modeled on the architecture and strategy of the GeneCards database of human genes. MalaCards mines and merges 44 data sources to generate a computerized card for each of 16 919 human diseases. Each MalaCard contains disease-specific prioritized annotations, as well as inter-disease connections, empowered by the GeneCards relational database, its searches and GeneDecks set analyses. First, we generate a disease list from 15 ranked sources, using disease-name unification heuristics. Next, we use four schemes to populate MalaCards sections: (i) directly interrogating disease resources, to establish integrated disease names, synonyms, summaries, drugs/therapeutics, clinical features, genetic tests and anatomical context; (ii) searching GeneCards for related publications, and for associated genes with corresponding relevance scores; (iii) analyzing disease-associated gene sets in GeneDecks to yield affiliated pathways, phenotypes, compounds and GO terms, sorted by a composite relevance score and presented with GeneCards links; and (iv) searching within MalaCards itself, e.g. for additional related diseases and anatomical context. The latter forms the basis for the construction of a disease network, based on shared MalaCards annotations, embodying associations based on etiology, clinical features and clinical conditions. This broadly disposed network has a power-law degree distribution, suggesting that this might be an inherent property of such networks. Work in progress includes hierarchical malady classification, ontological mapping and disease set analyses, striving to make MalaCards an even more effective tool for biomedical research. Database URL: http://www.malacards.org/ PMID:23584832

The complex genetics of human insulin-like growth factor 2 are not reflected in public databases.

PubMed

Rotwein, Peter

2018-03-23

Recent advances in genetics present unique opportunities for enhancing knowledge about human physiology and disease susceptibility. Understanding this information at the individual gene level is challenging and requires extracting, collating, and interpreting data from a variety of public gene repositories. Here, I illustrate this challenge by analyzing the gene for human insulin-like growth factor 2 ( IGF2 ) through the lens of several databases. IGF2, a 67-amino acid secreted peptide, is essential for normal prenatal growth and is involved in other physiological and pathophysiological processes in humans. Surprisingly, none of the genetic databases accurately described or completely delineated human IGF2 gene structure or transcript expression, even though all relevant information could be found in the published literature. Although IGF2 shares multiple features with the mouse Igf2 gene, it has several unique properties, including transcription from five promoters. Both genes undergo parental imprinting, with IGF2 / Igf2 being expressed primarily from the paternal chromosome and the adjacent H19 gene from the maternal chromosome. Unlike mouse Igf2 , whose expression declines after birth, human IGF2 remains active throughout life. This characteristic has been attributed to a unique human gene promoter that escapes imprinting, but as shown here, it involves several different promoters with distinct tissue-specific expression patterns. Because new testable hypotheses could lead to critical insights into IGF2 actions in human physiology and disease, it is incumbent that our fundamental understanding is accurate. Similar challenges affecting knowledge of other human genes should promote attempts to critically evaluate, interpret, and correct human genetic data in publicly available databases. © 2018 by The American Society for Biochemistry and Molecular Biology, Inc.

Wild-type isopropylmalate isomerase in Salmonella typhimurium is composed of two different subunits.

PubMed Central

Fultz, P N; Kemper, J

1981-01-01

The isopropylmalate isomerase in Salmonella typhimurium is the second enzyme specific for leucine biosynthesis. It is a complex enzyme composed of two subunits which are coded for by two genes of the leucine operon, leuC and leuD. The two polypeptides have been shown to copurify through successive ammonium sulfate fractionations and have been identified on sodium dodecyl sulfate-polyacrylamide gels as having molecular weights of 51,000 (leuC gene product) and 23,500 (leuD gene product). They have also been shown to be fairly stable, since in vitro complementation of cell-free extracts of leuC and leuD mutant strains was demonstrated, with only a 40% loss of activity 16 h after preparation of the extracts. The native isopropylmalate isomerase was shown to have a Km for its substrate alpha-isopropylmalate of 3 x 10(-4)M. Images PMID:7026530

GExplore: a web server for integrated queries of protein domains, gene expression and mutant phenotypes

PubMed Central

2009-01-01

Background The majority of the genes even in well-studied multi-cellular model organisms have not been functionally characterized yet. Mining the numerous genome wide data sets related to protein function to retrieve potential candidate genes for a particular biological process remains a challenge. Description GExplore has been developed to provide a user-friendly database interface for data mining at the gene expression/protein function level to help in hypothesis development and experiment design. It supports combinatorial searches for proteins with certain domains, tissue- or developmental stage-specific expression patterns, and mutant phenotypes. GExplore operates on a stand-alone database and has fast response times, which is essential for exploratory searches. The interface is not only user-friendly, but also modular so that it accommodates additional data sets in the future. Conclusion GExplore is an online database for quick mining of data related to gene and protein function, providing a multi-gene display of data sets related to the domain composition of proteins as well as expression and phenotype data. GExplore is publicly available at: http://genome.sfu.ca/gexplore/ PMID:19917126

Bayesian approach to transforming public gene expression repositories into disease diagnosis databases.

PubMed

Huang, Haiyan; Liu, Chun-Chi; Zhou, Xianghong Jasmine

2010-04-13

The rapid accumulation of gene expression data has offered unprecedented opportunities to study human diseases. The National Center for Biotechnology Information Gene Expression Omnibus is currently the largest database that systematically documents the genome-wide molecular basis of diseases. However, thus far, this resource has been far from fully utilized. This paper describes the first study to transform public gene expression repositories into an automated disease diagnosis database. Particularly, we have developed a systematic framework, including a two-stage Bayesian learning approach, to achieve the diagnosis of one or multiple diseases for a query expression profile along a hierarchical disease taxonomy. Our approach, including standardizing cross-platform gene expression data and heterogeneous disease annotations, allows analyzing both sources of information in a unified probabilistic system. A high level of overall diagnostic accuracy was shown by cross validation. It was also demonstrated that the power of our method can increase significantly with the continued growth of public gene expression repositories. Finally, we showed how our disease diagnosis system can be used to characterize complex phenotypes and to construct a disease-drug connectivity map.

MARRVEL: Integration of Human and Model Organism Genetic Resources to Facilitate Functional Annotation of the Human Genome.

PubMed

Wang, Julia; Al-Ouran, Rami; Hu, Yanhui; Kim, Seon-Young; Wan, Ying-Wooi; Wangler, Michael F; Yamamoto, Shinya; Chao, Hsiao-Tuan; Comjean, Aram; Mohr, Stephanie E; Perrimon, Norbert; Liu, Zhandong; Bellen, Hugo J

2017-06-01

One major challenge encountered with interpreting human genetic variants is the limited understanding of the functional impact of genetic alterations on biological processes. Furthermore, there remains an unmet demand for an efficient survey of the wealth of information on human homologs in model organisms across numerous databases. To efficiently assess the large volume of publically available information, it is important to provide a concise summary of the most relevant information in a rapid user-friendly format. To this end, we created MARRVEL (model organism aggregated resources for rare variant exploration). MARRVEL is a publicly available website that integrates information from six human genetic databases and seven model organism databases. For any given variant or gene, MARRVEL displays information from OMIM, ExAC, ClinVar, Geno2MP, DGV, and DECIPHER. Importantly, it curates model organism-specific databases to concurrently display a concise summary regarding the human gene homologs in budding and fission yeast, worm, fly, fish, mouse, and rat on a single webpage. Experiment-based information on tissue expression, protein subcellular localization, biological process, and molecular function for the human gene and homologs in the seven model organisms are arranged into a concise output. Hence, rather than visiting multiple separate databases for variant and gene analysis, users can obtain important information by searching once through MARRVEL. Altogether, MARRVEL dramatically improves efficiency and accessibility to data collection and facilitates analysis of human genes and variants by cross-disciplinary integration of 18 million records available in public databases to facilitate clinical diagnosis and basic research. Copyright © 2017 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

Knowledge Discovery in Biological Databases for Revealing Candidate Genes Linked to Complex Phenotypes.

PubMed

Hassani-Pak, Keywan; Rawlings, Christopher

2017-06-13

Genetics and "omics" studies designed to uncover genotype to phenotype relationships often identify large numbers of potential candidate genes, among which the causal genes are hidden. Scientists generally lack the time and technical expertise to review all relevant information available from the literature, from key model species and from a potentially wide range of related biological databases in a variety of data formats with variable quality and coverage. Computational tools are needed for the integration and evaluation of heterogeneous information in order to prioritise candidate genes and components of interaction networks that, if perturbed through potential interventions, have a positive impact on the biological outcome in the whole organism without producing negative side effects. Here we review several bioinformatics tools and databases that play an important role in biological knowledge discovery and candidate gene prioritization. We conclude with several key challenges that need to be addressed in order to facilitate biological knowledge discovery in the future.

Mouse Genome Database: From sequence to phenotypes and disease models

PubMed Central

Richardson, Joel E.; Kadin, James A.; Smith, Cynthia L.; Blake, Judith A.; Bult, Carol J.

2015-01-01

Summary The Mouse Genome Database (MGD, www.informatics.jax.org) is the international scientific database for genetic, genomic, and biological data on the laboratory mouse to support the research requirements of the biomedical community. To accomplish this goal, MGD provides broad data coverage, serves as the authoritative standard for mouse nomenclature for genes, mutants, and strains, and curates and integrates many types of data from literature and electronic sources. Among the key data sets MGD supports are: the complete catalog of mouse genes and genome features, comparative homology data for mouse and vertebrate genes, the authoritative set of Gene Ontology (GO) annotations for mouse gene functions, a comprehensive catalog of mouse mutations and their phenotypes, and a curated compendium of mouse models of human diseases. Here, we describe the data acquisition process, specifics about MGD's key data areas, methods to access and query MGD data, and outreach and user help facilities. genesis 53:458–473, 2015. © 2015 The Authors. Genesis Published by Wiley Periodicals, Inc. PMID:26150326

DEXTER: Disease-Expression Relation Extraction from Text.

PubMed

Gupta, Samir; Dingerdissen, Hayley; Ross, Karen E; Hu, Yu; Wu, Cathy H; Mazumder, Raja; Vijay-Shanker, K

2018-01-01

Gene expression levels affect biological processes and play a key role in many diseases. Characterizing expression profiles is useful for clinical research, and diagnostics and prognostics of diseases. There are currently several high-quality databases that capture gene expression information, obtained mostly from large-scale studies, such as microarray and next-generation sequencing technologies, in the context of disease. The scientific literature is another rich source of information on gene expression-disease relationships that not only have been captured from large-scale studies but have also been observed in thousands of small-scale studies. Expression information obtained from literature through manual curation can extend expression databases. While many of the existing databases include information from literature, they are limited by the time-consuming nature of manual curation and have difficulty keeping up with the explosion of publications in the biomedical field. In this work, we describe an automated text-mining tool, Disease-Expression Relation Extraction from Text (DEXTER) to extract information from literature on gene and microRNA expression in the context of disease. One of the motivations in developing DEXTER was to extend the BioXpress database, a cancer-focused gene expression database that includes data derived from large-scale experiments and manual curation of publications. The literature-based portion of BioXpress lags behind significantly compared to expression information obtained from large-scale studies and can benefit from our text-mined results. We have conducted two different evaluations to measure the accuracy of our text-mining tool and achieved average F-scores of 88.51 and 81.81% for the two evaluations, respectively. Also, to demonstrate the ability to extract rich expression information in different disease-related scenarios, we used DEXTER to extract information on differential expression information for 2024 genes in lung cancer, 115 glycosyltransferases in 62 cancers and 826 microRNA in 171 cancers. All extractions using DEXTER are integrated in the literature-based portion of BioXpress.Database URL: http://biotm.cis.udel.edu/DEXTER.

funRiceGenes dataset for comprehensive understanding and application of rice functional genes.

PubMed

Yao, Wen; Li, Guangwei; Yu, Yiming; Ouyang, Yidan

2018-01-01

As a main staple food, rice is also a model plant for functional genomic studies of monocots. Decoding of every DNA element of the rice genome is essential for genetic improvement to address increasing food demands. The past 15 years have witnessed extraordinary advances in rice functional genomics. Systematic characterization and proper deposition of every rice gene are vital for both functional studies and crop genetic improvement. We built a comprehensive and accurate dataset of ∼2800 functionally characterized rice genes and ∼5000 members of different gene families by integrating data from available databases and reviewing every publication on rice functional genomic studies. The dataset accounts for 19.2% of the 39 045 annotated protein-coding rice genes, which provides the most exhaustive archive for investigating the functions of rice genes. We also constructed 214 gene interaction networks based on 1841 connections between 1310 genes. The largest network with 762 genes indicated that pleiotropic genes linked different biological pathways. Increasing degree of conservation of the flowering pathway was observed among more closely related plants, implying substantial value of rice genes for future dissection of flowering regulation in other crops. All data are deposited in the funRiceGenes database (https://funricegenes.github.io/). Functionality for advanced search and continuous updating of the database are provided by a Shiny application (http://funricegenes.ncpgr.cn/). The funRiceGenes dataset would enable further exploring of the crosslink between gene functions and natural variations in rice, which can also facilitate breeding design to improve target agronomic traits of rice. © The Authors 2017. Published by Oxford University Press.

The Co-regulation Data Harvester: Automating gene annotation starting from a transcriptome database

NASA Astrophysics Data System (ADS)

Tsypin, Lev M.; Turkewitz, Aaron P.

Identifying co-regulated genes provides a useful approach for defining pathway-specific machinery in an organism. To be efficient, this approach relies on thorough genome annotation, a process much slower than genome sequencing per se. Tetrahymena thermophila, a unicellular eukaryote, has been a useful model organism and has a fully sequenced but sparsely annotated genome. One important resource for studying this organism has been an online transcriptomic database. We have developed an automated approach to gene annotation in the context of transcriptome data in T. thermophila, called the Co-regulation Data Harvester (CDH). Beginning with a gene of interest, the CDH identifies co-regulated genes by accessing the Tetrahymena transcriptome database. It then identifies their closely related genes (orthologs) in other organisms by using reciprocal BLAST searches. Finally, it collates the annotations of those orthologs' functions, which provides the user with information to help predict the cellular role of the initial query. The CDH, which is freely available, represents a powerful new tool for analyzing cell biological pathways in Tetrahymena. Moreover, to the extent that genes and pathways are conserved between organisms, the inferences obtained via the CDH should be relevant, and can be explored, in many other systems.

Investigation of mutations in the HBB gene using the 1,000 genomes database.

PubMed

Carlice-Dos-Reis, Tânia; Viana, Jaime; Moreira, Fabiano Cordeiro; Cardoso, Greice de Lemos; Guerreiro, João; Santos, Sidney; Ribeiro-Dos-Santos, Ândrea

2017-01-01

Mutations in the HBB gene are responsible for several serious hemoglobinopathies, such as sickle cell anemia and β-thalassemia. Sickle cell anemia is one of the most common monogenic diseases worldwide. Due to its prevalence, diverse strategies have been developed for a better understanding of its molecular mechanisms. In silico analysis has been increasingly used to investigate the genotype-phenotype relationship of many diseases, and the sequences of healthy individuals deposited in the 1,000 Genomes database appear to be an excellent tool for such analysis. The objective of this study is to analyze the variations in the HBB gene in the 1,000 Genomes database, to describe the mutation frequencies in the different population groups, and to investigate the pattern of pathogenicity. The computational tool SNPEFF was used to align the data from 2,504 samples of the 1,000 Genomes database with the HG19 genome reference. The pathogenicity of each amino acid change was investigated using the databases CLINVAR, dbSNP and HbVar and five different predictors. Twenty different mutations were found in 209 healthy individuals. The African group had the highest number of individuals with mutations, and the European group had the lowest number. Thus, it is concluded that approximately 8.3% of phenotypically healthy individuals from the 1,000 Genomes database have some mutation in the HBB gene. The frequency of mutated genes was estimated at 0.042, so that the expected frequency of being homozygous or compound heterozygous for these variants in the next generation is approximately 0.002. In total, 193 subjects had a non-synonymous mutation, which 186 (7.4%) have a deleterious mutation. Considering that the 1,000 Genomes database is representative of the world's population, it can be estimated that fourteen out of every 10,000 individuals in the world will have a hemoglobinopathy in the next generation.

Analysis of databases appropriation in the academic staffs of Iranian Universities of Medical Sciences according to the social appropriation approach.

PubMed

Keyvanara, Mahmoud; Sohrabi, Mozaffar Cheshmeh; Zare, Firoozeh; Hassnazadeh, Akbar; Malekahmadi, Parisa

2014-01-01

Numerous researches conducted on about the quality of perception of media messages shows that the people are not passive receivers but they have the ability of understanding, interpreting and accepting or rejecting messages. In order to make clear the relationship of information and communication technologies with social changes and to gain a broader vision from this scope, sociological theories about information and communication technologies' usage, especially appropriation approach can be very useful. So, keeping in mind the important role of Databases in the qualitative expansion of education, research, diagnosis, remedy and medical services presentation, this research was carried out with the aim of status determination of databases appropriation in the academic staffs of Iranian Universities of Medical Sciences according to the social appropriation approach in 2012. This is an applicative research of an analytical-descriptive type, which was carried out by measurement approach. The statistical society of this research was composed of the academic staffs of the Iranian Universities of Medical Sciences in 2012 and finally 390 academic staffs were selected according to the Cochran's formula were selected. The research tool are searcher's made questionnaire, which was composed of nine separate parts. Its validity was accepted by the specialists and its reliability was calculated and found to be 0.961 by Cronbakh's alpha. Database appropriation score in the academic staffs of Iranian Universities of Medical Sciences with 65.020% was in a good status and data bases dis appropriation score with 71.484 was in a high status. According to the findings of this research, Librarians and politicians in this scope-with determination of the academic staff's positive and negative points in usage and appropriation would be capable of accurately diagnozing and analyzing the chances and challenges of the academic staffs members in using databases and would also be capable of achieving solutions and appropriate catalyzers of prolific usage and appropriation of databases.

PLMItRNA, a database on the heterogeneous genetic origin of mitochondrial tRNA genes and tRNAs in photosynthetic eukaryotes.

PubMed

Rainaldi, Guglielmo; Volpicella, Mariateresa; Licciulli, Flavio; Liuni, Sabino; Gallerani, Raffaele; Ceci, Luigi R

2003-01-01

The updated version of PLMItRNA reports information and multialignments on 609 genes and 34 tRNA molecules active in the mitochondria of Viridiplantae (27 Embryophyta and 10 Chlorophyta), and photosynthetic algae (one Cryptophyta, four Rhodophyta and two Stramenopiles). Colour-code based tables reporting the different genetic origin of identified genes allow hyper-textual link to single entries. Promoter sequences identified for tRNA genes in the mitochondrial genomes of Angiospermae are also reported. The PLMItRNA database is accessible at http://bighost.area.ba.cnr.it/PLMItRNA/.

Post-genomics of microsporidia, with emphasis on a model of minimal eukaryotic proteome: a review.

PubMed

Texier, Catherine; Brosson, Damien; El Alaoui, Hicham; Méténier, Guy; Vivarès, Christian P

2005-05-01

The genome sequence of the microsporidian parasite Encephalitozoon cuniculi Levaditi, Nicolau et Schoen, 1923 contains about 2,000 genes that are representative of a non-redundant potential proteome composed of 1,909 protein chains. The purpose of this review is to relate some advances in the characterisation of this proteome through bioinformatics and experimental approaches. The reduced diversity of the set of E. cuniculi proteins is perceptible in all the compilations of predicted domains, orthologs, families and superfamilies, available in several public databases. The phyletic patterns of orthologs for seven eukaryotic organisms support an extensive gene loss in the fungal clade, with additional deletions in E. cuniculi. Most microsporidial orthologs are the smallest ones among eukaryotes, justifying an interest in the use of these compacted proteins to better discriminate between essential and non-essential regions. The three components of the E. cuniculi mRNA capping apparatus have been especially well characterized and the three-dimensional structure of the cap methyltransferase has been elucidated following the crystallisation of the microsporidial enzyme Ecm1. So far, our mass spectrometry-based analyses of the E. cuniculi spore proteome has led to the identification of about 170 proteins, one-quarter of these having no clearly predicted function. Immunocytochemical studies are in progress to determine the subcellular localisation of microsporidia-specific proteins. Post-translational modifications such as phosphorylation and glycosylation are expected to be soon explored.

WormQTLHD—a web database for linking human disease to natural variation data in C. elegans

PubMed Central

van der Velde, K. Joeri; de Haan, Mark; Zych, Konrad; Arends, Danny; Snoek, L. Basten; Kammenga, Jan E.; Jansen, Ritsert C.; Swertz, Morris A.; Li, Yang

2014-01-01

Interactions between proteins are highly conserved across species. As a result, the molecular basis of multiple diseases affecting humans can be studied in model organisms that offer many alternative experimental opportunities. One such organism—Caenorhabditis elegans—has been used to produce much molecular quantitative genetics and systems biology data over the past decade. We present WormQTLHD (Human Disease), a database that quantitatively and systematically links expression Quantitative Trait Loci (eQTL) findings in C. elegans to gene–disease associations in man. WormQTLHD, available online at http://www.wormqtl-hd.org, is a user-friendly set of tools to reveal functionally coherent, evolutionary conserved gene networks. These can be used to predict novel gene-to-gene associations and the functions of genes underlying the disease of interest. We created a new database that links C. elegans eQTL data sets to human diseases (34 337 gene–disease associations from OMIM, DGA, GWAS Central and NHGRI GWAS Catalogue) based on overlapping sets of orthologous genes associated to phenotypes in these two species. We utilized QTL results, high-throughput molecular phenotypes, classical phenotypes and genotype data covering different developmental stages and environments from WormQTL database. All software is available as open source, built on MOLGENIS and xQTL workbench. PMID:24217915

Genetic variants of the DNA repair genes from Exome Aggregation Consortium (EXAC) database: significance in cancer.

PubMed

Das, Raima; Ghosh, Sankar Kumar

2017-04-01

DNA repair pathway is a primary defense system that eliminates wide varieties of DNA damage. Any deficiencies in them are likely to cause the chromosomal instability that leads to cell malfunctioning and tumorigenesis. Genetic polymorphisms in DNA repair genes have demonstrated a significant association with cancer risk. Our study attempts to give a glimpse of the overall scenario of the germline polymorphisms in the DNA repair genes by taking into account of the Exome Aggregation Consortium (ExAC) database as well as the Human Gene Mutation Database (HGMD) for evaluating the disease link, particularly in cancer. It has been found that ExAC DNA repair dataset (which consists of 228 DNA repair genes) comprises 30.4% missense, 12.5% dbSNP reported and 3.2% ClinVar significant variants. 27% of all the missense variants has the deleterious SIFT score of 0.00 and 6% variants carrying the most damaging Polyphen-2 score of 1.00, thus affecting the protein structure and function. However, as per HGMD, only a fraction (1.2%) of ExAC DNA repair variants was found to be cancer-related, indicating remaining variants reported in both the databases to be further analyzed. This, in turn, may provide an increased spectrum of the reported cancer linked variants in the DNA repair genes present in ExAC database. Moreover, further in silico functional assay of the identified vital cancer-associated variants, which is essential to get their actual biological significance, may shed some lights in the field of targeted drug development in near future. Copyright © 2017. Published by Elsevier B.V.

A Bayesian taxonomic classification method for 16S rRNA gene sequences with improved species-level accuracy.

PubMed

Gao, Xiang; Lin, Huaiying; Revanna, Kashi; Dong, Qunfeng

2017-05-10

Species-level classification for 16S rRNA gene sequences remains a serious challenge for microbiome researchers, because existing taxonomic classification tools for 16S rRNA gene sequences either do not provide species-level classification, or their classification results are unreliable. The unreliable results are due to the limitations in the existing methods which either lack solid probabilistic-based criteria to evaluate the confidence of their taxonomic assignments, or use nucleotide k-mer frequency as the proxy for sequence similarity measurement. We have developed a method that shows significantly improved species-level classification results over existing methods. Our method calculates true sequence similarity between query sequences and database hits using pairwise sequence alignment. Taxonomic classifications are assigned from the species to the phylum levels based on the lowest common ancestors of multiple database hits for each query sequence, and further classification reliabilities are evaluated by bootstrap confidence scores. The novelty of our method is that the contribution of each database hit to the taxonomic assignment of the query sequence is weighted by a Bayesian posterior probability based upon the degree of sequence similarity of the database hit to the query sequence. Our method does not need any training datasets specific for different taxonomic groups. Instead only a reference database is required for aligning to the query sequences, making our method easily applicable for different regions of the 16S rRNA gene or other phylogenetic marker genes. Reliable species-level classification for 16S rRNA or other phylogenetic marker genes is critical for microbiome research. Our software shows significantly higher classification accuracy than the existing tools and we provide probabilistic-based confidence scores to evaluate the reliability of our taxonomic classification assignments based on multiple database matches to query sequences. Despite its higher computational costs, our method is still suitable for analyzing large-scale microbiome datasets for practical purposes. Furthermore, our method can be applied for taxonomic classification of any phylogenetic marker gene sequences. Our software, called BLCA, is freely available at https://github.com/qunfengdong/BLCA .

AbMiner: a bioinformatic resource on available monoclonal antibodies and corresponding gene identifiers for genomic, proteomic, and immunologic studies.

PubMed

Major, Sylvia M; Nishizuka, Satoshi; Morita, Daisaku; Rowland, Rick; Sunshine, Margot; Shankavaram, Uma; Washburn, Frank; Asin, Daniel; Kouros-Mehr, Hosein; Kane, David; Weinstein, John N

2006-04-06

Monoclonal antibodies are used extensively throughout the biomedical sciences for detection of antigens, either in vitro or in vivo. We, for example, have used them for quantitation of proteins on "reverse-phase" protein lysate arrays. For those studies, we quality-controlled > 600 available monoclonal antibodies and also needed to develop precise information on the genes that encode their antigens. Translation among the various protein and gene identifier types proved non-trivial because of one-to-many and many-to-one relationships. To organize the antibody, protein, and gene information, we initially developed a relational database in Filemaker for our own use. When it became apparent that the information would be useful to many other researchers faced with the need to choose or characterize antibodies, we developed it further as AbMiner, a fully relational web-based database under MySQL, programmed in Java. AbMiner is a user-friendly, web-based relational database of information on > 600 commercially available antibodies that we validated by Western blot for protein microarray studies. It includes many types of information on the antibody, the immunogen, the vendor, the antigen, and the antigen's gene. Multiple gene and protein identifier types provide links to corresponding entries in a variety of other public databases, including resources for phosphorylation-specific antibodies. AbMiner also includes our quality-control data against a pool of 60 diverse cancer cell types (the NCI-60) and also protein expression levels for the NCI-60 cells measured using our high-density "reverse-phase" protein lysate microarrays for a selection of the listed antibodies. Some other available database resources give information on antibody specificity for one or a couple of cell types. In contrast, the data in AbMiner indicate specificity with respect to the antigens in a pool of 60 diverse cell types from nine different tissues of origin. AbMiner is a relational database that provides extensive information from our own laboratory and other sources on more than 600 available antibodies and the genes that encode the antibodies' antigens. The data will be made freely available at http://discover.nci.nih.gov/abminer.

HEDD: Human Enhancer Disease Database

PubMed Central

Wang, Zhen; Zhang, Quanwei; Zhang, Wen; Lin, Jhih-Rong; Cai, Ying; Mitra, Joydeep

2018-01-01

Abstract Enhancers, as specialized genomic cis-regulatory elements, activate transcription of their target genes and play an important role in pathogenesis of many human complex diseases. Despite recent systematic identification of them in the human genome, currently there is an urgent need for comprehensive annotation databases of human enhancers with a focus on their disease connections. In response, we built the Human Enhancer Disease Database (HEDD) to facilitate studies of enhancers and their potential roles in human complex diseases. HEDD currently provides comprehensive genomic information for ∼2.8 million human enhancers identified by ENCODE, FANTOM5 and RoadMap with disease association scores based on enhancer–gene and gene–disease connections. It also provides Web-based analytical tools to visualize enhancer networks and score enhancers given a set of selected genes in a specific gene network. HEDD is freely accessible at http://zdzlab.einstein.yu.edu/1/hedd.php. PMID:29077884

Microplate-based platform for combined chromatin and DNA methylation immunoprecipitation assays

PubMed Central

2011-01-01

Background The processes that compose expression of a given gene are far more complex than previously thought presenting unprecedented conceptual and mechanistic challenges that require development of new tools. Chromatin structure, which is regulated by DNA methylation and histone modification, is at the center of gene regulation. Immunoprecipitations of chromatin (ChIP) and methylated DNA (MeDIP) represent a major achievement in this area that allow researchers to probe chromatin modifications as well as specific protein-DNA interactions in vivo and to estimate the density of proteins at specific sites genome-wide. Although a critical component of chromatin structure, DNA methylation has often been studied independently of other chromatin events and transcription. Results To allow simultaneous measurements of DNA methylation with other genomic processes, we developed and validated a simple and easy-to-use high throughput microplate-based platform for analysis of DNA methylation. Compared to the traditional beads-based MeDIP the microplate MeDIP was more sensitive and had lower non-specific binding. We integrated the MeDIP method with a microplate ChIP assay which allows measurements of both DNA methylation and histone marks at the same time, Matrix ChIP-MeDIP platform. We illustrated several applications of this platform to relate DNA methylation, with chromatin and transcription events at selected genes in cultured cells, human cancer and in a model of diabetic kidney disease. Conclusion The high throughput capacity of Matrix ChIP-MeDIP to profile tens and potentially hundreds of different genomic events at the same time as DNA methylation represents a powerful platform to explore complex genomic mechanism at selected genes in cultured cells and in whole tissues. In this regard, Matrix ChIP-MeDIP should be useful to complement genome-wide studies where the rich chromatin and transcription database resources provide fruitful foundation to pursue mechanistic, functional and diagnostic information at genes of interest in health and disease. PMID:22098709

Marfan Database (second edition): software and database for the analysis of mutations in the human FBN1 gene.

PubMed Central

Collod-Béroud, G; Béroud, C; Adès, L; Black, C; Boxer, M; Brock, D J; Godfrey, M; Hayward, C; Karttunen, L; Milewicz, D; Peltonen, L; Richards, R I; Wang, M; Junien, C; Boileau, C

1997-01-01

Fibrillin is the major component of extracellular microfibrils. Mutations in the fibrillin gene on chromosome 15 (FBN1) were described at first in the heritable connective tissue disorder, Marfan syndrome (MFS). More recently, FBN1 has also been shown to harbor mutations related to a spectrum of conditions phenotypically related to MFS. These mutations are private, essentially missense, generally non-recurrent and widely distributed throughout the gene. To date no clear genotype/phenotype relationship has been observed excepted for the localization of neonatal mutations in a cluster between exons 24 and 32. The second version of the computerized Marfan database contains 89 entries. The software has been modified to accomodate new functions and routines. PMID:9016526

[Genetic mutation databases: stakes and perspectives for orphan genetic diseases].

PubMed

Humbertclaude, V; Tuffery-Giraud, S; Bareil, C; Thèze, C; Paulet, D; Desmet, F-O; Hamroun, D; Baux, D; Girardet, A; Collod-Béroud, G; Khau Van Kien, P; Roux, A-F; des Georges, M; Béroud, C; Claustres, M

2010-10-01

New technologies, which constantly become available for mutation detection and gene analysis, have contributed to an exponential rate of discovery of disease genes and variation in the human genome. The task of collecting and documenting this enormous amount of data in genetic databases represents a major challenge for the future of biological and medical science. The Locus Specific Databases (LSDBs) are so far the most efficient mutation databases. This review presents the main types of databases available for the analysis of mutations responsible for genetic disorders, as well as open perspectives for new therapeutic research or challenges for future medicine. Accurate and exhaustive collection of variations in human genomes will be crucial for research and personalized delivery of healthcare. Copyright © 2009 Elsevier Masson SAS. All rights reserved.

Cloning and Sequence Analysis of Vibrio halioticoli Genes Encoding Three Types of Polyguluronate Lyase.

PubMed

Sugimura; Sawabe; Ezura

2000-01-01

The alginate lyase-coding genes of Vibrio halioticoli IAM 14596(T), which was isolated from the gut of the abalone Haliotis discus hannai, were cloned using plasmid vector pUC 18, and expressed in Escherichia coli. Three alginate lyase-positive clones, pVHB, pVHC, and pVHE, were obtained, and all clones expressed the enzyme activity specific for polyguluronate. Three genes, alyVG1, alyVG2, and alyVG3, encoding polyguluronate lyase were sequenced: alyVG1 from pVHB was composed of a 1056-bp open reading frame (ORF) encoding 352 amino acid residues; alyVG2 gene from pVHC was composed of a 993-bp ORF encoding 331 amino acid residues; and alyVG3 gene from pVHE was composed of a 705-bp ORF encoding 235 amino acid residues. Comparison of nucleotide and deduced amino acid sequences among AlyVG1, AlyVG2, and AlyVG3 revealed low homologies. The identity value between AlyVG1 and AlyVG2 was 18.7%, and that between AlyVG2 and AlyVG3 was 17.0%. A higher identity value (26.0%) was observed between AlyVG1 and AlyVG3. Sequence comparison among known polyguluronate lyases including AlyVG1, AlyVG2, and AlyVG3 also did not reveal an identical region in these sequences. However, AlyVG1 showed the highest identity value (36.2%) and the highest similarity (73.3%) to AlyA from Klebsiella pneumoniae. A consensus region comprising nine amino acid (YFKAGXYXQ) in the carboxy-terminal region previously reported by Mallisard and colleagues was observed only in AlyVG1 and AlyVG2.

Distributional fold change test – a statistical approach for detecting differential expression in microarray experiments

PubMed Central

2012-01-01

Background Because of the large volume of data and the intrinsic variation of data intensity observed in microarray experiments, different statistical methods have been used to systematically extract biological information and to quantify the associated uncertainty. The simplest method to identify differentially expressed genes is to evaluate the ratio of average intensities in two different conditions and consider all genes that differ by more than an arbitrary cut-off value to be differentially expressed. This filtering approach is not a statistical test and there is no associated value that can indicate the level of confidence in the designation of genes as differentially expressed or not differentially expressed. At the same time the fold change by itself provide valuable information and it is important to find unambiguous ways of using this information in expression data treatment. Results A new method of finding differentially expressed genes, called distributional fold change (DFC) test is introduced. The method is based on an analysis of the intensity distribution of all microarray probe sets mapped to a three dimensional feature space composed of average expression level, average difference of gene expression and total variance. The proposed method allows one to rank each feature based on the signal-to-noise ratio and to ascertain for each feature the confidence level and power for being differentially expressed. The performance of the new method was evaluated using the total and partial area under receiver operating curves and tested on 11 data sets from Gene Omnibus Database with independently verified differentially expressed genes and compared with the t-test and shrinkage t-test. Overall the DFC test performed the best – on average it had higher sensitivity and partial AUC and its elevation was most prominent in the low range of differentially expressed features, typical for formalin-fixed paraffin-embedded sample sets. Conclusions The distributional fold change test is an effective method for finding and ranking differentially expressed probesets on microarrays. The application of this test is advantageous to data sets using formalin-fixed paraffin-embedded samples or other systems where degradation effects diminish the applicability of correlation adjusted methods to the whole feature set. PMID:23122055

Elicitors and defense gene induction in plants with altered lignin compositions.

PubMed

Gallego-Giraldo, Lina; Posé, Sara; Pattathil, Sivakumar; Peralta, Angelo Gabriel; Hahn, Michael G; Ayre, Brian G; Sunuwar, Janak; Hernandez, Jonathan; Patel, Monika; Shah, Jyoti; Rao, Xiaolan; Knox, J Paul; Dixon, Richard A

2018-06-27

A reduction in the lignin content in transgenic plants induces the ectopic expression of defense genes, but the importance of altered lignin composition in such phenomena remains unclear. Two Arabidopsis lines with similar lignin contents, but strikingly different lignin compositions, exhibited different quantitative and qualitative transcriptional responses. Plants with lignin composed primarily of guaiacyl units overexpressed genes responsive to oomycete and bacterial pathogen attack, whereas plants with lignin composed primarily of syringyl units expressed a far greater number of defense genes, including some associated with cis-jasmone-mediated responses to aphids; these plants exhibited altered responsiveness to bacterial and aphid inoculation. Several of the defense genes were differentially induced by water-soluble extracts from cell walls of plants of the two lines. Glycome profiling, fractionation and enzymatic digestion studies indicated that the different lignin compositions led to differential extractability of a range of heterogeneous oligosaccharide epitopes, with elicitor activity originating from different cell wall polymers. Alteration of lignin composition affects interactions with plant cell wall matrix polysaccharides to alter the sequestration of multiple latent defense signal molecules with an impact on biotic stress responses. © 2018 The Authors. New Phytologist © 2018 New Phytologist Trust.

EUCANEXT: an integrated database for the exploration of genomic and transcriptomic data from Eucalyptus species

PubMed Central

Nascimento, Leandro Costa; Salazar, Marcela Mendes; Lepikson-Neto, Jorge; Camargo, Eduardo Leal Oliveira; Parreiras, Lucas Salera; Carazzolle, Marcelo Falsarella

2017-01-01

Abstract Tree species of the genus Eucalyptus are the most valuable and widely planted hardwoods in the world. Given the economic importance of Eucalyptus trees, much effort has been made towards the generation of specimens with superior forestry properties that can deliver high-quality feedstocks, customized to the industrýs needs for both cellulosic (paper) and lignocellulosic biomass production. In line with these efforts, large sets of molecular data have been generated by several scientific groups, providing invaluable information that can be applied in the development of improved specimens. In order to fully explore the potential of available datasets, the development of a public database that provides integrated access to genomic and transcriptomic data from Eucalyptus is needed. EUCANEXT is a database that analyses and integrates publicly available Eucalyptus molecular data, such as the E. grandis genome assembly and predicted genes, ESTs from several species and digital gene expression from 26 RNA-Seq libraries. The database has been implemented in a Fedora Linux machine running MySQL and Apache, while Perl CGI was used for the web interfaces. EUCANEXT provides a user-friendly web interface for easy access and analysis of publicly available molecular data from Eucalyptus species. This integrated database allows for complex searches by gene name, keyword or sequence similarity and is publicly accessible at http://www.lge.ibi.unicamp.br/eucalyptusdb. Through EUCANEXT, users can perform complex analysis to identify genes related traits of interest using RNA-Seq libraries and tools for differential expression analysis. Moreover, all the bioinformatics pipeline here described, including the database schema and PERL scripts, are readily available and can be applied to any genomic and transcriptomic project, regardless of the organism. Database URL: http://www.lge.ibi.unicamp.br/eucalyptusdb PMID:29220468

Xanthine urolithiasis in a cat: a case report and evaluation of a candidate gene for xanthine dehydrogenase.

PubMed

Tsuchida, Shuichi; Kagi, Akiko; Koyama, Hidekazu; Tagawa, Masahiro

2007-12-01

Xanthine urolithiasis was found in a 4-year-old spayed female Himalayan cat with a 10-month history of intermittent haematuria and dysuria. Ultrasonographs indicated the existence of several calculi in the bladder that were undetectable by survey radiographic examination. Four bladder stones were removed by cystotomy. The stones were spherical brownish-yellow and their surface was smooth and glossy. Quantitative mineral analysis showed a representative urolith to be composed of more than 95% xanthine. Ultrasonographic examination of the bladder 4.5 months postoperatively indicated the recurrence of urolithiasis. Analysis of purine concentration in urine and blood showed that the cat excreted excessive amounts of xanthine. In order to test the hypothesis that xanthinuria was caused by a homozygote of the inherited mutant allele of a gene responsible for deficiency of enzyme activity in purine degradation pathway, the allele composition of xanthine dehydrogenase (XDH) gene (one of the candidate genes for hereditary xanthinuria) was evaluated. The cat with xanthinuria was a heterozygote of the polymorphism. A single nucleotide polymorphism analysis of the cat XDH gene strongly indicated that the XDH gene of the patient cat was composed of two kinds of alleles and ruled out the hypothesis that the cat inherited the same recessive XDH allele suggesting no activity from a single ancestor.

Inferring gene and protein interactions using PubMed citations and consensus Bayesian networks

PubMed Central

Dalman, Mark; Haddad, Joseph; Duan, Zhong-Hui

2017-01-01

The PubMed database offers an extensive set of publication data that can be useful, yet inherently complex to use without automated computational techniques. Data repositories such as the Genomic Data Commons (GDC) and the Gene Expression Omnibus (GEO) offer experimental data storage and retrieval as well as curated gene expression profiles. Genetic interaction databases, including Reactome and Ingenuity Pathway Analysis, offer pathway and experiment data analysis using data curated from these publications and data repositories. We have created a method to generate and analyze consensus networks, inferring potential gene interactions, using large numbers of Bayesian networks generated by data mining publications in the PubMed database. Through the concept of network resolution, these consensus networks can be tailored to represent possible genetic interactions. We designed a set of experiments to confirm that our method is stable across variation in both sample and topological input sizes. Using gene product interactions from the KEGG pathway database and data mining PubMed publication abstracts, we verify that regardless of the network resolution or the inferred consensus network, our method is capable of inferring meaningful gene interactions through consensus Bayesian network generation with multiple, randomized topological orderings. Our method can not only confirm the existence of currently accepted interactions, but has the potential to hypothesize new ones as well. We show our method confirms the existence of known gene interactions such as JAK-STAT-PI3K-AKT-mTOR, infers novel gene interactions such as RAS- Bcl-2 and RAS-AKT, and found significant pathway-pathway interactions between the JAK-STAT signaling and Cardiac Muscle Contraction KEGG pathways. PMID:29049295

Clinical value of miR-182-5p in lung squamous cell carcinoma: a study combining data from TCGA, GEO, and RT-qPCR validation.

PubMed

Luo, Jie; Shi, Ke; Yin, Shu-Ya; Tang, Rui-Xue; Chen, Wen-Jie; Huang, Lin-Zhen; Gan, Ting-Qing; Cai, Zheng-Wen; Chen, Gang

2018-04-10

MiR-182-5p, as a member of miRNA family, can be detected in lung cancer and plays an important role in lung cancer. To explore the clinical value of miR-182-5p in lung squamous cell carcinoma (LUSC) and to unveil the molecular mechanism of LUSC. The clinical value of miR-182-5p in LUSC was investigated by collecting and calculating data from The Cancer Genome Atlas (TCGA) database, the Gene Expression Omnibus (GEO) database, and real-time quantitative polymerase chain reaction (RT-qPCR). Twelve prediction platforms were used to predict the target genes of miR-182-5p. Protein-protein interaction (PPI) networks and gene ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were used to explore the molecular mechanism of LUSC. The expression of miR-182-5p was significantly over-expressed in LUSC than in non-cancerous tissues, as evidenced by various approaches, including the TCGA database, GEO microarrays, RT-qPCR, and a comprehensive meta-analysis of 501 LUSC cases and 148 non-cancerous cases. Furthermore, a total of 81 potential target genes were chosen from the union of predicted genes and the TCGA database. GO and KEGG analyses demonstrated that the target genes are involved in pathways related to biological processes. PPIs revealed the relationships between these genes, with EPAS1, PRKCE, NR3C1, and RHOB being located in the center of the PPI network. MiR-182-5p upregulation greatly contributes to LUSC and may serve as a biomarker in LUSC.

Genes2Networks: connecting lists of gene symbols using mammalian protein interactions databases.

PubMed

Berger, Seth I; Posner, Jeremy M; Ma'ayan, Avi

2007-10-04

In recent years, mammalian protein-protein interaction network databases have been developed. The interactions in these databases are either extracted manually from low-throughput experimental biomedical research literature, extracted automatically from literature using techniques such as natural language processing (NLP), generated experimentally using high-throughput methods such as yeast-2-hybrid screens, or interactions are predicted using an assortment of computational approaches. Genes or proteins identified as significantly changing in proteomic experiments, or identified as susceptibility disease genes in genomic studies, can be placed in the context of protein interaction networks in order to assign these genes and proteins to pathways and protein complexes. Genes2Networks is a software system that integrates the content of ten mammalian interaction network datasets. Filtering techniques to prune low-confidence interactions were implemented. Genes2Networks is delivered as a web-based service using AJAX. The system can be used to extract relevant subnetworks created from "seed" lists of human Entrez gene symbols. The output includes a dynamic linkable three color web-based network map, with a statistical analysis report that identifies significant intermediate nodes used to connect the seed list. Genes2Networks is powerful web-based software that can help experimental biologists to interpret lists of genes and proteins such as those commonly produced through genomic and proteomic experiments, as well as lists of genes and proteins associated with disease processes. This system can be used to find relationships between genes and proteins from seed lists, and predict additional genes or proteins that may play key roles in common pathways or protein complexes.

Recommendations for Locus-Specific Databases and Their Curation

PubMed Central

Cotton, R.G.H.; Auerbach, A.D.; Beckmann, J.S.; Blumenfeld, O.O.; Brookes, A.J.; Brown, A.F.; Carrera, P.; Cox, D.W.; Gottlieb, B.; Greenblatt, M.S.; Hilbert, P.; Lehvaslaiho, H.; Liang, P.; Marsh, S.; Nebert, D.W.; Povey, S.; Rossetti, S.; Scriver, C.R.; Summar, M.; Tolan, D.R.; Verma, I.C.; Vihinen, M.; den Dunnen, J.T.

2009-01-01

Expert curation and complete collection of mutations in genes that affect human health is essential for proper genetic healthcare and research. Expert curation is given by the curators of gene-specific mutation databases or locus-specific databases (LSDBs). While there are over 700 such databases, they vary in their content, completeness, time available for curation, and the expertise of the curator. Curation and LSDBs have been discussed, written about, and protocols have been provided for over 10 years, but there have been no formal recommendations for the ideal form of these entities. This work initiates a discussion on this topic to assist future efforts in human genetics. Further discussion is welcome. PMID:18157828

Recommendations for locus-specific databases and their curation.

PubMed

Cotton, R G H; Auerbach, A D; Beckmann, J S; Blumenfeld, O O; Brookes, A J; Brown, A F; Carrera, P; Cox, D W; Gottlieb, B; Greenblatt, M S; Hilbert, P; Lehvaslaiho, H; Liang, P; Marsh, S; Nebert, D W; Povey, S; Rossetti, S; Scriver, C R; Summar, M; Tolan, D R; Verma, I C; Vihinen, M; den Dunnen, J T

2008-01-01

Expert curation and complete collection of mutations in genes that affect human health is essential for proper genetic healthcare and research. Expert curation is given by the curators of gene-specific mutation databases or locus-specific databases (LSDBs). While there are over 700 such databases, they vary in their content, completeness, time available for curation, and the expertise of the curator. Curation and LSDBs have been discussed, written about, and protocols have been provided for over 10 years, but there have been no formal recommendations for the ideal form of these entities. This work initiates a discussion on this topic to assist future efforts in human genetics. Further discussion is welcome. (c) 2007 Wiley-Liss, Inc.

PlantTribes: a gene and gene family resource for comparative genomics in plants

PubMed Central

Wall, P. Kerr; Leebens-Mack, Jim; Müller, Kai F.; Field, Dawn; Altman, Naomi S.; dePamphilis, Claude W.

2008-01-01

The PlantTribes database (http://fgp.huck.psu.edu/tribe.html) is a plant gene family database based on the inferred proteomes of five sequenced plant species: Arabidopsis thaliana, Carica papaya, Medicago truncatula, Oryza sativa and Populus trichocarpa. We used the graph-based clustering algorithm MCL [Van Dongen (Technical Report INS-R0010 2000) and Enright et al. (Nucleic Acids Res. 2002; 30: 1575–1584)] to classify all of these species’ protein-coding genes into putative gene families, called tribes, using three clustering stringencies (low, medium and high). For all tribes, we have generated protein and DNA alignments and maximum-likelihood phylogenetic trees. A parallel database of microarray experimental results is linked to the genes, which lets researchers identify groups of related genes and their expression patterns. Unified nomenclatures were developed, and tribes can be related to traditional gene families and conserved domain identifiers. SuperTribes, constructed through a second iteration of MCL clustering, connect distant, but potentially related gene clusters. The global classification of nearly 200 000 plant proteins was used as a scaffold for sorting ∼4 million additional cDNA sequences from over 200 plant species. All data and analyses are accessible through a flexible interface allowing users to explore the classification, to place query sequences within the classification, and to download results for further study. PMID:18073194

RiceMetaSys for salt and drought stress responsive genes in rice: a web interface for crop improvement.

PubMed

Sandhu, Maninder; Sureshkumar, V; Prakash, Chandra; Dixit, Rekha; Solanke, Amolkumar U; Sharma, Tilak Raj; Mohapatra, Trilochan; S V, Amitha Mithra

2017-09-30

Genome-wide microarray has enabled development of robust databases for functional genomics studies in rice. However, such databases do not directly cater to the needs of breeders. Here, we have attempted to develop a web interface which combines the information from functional genomic studies across different genetic backgrounds with DNA markers so that they can be readily deployed in crop improvement. In the current version of the database, we have included drought and salinity stress studies since these two are the major abiotic stresses in rice. RiceMetaSys, a user-friendly and freely available web interface provides comprehensive information on salt responsive genes (SRGs) and drought responsive genes (DRGs) across genotypes, crop development stages and tissues, identified from multiple microarray datasets. 'Physical position search' is an attractive tool for those using QTL based approach for dissecting tolerance to salt and drought stress since it can provide the list of SRGs and DRGs in any physical interval. To identify robust candidate genes for use in crop improvement, the 'common genes across varieties' search tool is useful. Graphical visualization of expression profiles across genes and rice genotypes has been enabled to facilitate the user and to make the comparisons more impactful. Simple Sequence Repeat (SSR) search in the SRGs and DRGs is a valuable tool for fine mapping and marker assisted selection since it provides primers for survey of polymorphism. An external link to intron specific markers is also provided for this purpose. Bulk retrieval of data without any limit has been enabled in case of locus and SSR search. The aim of this database is to facilitate users with a simple and straight-forward search options for identification of robust candidate genes from among thousands of SRGs and DRGs so as to facilitate linking variation in expression profiles to variation in phenotype. Database URL: http://14.139.229.201.

Draft Genome Sequence of Mycobacterium triplex DSM 44626.

PubMed

Sassi, Mohamed; Croce, Olivier; Robert, Catherine; Raoult, Didier; Drancourt, Michel

2014-05-29

We announce the draft genome sequence of Mycobacterium triplex strain DSM 44626, a nontuberculosis species responsible for opportunistic infections. The genome described here is composed of 6,382,840 bp, with a G+C content of 66.57%, and contains 5,988 protein-coding genes and 81 RNA genes. Copyright © 2014 Sassi et al.

Combinatorial peptide libraries and biometric score matrices permit the quantitative analysis of specific and degenerate interactions between clonotypic TCR and MHC peptide ligands.

PubMed

Zhao, Y; Gran, B; Pinilla, C; Markovic-Plese, S; Hemmer, B; Tzou, A; Whitney, L W; Biddison, W E; Martin, R; Simon, R

2001-08-15

The interaction of TCRs with MHC peptide ligands can be highly flexible, so that many different peptides are recognized by the same TCR in the context of a single restriction element. We provide a quantitative description of such interactions, which allows the identification of T cell epitopes and molecular mimics. The response of T cell clones to positional scanning synthetic combinatorial libraries is analyzed with a mathematical approach that is based on a model of independent contribution of individual amino acids to peptide Ag recognition. This biometric analysis compares the information derived from these libraries composed of trillions of decapeptides with all the millions of decapeptides contained in a protein database to rank and predict the most stimulatory peptides for a given T cell clone. We demonstrate the predictive power of the novel strategy and show that, together with gene expression profiling by cDNA microarrays, it leads to the identification of novel candidate autoantigens in the inflammatory autoimmune disease, multiple sclerosis.

The Human Ageing Genomic Resources: online databases and tools for biogerontologists

PubMed Central

de Magalhães, João Pedro; Budovsky, Arie; Lehmann, Gilad; Costa, Joana; Li, Yang; Fraifeld, Vadim; Church, George M.

2009-01-01

Summary Ageing is a complex, challenging phenomenon that will require multiple, interdisciplinary approaches to unravel its puzzles. To assist basic research on ageing, we developed the Human Ageing Genomic Resources (HAGR). This work provides an overview of the databases and tools in HAGR and describes how the gerontology research community can employ them. Several recent changes and improvements to HAGR are also presented. The two centrepieces in HAGR are GenAge and AnAge. GenAge is a gene database featuring genes associated with ageing and longevity in model organisms, a curated database of genes potentially associated with human ageing, and a list of genes tested for their association with human longevity. A myriad of biological data and information is included for hundreds of genes, making GenAge a reference for research that reflects our current understanding of the genetic basis of ageing. GenAge can also serve as a platform for the systems biology of ageing, and tools for the visualization of protein-protein interactions are also included. AnAge is a database of ageing in animals, featuring over 4,000 species, primarily assembled as a resource for comparative and evolutionary studies of ageing. Longevity records, developmental and reproductive traits, taxonomic information, basic metabolic characteristics, and key observations related to ageing are included in AnAge. Software is also available to aid researchers in the form of Perl modules to automate numerous tasks and as an SPSS script to analyse demographic mortality data. The Human Ageing Genomic Resources are available online at http://genomics.senescence.info. PMID:18986374

Literature and patent analysis of the cloning and identification of human functional genes in China.

PubMed

Xia, Yan; Tang, LiSha; Yao, Lei; Wan, Bo; Yang, XianMei; Yu, Long

2012-03-01

The Human Genome Project was launched at the end of the 1980s. Since then, the cloning and identification of functional genes has been a major focus of research across the world. In China too, the potentially profound impact of such studies on the life sciences and on human health was realized, and relevant studies were initiated in the 1990s. To advance China's involvement in the Human Genome Project, in the mid-1990s, Committee of Experts in Biology from National High Technology Research and Development Program of China (863 Program) proposed the "two 1%" goal. This goal envisaged China contributing 1% of the total sequencing work, and cloning and identifying 1% of the total human functional genes. Over the past 20 years, tremendous achievement has been accomplished by Chinese scientists. It is well known that scientists in China finished the 1% of sequencing work of the Human Genome Project, whereas, there is no comprehensive report about "whether China had finished cloning and identifying 1% of human functional genes". In the present study, the GenBank database at the National Center of Biotechnology Information, the PubMed search tool, and the patent database of the State Intellectual Property Office, China, were used to retrieve entries based on two screening standards: (i) Were the newly cloned and identified genes first reported by Chinese scientists? (ii) Were the Chinese scientists awarded the gene sequence patent? Entries were retrieved from the databases up to the cut-off date of 30 June 2011 and the obtained data were analyzed further. The results showed that 589 new human functional genes were first reported by Chinese scientists and 159 gene sequences were patented (http://gene.fudan.sh.cn/introduction/database/chinagene/chinagene.html). This study systematically summarizes China's contributions to human functional genomics research and answers the question "has China finished cloning and identifying 1% of human functional genes?" in the affirmative.

Candidate gene database and transcript map for peach, a model species for fruit trees.

PubMed

Horn, Renate; Lecouls, Anne-Claire; Callahan, Ann; Dandekar, Abhaya; Garay, Lilibeth; McCord, Per; Howad, Werner; Chan, Helen; Verde, Ignazio; Main, Doreen; Jung, Sook; Georgi, Laura; Forrest, Sam; Mook, Jennifer; Zhebentyayeva, Tatyana; Yu, Yeisoo; Kim, Hye Ran; Jesudurai, Christopher; Sosinski, Bryon; Arús, Pere; Baird, Vance; Parfitt, Dan; Reighard, Gregory; Scorza, Ralph; Tomkins, Jeffrey; Wing, Rod; Abbott, Albert Glenn

2005-05-01

Peach (Prunus persica) is a model species for the Rosaceae, which includes a number of economically important fruit tree species. To develop an extensive Prunus expressed sequence tag (EST) database for identifying and cloning the genes important to fruit and tree development, we generated 9,984 high-quality ESTs from a peach cDNA library of developing fruit mesocarp. After assembly and annotation, a putative peach unigene set consisting of 3,842 ESTs was defined. Gene ontology (GO) classification was assigned based on the annotation of the single "best hit" match against the Swiss-Prot database. No significant homology could be found in the GenBank nr databases for 24.3% of the sequences. Using core markers from the general Prunus genetic map, we anchored bacterial artificial chromosome (BAC) clones on the genetic map, thereby providing a framework for the construction of a physical and transcript map. A transcript map was developed by hybridizing 1,236 ESTs from the putative peach unigene set and an additional 68 peach cDNA clones against the peach BAC library. Hybridizing ESTs to genetically anchored BACs immediately localized 11.2% of the ESTs on the genetic map. ESTs showed a clustering of expressed genes in defined regions of the linkage groups. [The data were built into a regularly updated Genome Database for Rosaceae (GDR), available at (http://www.genome.clemson.edu/gdr/).].

From 20th century metabolic wall charts to 21st century systems biology: database of mammalian metabolic enzymes

PubMed Central

Corcoran, Callan C.; Grady, Cameron R.; Pisitkun, Trairak; Parulekar, Jaya

2017-01-01

The organization of the mammalian genome into gene subsets corresponding to specific functional classes has provided key tools for systems biology research. Here, we have created a web-accessible resource called the Mammalian Metabolic Enzyme Database (https://hpcwebapps.cit.nih.gov/ESBL/Database/MetabolicEnzymes/MetabolicEnzymeDatabase.html) keyed to the biochemical reactions represented on iconic metabolic pathway wall charts created in the previous century. Overall, we have mapped 1,647 genes to these pathways, representing ~7 percent of the protein-coding genome. To illustrate the use of the database, we apply it to the area of kidney physiology. In so doing, we have created an additional database (Database of Metabolic Enzymes in Kidney Tubule Segments: https://hpcwebapps.cit.nih.gov/ESBL/Database/MetabolicEnzymes/), mapping mRNA abundance measurements (mined from RNA-Seq studies) for all metabolic enzymes to each of 14 renal tubule segments. We carry out bioinformatics analysis of the enzyme expression pattern among renal tubule segments and mine various data sources to identify vasopressin-regulated metabolic enzymes in the renal collecting duct. PMID:27974320

GMDD: a database of GMO detection methods

PubMed Central

Dong, Wei; Yang, Litao; Shen, Kailin; Kim, Banghyun; Kleter, Gijs A; Marvin, Hans JP; Guo, Rong; Liang, Wanqi; Zhang, Dabing

2008-01-01

Background Since more than one hundred events of genetically modified organisms (GMOs) have been developed and approved for commercialization in global area, the GMO analysis methods are essential for the enforcement of GMO labelling regulations. Protein and nucleic acid-based detection techniques have been developed and utilized for GMOs identification and quantification. However, the information for harmonization and standardization of GMO analysis methods at global level is needed. Results GMO Detection method Database (GMDD) has collected almost all the previous developed and reported GMOs detection methods, which have been grouped by different strategies (screen-, gene-, construct-, and event-specific), and also provide a user-friendly search service of the detection methods by GMO event name, exogenous gene, or protein information, etc. In this database, users can obtain the sequences of exogenous integration, which will facilitate PCR primers and probes design. Also the information on endogenous genes, certified reference materials, reference molecules, and the validation status of developed methods is included in this database. Furthermore, registered users can also submit new detection methods and sequences to this database, and the newly submitted information will be released soon after being checked. Conclusion GMDD contains comprehensive information of GMO detection methods. The database will make the GMOs analysis much easier. PMID:18522755

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Yanfeng; Zheng, Yi; Qin, Ling

Beta-hydroxyacid dehydrogenase (β-HAD) genes have been identified in all sequenced genomes of eukaryotes and prokaryotes. Their gene products catalyze the NAD+- or NADP+-dependent oxidation of various β-hydroxy acid substrates into their corresponding semialdehyde. In many fungal and bacterial genomes, multiple β-HAD genes are observed leading to the hypothesis that these gene products may have unique, uncharacterized metabolic roles specific to their species. The genomes of Geobacter sulfurreducens and Geobacter metallireducens each contain two potential β-HAD genes. The protein sequences of one pair of these genes, Gs-βHAD (Q74DE4) and Gm-βHAD (Q39R98), have 65% sequence identity and 77% sequence similarity with eachmore » other. Both proteins reduce succinic semialdehyde, a metabolite of the GABA shunt. To further explore the structural and functional characteristics of these two β-HADs with a potentially unique substrate specificity, crystal structures for Gs-βHAD and Gm-βHAD in complex with NADP+ were determined to a resolution of 1.89 Å and 2.07 Å, respectively. The structure of both proteins are similar, composed of 14 α-helices and nine β-strands organized into two domains. Domain One (1-165) adopts a typical Rossmann fold composed of two α/β units: a six-strand parallel β-sheet surrounded by six α-helices (α1 – α6) followed by a mixed three-strand β-sheet surrounded by two α-helices (α7 and α8). Domain Two (166-287) is composed of a bundle of seven α-helices (α9 – α14). Four functional regions conserved in all β-HADs are spatially located near each other at the interdomain cleft in both Gs-βHAD and Gm-βHAD with a buried molecule of NADP+. The structural features of Gs-βHAD and Gm-βHAD are described in relation to the four conserved consensus sequences characteristic of β-HADs and the potential biochemical importance of these enzymes as an alternative pathway for the degradation of succinic semialdehyde.« less

Ribosomal DNA stability is supported by many 'buffer genes'-introduction to the Yeast rDNA Stability Database.

PubMed

Kobayashi, Takehiko; Sasaki, Mariko

2017-01-01

The ribosomal RNA gene (rDNA) is the most abundant gene in yeast and other eukaryotic organisms. Due to its heavy transcription, repetitive structure and programmed replication fork pauses, the rDNA is one of the most unstable regions in the genome. Thus, the rDNA is the best region to study the mechanisms responsible for maintaining genome integrity. Recently, we screened a library of ∼4800 budding yeast gene knockout strains to identify mutants defective in the maintenance of rDNA stability. The results of this screen are summarized in the Yeast rDNA Stability (YRS) Database, in which the stability and copy number of rDNA in each mutant are presented. From this screen, we identified ∼700 genes that may contribute to the maintenance of rDNA stability. In addition, ∼50 mutants had abnormally high or low rDNA copy numbers. Moreover, some mutants with unstable rDNA displayed abnormalities in another chromosome. In this review, we introduce the YRS Database and discuss the roles of newly identified genes that contribute to rDNA maintenance and genome integrity. © FEMS 2017. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

UniVIO: A Multiple Omics Database with Hormonome and Transcriptome Data from Rice

PubMed Central

Sakurai, Tetsuya; Sakakibara, Hitoshi

2013-01-01

Plant hormones play important roles as signaling molecules in the regulation of growth and development by controlling the expression of downstream genes. Since the hormone signaling system represents a complex network involving functional cross-talk through the mutual regulation of signaling and metabolism, a comprehensive and integrative analysis of plant hormone concentrations and gene expression is important for a deeper understanding of hormone actions. We have developed a database named Uniformed Viewer for Integrated Omics (UniVIO: http://univio.psc.riken.jp/), which displays hormone-metabolome (hormonome) and transcriptome data in a single formatted (uniformed) heat map. At the present time, hormonome and transcriptome data obtained from 14 organ parts of rice plants at the reproductive stage and seedling shoots of three gibberellin signaling mutants are included in the database. The hormone concentration and gene expression data can be searched by substance name, probe ID, gene locus ID or gene description. A correlation search function has been implemented to enable users to obtain information of correlated substance accumulation and gene expression. In the correlation search, calculation method, range of correlation coefficient and plant samples can be selected freely. PMID:23314752

CoryneRegNet 4.0 – A reference database for corynebacterial gene regulatory networks

PubMed Central

Baumbach, Jan

2007-01-01

Background Detailed information on DNA-binding transcription factors (the key players in the regulation of gene expression) and on transcriptional regulatory interactions of microorganisms deduced from literature-derived knowledge, computer predictions and global DNA microarray hybridization experiments, has opened the way for the genome-wide analysis of transcriptional regulatory networks. The large-scale reconstruction of these networks allows the in silico analysis of cell behavior in response to changing environmental conditions. We previously published CoryneRegNet, an ontology-based data warehouse of corynebacterial transcription factors and regulatory networks. Initially, it was designed to provide methods for the analysis and visualization of the gene regulatory network of Corynebacterium glutamicum. Results Now we introduce CoryneRegNet release 4.0, which integrates data on the gene regulatory networks of 4 corynebacteria, 2 mycobacteria and the model organism Escherichia coli K12. As the previous versions, CoryneRegNet provides a web-based user interface to access the database content, to allow various queries, and to support the reconstruction, analysis and visualization of regulatory networks at different hierarchical levels. In this article, we present the further improved database content of CoryneRegNet along with novel analysis features. The network visualization feature GraphVis now allows the inter-species comparisons of reconstructed gene regulatory networks and the projection of gene expression levels onto that networks. Therefore, we added stimulon data directly into the database, but also provide Web Service access to the DNA microarray analysis platform EMMA. Additionally, CoryneRegNet now provides a SOAP based Web Service server, which can easily be consumed by other bioinformatics software systems. Stimulons (imported from the database, or uploaded by the user) can be analyzed in the context of known transcriptional regulatory networks to predict putative contradictions or further gene regulatory interactions. Furthermore, it integrates protein clusters by means of heuristically solving the weighted graph cluster editing problem. In addition, it provides Web Service based access to up to date gene annotation data from GenDB. Conclusion The release 4.0 of CoryneRegNet is a comprehensive system for the integrated analysis of procaryotic gene regulatory networks. It is a versatile systems biology platform to support the efficient and large-scale analysis of transcriptional regulation of gene expression in microorganisms. It is publicly available at . PMID:17986320

The salinity tolerant poplar database (STPD): a comprehensive database for studying tree salt-tolerant adaption and poplar genomics.

PubMed

Ma, Yazhen; Xu, Ting; Wan, Dongshi; Ma, Tao; Shi, Sheng; Liu, Jianquan; Hu, Quanjun

2015-03-17

Soil salinity is a significant factor that impairs plant growth and agricultural productivity, and numerous efforts are underway to enhance salt tolerance of economically important plants. Populus species are widely cultivated for diverse uses. Especially, they grow in different habitats, from salty soil to mesophytic environment, and are therefore used as a model genus for elucidating physiological and molecular mechanisms of stress tolerance in woody plants. The Salinity Tolerant Poplar Database (STPD) is an integrative database for salt-tolerant poplar genome biology. Currently the STPD contains Populus euphratica genome and its related genetic resources. P. euphratica, with a preference of the salty habitats, has become a valuable genetic resource for the exploitation of tolerance characteristics in trees. This database contains curated data including genomic sequence, genes and gene functional information, non-coding RNA sequences, transposable elements, simple sequence repeats and single nucleotide polymorphisms information of P. euphratica, gene expression data between P. euphratica and Populus tomentosa, and whole-genome alignments between Populus trichocarpa, P. euphratica and Salix suchowensis. The STPD provides useful searching and data mining tools, including GBrowse genome browser, BLAST servers and genome alignments viewer, which can be used to browse genome regions, identify similar sequences and visualize genome alignments. Datasets within the STPD can also be downloaded to perform local searches. A new Salinity Tolerant Poplar Database has been developed to assist studies of salt tolerance in trees and poplar genomics. The database will be continuously updated to incorporate new genome-wide data of related poplar species. This database will serve as an infrastructure for researches on the molecular function of genes, comparative genomics, and evolution in closely related species as well as promote advances in molecular breeding within Populus. The STPD can be accessed at http://me.lzu.edu.cn/stpd/ .

APADB: a database for alternative polyadenylation and microRNA regulation events

PubMed Central

Müller, Sören; Rycak, Lukas; Afonso-Grunz, Fabian; Winter, Peter; Zawada, Adam M.; Damrath, Ewa; Scheider, Jessica; Schmäh, Juliane; Koch, Ina; Kahl, Günter; Rotter, Björn

2014-01-01

Alternative polyadenylation (APA) is a widespread mechanism that contributes to the sophisticated dynamics of gene regulation. Approximately 50% of all protein-coding human genes harbor multiple polyadenylation (PA) sites; their selective and combinatorial use gives rise to transcript variants with differing length of their 3′ untranslated region (3′UTR). Shortened variants escape UTR-mediated regulation by microRNAs (miRNAs), especially in cancer, where global 3′UTR shortening accelerates disease progression, dedifferentiation and proliferation. Here we present APADB, a database of vertebrate PA sites determined by 3′ end sequencing, using massive analysis of complementary DNA ends. APADB provides (A)PA sites for coding and non-coding transcripts of human, mouse and chicken genes. For human and mouse, several tissue types, including different cancer specimens, are available. APADB records the loss of predicted miRNA binding sites and visualizes next-generation sequencing reads that support each PA site in a genome browser. The database tables can either be browsed according to organism and tissue or alternatively searched for a gene of interest. APADB is the largest database of APA in human, chicken and mouse. The stored information provides experimental evidence for thousands of PA sites and APA events. APADB combines 3′ end sequencing data with prediction algorithms of miRNA binding sites, allowing to further improve prediction algorithms. Current databases lack correct information about 3′UTR lengths, especially for chicken, and APADB provides necessary information to close this gap. Database URL: http://tools.genxpro.net/apadb/ PMID:25052703

Mouse IDGenes: a reference database for genetic interactions in the developing mouse brain

PubMed Central

Matthes, Michaela; Preusse, Martin; Zhang, Jingzhong; Schechter, Julia; Mayer, Daniela; Lentes, Bernd; Theis, Fabian; Prakash, Nilima; Wurst, Wolfgang; Trümbach, Dietrich

2014-01-01

The study of developmental processes in the mouse and other vertebrates includes the understanding of patterning along the anterior–posterior, dorsal–ventral and medial– lateral axis. Specifically, neural development is also of great clinical relevance because several human neuropsychiatric disorders such as schizophrenia, autism disorders or drug addiction and also brain malformations are thought to have neurodevelopmental origins, i.e. pathogenesis initiates during childhood and adolescence. Impacts during early neurodevelopment might also predispose to late-onset neurodegenerative disorders, such as Parkinson’s disease. The neural tube develops from its precursor tissue, the neural plate, in a patterning process that is determined by compartmentalization into morphogenetic units, the action of local signaling centers and a well-defined and locally restricted expression of genes and their interactions. While public databases provide gene expression data with spatio-temporal resolution, they usually neglect the genetic interactions that govern neural development. Here, we introduce Mouse IDGenes, a reference database for genetic interactions in the developing mouse brain. The database is highly curated and offers detailed information about gene expressions and the genetic interactions at the developing mid-/hindbrain boundary. To showcase the predictive power of interaction data, we infer new Wnt/β-catenin target genes by machine learning and validate one of them experimentally. The database is updated regularly. Moreover, it can easily be extended by the research community. Mouse IDGenes will contribute as an important resource to the research on mouse brain development, not exclusively by offering data retrieval, but also by allowing data input. Database URL: http://mouseidgenes.helmholtz-muenchen.de. PMID:25145340

Patome: a database server for biological sequence annotation and analysis in issued patents and published patent applications

PubMed Central

Lee, Byungwook; Kim, Taehyung; Kim, Seon-Kyu; Lee, Kwang H.; Lee, Doheon

2007-01-01

With the advent of automated and high-throughput techniques, the number of patent applications containing biological sequences has been increasing rapidly. However, they have attracted relatively little attention compared to other sequence resources. We have built a database server called Patome, which contains biological sequence data disclosed in patents and published applications, as well as their analysis information. The analysis is divided into two steps. The first is an annotation step in which the disclosed sequences were annotated with RefSeq database. The second is an association step where the sequences were linked to Entrez Gene, OMIM and GO databases, and their results were saved as a gene–patent table. From the analysis, we found that 55% of human genes were associated with patenting. The gene–patent table can be used to identify whether a particular gene or disease is related to patenting. Patome is available at ; the information is updated bimonthly. PMID:17085479

The Degradome database: expanding roles of mammalian proteases in life and disease

PubMed Central

Pérez-Silva, José G.; Español, Yaiza; Velasco, Gloria; Quesada, Víctor

2016-01-01

Since the definition of the degradome as the complete repertoire of proteases in a given organism, the combined effort of numerous laboratories has greatly expanded our knowledge of its roles in biology and pathology. Once the genomic sequences of several important model organisms were made available, we presented the Degradome database containing the curated sets of known protease genes in human, chimpanzee, mouse and rat. Here, we describe the updated Degradome database, featuring 81 new protease genes and 7 new protease families. Notably, in this short time span, the number of known hereditary diseases caused by mutations in protease genes has increased from 77 to 119. This increase reflects the growing interest on the roles of the degradome in multiple diseases, including cancer and ageing. Finally, we have leveraged the widespread adoption of new webtools to provide interactive graphic views that show information about proteases in the global context of the degradome. The Degradome database can be accessed through its web interface at http://degradome.uniovi.es. PMID:26553809

Relax with CouchDB - Into the non-relational DBMS era of Bioinformatics

PubMed Central

Manyam, Ganiraju; Payton, Michelle A.; Roth, Jack A.; Abruzzo, Lynne V.; Coombes, Kevin R.

2012-01-01

With the proliferation of high-throughput technologies, genome-level data analysis has become common in molecular biology. Bioinformaticians are developing extensive resources to annotate and mine biological features from high-throughput data. The underlying database management systems for most bioinformatics software are based on a relational model. Modern non-relational databases offer an alternative that has flexibility, scalability, and a non-rigid design schema. Moreover, with an accelerated development pace, non-relational databases like CouchDB can be ideal tools to construct bioinformatics utilities. We describe CouchDB by presenting three new bioinformatics resources: (a) geneSmash, which collates data from bioinformatics resources and provides automated gene-centric annotations, (b) drugBase, a database of drug-target interactions with a web interface powered by geneSmash, and (c) HapMap-CN, which provides a web interface to query copy number variations from three SNP-chip HapMap datasets. In addition to the web sites, all three systems can be accessed programmatically via web services. PMID:22609849

SorghumFDB: sorghum functional genomics database with multidimensional network analysis.

PubMed

Tian, Tian; You, Qi; Zhang, Liwei; Yi, Xin; Yan, Hengyu; Xu, Wenying; Su, Zhen

2016-01-01

Sorghum (Sorghum bicolor [L.] Moench) has excellent agronomic traits and biological properties, such as heat and drought-tolerance. It is a C4 grass and potential bioenergy-producing plant, which makes it an important crop worldwide. With the sorghum genome sequence released, it is essential to establish a sorghum functional genomics data mining platform. We collected genomic data and some functional annotations to construct a sorghum functional genomics database (SorghumFDB). SorghumFDB integrated knowledge of sorghum gene family classifications (transcription regulators/factors, carbohydrate-active enzymes, protein kinases, ubiquitins, cytochrome P450, monolignol biosynthesis related enzymes, R-genes and organelle-genes), detailed gene annotations, miRNA and target gene information, orthologous pairs in the model plants Arabidopsis, rice and maize, gene loci conversions and a genome browser. We further constructed a dynamic network of multidimensional biological relationships, comprised of the co-expression data, protein-protein interactions and miRNA-target pairs. We took effective measures to combine the network, gene set enrichment and motif analyses to determine the key regulators that participate in related metabolic pathways, such as the lignin pathway, which is a major biological process in bioenergy-producing plants.Database URL: http://structuralbiology.cau.edu.cn/sorghum/index.html. © The Author(s) 2016. Published by Oxford University Press.

Sequencing rare marine actinomycete genomes reveals high density of unique natural product biosynthetic gene clusters.

PubMed

Schorn, Michelle A; Alanjary, Mohammad M; Aguinaldo, Kristen; Korobeynikov, Anton; Podell, Sheila; Patin, Nastassia; Lincecum, Tommie; Jensen, Paul R; Ziemert, Nadine; Moore, Bradley S

2016-12-01

Traditional natural product discovery methods have nearly exhausted the accessible diversity of microbial chemicals, making new sources and techniques paramount in the search for new molecules. Marine actinomycete bacteria have recently come into the spotlight as fruitful producers of structurally diverse secondary metabolites, and remain relatively untapped. In this study, we sequenced 21 marine-derived actinomycete strains, rarely studied for their secondary metabolite potential and under-represented in current genomic databases. We found that genome size and phylogeny were good predictors of biosynthetic gene cluster diversity, with larger genomes rivalling the well-known marine producers in the Streptomyces and Salinispora genera. Genomes in the Micrococcineae suborder, however, had consistently the lowest number of biosynthetic gene clusters. By networking individual gene clusters into gene cluster families, we were able to computationally estimate the degree of novelty each genus contributed to the current sequence databases. Based on the similarity measures between all actinobacteria in the Joint Genome Institute's Atlas of Biosynthetic gene Clusters database, rare marine genera show a high degree of novelty and diversity, with Corynebacterium, Gordonia, Nocardiopsis, Saccharomonospora and Pseudonocardia genera representing the highest gene cluster diversity. This research validates that rare marine actinomycetes are important candidates for exploration, as they are relatively unstudied, and their relatives are historically rich in secondary metabolites.

Gene therapy clinical trials worldwide to 2017: An update.

PubMed

Ginn, Samantha L; Amaya, Anais K; Alexander, Ian E; Edelstein, Michael; Abedi, Mohammad R

2018-03-25

To date, almost 2600 gene therapy clinical trials have been completed, are ongoing or have been approved worldwide. Our database brings together global information on gene therapy clinical activity from trial databases, official agency sources, published literature, conference presentations and posters kindly provided to us by individual investigators or trial sponsors. This review presents our analysis of clinical trials that, to the best of our knowledge, have been or are being performed worldwide. As of our November 2017 update, we have entries on 2597 trials undertaken in 38 countries. We have analysed the geographical distribution of trials, the disease indications (or other reasons) for trials, the proportions to which different vector types are used, and the genes that have been transferred. Details of the analyses presented, and our searchable database are available via The Journal of Gene Medicine Gene Therapy Clinical Trials Worldwide website at: http://www.wiley.co.uk/genmed/clinical. We also provide an overview of the progress being made in gene therapy clinical trials around the world, and discuss key trends since the previous review, namely the use of chimeric antigen receptor T cells for the treatment of cancer and advancements in genome editing technologies, which have the potential to transform the field moving forward. Copyright © 2018 John Wiley & Sons, Ltd.

SGP-1: Prediction and Validation of Homologous Genes Based on Sequence Alignments

PubMed Central

Wiehe, Thomas; Gebauer-Jung, Steffi; Mitchell-Olds, Thomas; Guigó, Roderic

2001-01-01

Conventional methods of gene prediction rely on the recognition of DNA-sequence signals, the coding potential or the comparison of a genomic sequence with a cDNA, EST, or protein database. Reasons for limited accuracy in many circumstances are species-specific training and the incompleteness of reference databases. Lately, comparative genome analysis has attracted increasing attention. Several analysis tools that are based on human/mouse comparisons are already available. Here, we present a program for the prediction of protein-coding genes, termed SGP-1 (Syntenic Gene Prediction), which is based on the similarity of homologous genomic sequences. In contrast to most existing tools, the accuracy of SGP-1 depends little on species-specific properties such as codon usage or the nucleotide distribution. SGP-1 may therefore be applied to nonstandard model organisms in vertebrates as well as in plants, without the need for extensive parameter training. In addition to predicting genes in large-scale genomic sequences, the program may be useful to validate gene structure annotations from databases. To this end, SGP-1 output also contains comparisons between predicted and annotated gene structures in HTML format. The program can be accessed via a Web server at http://soft.ice.mpg.de/sgp-1. The source code, written in ANSI C, is available on request from the authors. PMID:11544202

Sequencing rare marine actinomycete genomes reveals high density of unique natural product biosynthetic gene clusters

PubMed Central

Schorn, Michelle A.; Alanjary, Mohammad M.; Aguinaldo, Kristen; Korobeynikov, Anton; Podell, Sheila; Patin, Nastassia; Lincecum, Tommie; Jensen, Paul R.; Ziemert, Nadine

2016-01-01

Traditional natural product discovery methods have nearly exhausted the accessible diversity of microbial chemicals, making new sources and techniques paramount in the search for new molecules. Marine actinomycete bacteria have recently come into the spotlight as fruitful producers of structurally diverse secondary metabolites, and remain relatively untapped. In this study, we sequenced 21 marine-derived actinomycete strains, rarely studied for their secondary metabolite potential and under-represented in current genomic databases. We found that genome size and phylogeny were good predictors of biosynthetic gene cluster diversity, with larger genomes rivalling the well-known marine producers in the Streptomyces and Salinispora genera. Genomes in the Micrococcineae suborder, however, had consistently the lowest number of biosynthetic gene clusters. By networking individual gene clusters into gene cluster families, we were able to computationally estimate the degree of novelty each genus contributed to the current sequence databases. Based on the similarity measures between all actinobacteria in the Joint Genome Institute's Atlas of Biosynthetic gene Clusters database, rare marine genera show a high degree of novelty and diversity, with Corynebacterium, Gordonia, Nocardiopsis, Saccharomonospora and Pseudonocardia genera representing the highest gene cluster diversity. This research validates that rare marine actinomycetes are important candidates for exploration, as they are relatively unstudied, and their relatives are historically rich in secondary metabolites. PMID:27902408

Design of Knowledge Bases for Plant Gene Regulatory Networks.

PubMed

Mukundi, Eric; Gomez-Cano, Fabio; Ouma, Wilberforce Zachary; Grotewold, Erich

2017-01-01

Developing a knowledge base that contains all the information necessary for the researcher studying gene regulation in a particular organism can be accomplished in four stages. This begins with defining the data scope. We describe here the necessary information and resources, and outline the methods for obtaining data. The second stage consists of designing the schema, which involves defining the entire arrangement of the database in a systematic plan. The third stage is the implementation, defined by actualization of the database by using software according to a predefined schema. The final stage is development, where the database is made available to users in a web-accessible system. The result is a knowledgebase that integrates all the information pertaining to gene regulation, and which is easily expandable and transferable.

The Zebrafish Model Organism Database: new support for human disease models, mutation details, gene expression phenotypes and searching

PubMed Central

Howe, Douglas G.; Bradford, Yvonne M.; Eagle, Anne; Fashena, David; Frazer, Ken; Kalita, Patrick; Mani, Prita; Martin, Ryan; Moxon, Sierra Taylor; Paddock, Holly; Pich, Christian; Ramachandran, Sridhar; Ruzicka, Leyla; Schaper, Kevin; Shao, Xiang; Singer, Amy; Toro, Sabrina; Van Slyke, Ceri; Westerfield, Monte

2017-01-01

The Zebrafish Model Organism Database (ZFIN; http://zfin.org) is the central resource for zebrafish (Danio rerio) genetic, genomic, phenotypic and developmental data. ZFIN curators provide expert manual curation and integration of comprehensive data involving zebrafish genes, mutants, transgenic constructs and lines, phenotypes, genotypes, gene expressions, morpholinos, TALENs, CRISPRs, antibodies, anatomical structures, models of human disease and publications. We integrate curated, directly submitted, and collaboratively generated data, making these available to zebrafish research community. Among the vertebrate model organisms, zebrafish are superbly suited for rapid generation of sequence-targeted mutant lines, characterization of phenotypes including gene expression patterns, and generation of human disease models. The recent rapid adoption of zebrafish as human disease models is making management of these data particularly important to both the research and clinical communities. Here, we describe recent enhancements to ZFIN including use of the zebrafish experimental conditions ontology, ‘Fish’ records in the ZFIN database, support for gene expression phenotypes, models of human disease, mutation details at the DNA, RNA and protein levels, and updates to the ZFIN single box search. PMID:27899582

The database of chromosome imbalance regions and genes resided in lung cancer from Asian and Caucasian identified by array-comparative genomic hybridization

PubMed Central

2012-01-01

Background Cancer-related genes show racial differences. Therefore, identification and characterization of DNA copy number alteration regions in different racial groups helps to dissect the mechanism of tumorigenesis. Methods Array-comparative genomic hybridization (array-CGH) was analyzed for DNA copy number profile in 40 Asian and 20 Caucasian lung cancer patients. Three methods including MetaCore analysis for disease and pathway correlations, concordance analysis between array-CGH database and the expression array database, and literature search for copy number variation genes were performed to select novel lung cancer candidate genes. Four candidate oncogenes were validated for DNA copy number and mRNA and protein expression by quantitative polymerase chain reaction (qPCR), chromogenic in situ hybridization (CISH), reverse transcriptase-qPCR (RT-qPCR), and immunohistochemistry (IHC) in more patients. Results We identified 20 chromosomal imbalance regions harboring 459 genes for Caucasian and 17 regions containing 476 genes for Asian lung cancer patients. Seven common chromosomal imbalance regions harboring 117 genes, included gain on 3p13-14, 6p22.1, 9q21.13, 13q14.1, and 17p13.3; and loss on 3p22.2-22.3 and 13q13.3 were found both in Asian and Caucasian patients. Gene validation for four genes including ARHGAP19 (10q24.1) functioning in Rho activity control, FRAT2 (10q24.1) involved in Wnt signaling, PAFAH1B1 (17p13.3) functioning in motility control, and ZNF322A (6p22.1) involved in MAPK signaling was performed using qPCR and RT-qPCR. Mean gene dosage and mRNA expression level of the four candidate genes in tumor tissues were significantly higher than the corresponding normal tissues (P<0.001~P=0.06). In addition, CISH analysis of patients indicated that copy number amplification indeed occurred for ARHGAP19 and ZNF322A genes in lung cancer patients. IHC analysis of paraffin blocks from Asian Caucasian patients demonstrated that the frequency of PAFAH1B1 protein overexpression was 68% in Asian and 70% in Caucasian. Conclusions Our study provides an invaluable database revealing common and differential imbalance regions at specific chromosomes among Asian and Caucasian lung cancer patients. Four validation methods confirmed our database, which would help in further studies on the mechanism of lung tumorigenesis. PMID:22691236

Virtual OPACs versus Union Database: Two Models of Union Catalogue Provision.

ERIC Educational Resources Information Center

Cousins, Shirley

1999-01-01

Considers some of the major technical and organizational issues involved in virtual-catalog production, contrasting them with the traditional union catalog approach exemplified by COPAC, an online public-access catalog composed of academic libraries in the United Kingdom. Suggest a method of integrating these two models of the union catalog.…

Structuring osteosarcoma knowledge: an osteosarcoma-gene association database based on literature mining and manual annotation.

PubMed

Poos, Kathrin; Smida, Jan; Nathrath, Michaela; Maugg, Doris; Baumhoer, Daniel; Neumann, Anna; Korsching, Eberhard

2014-01-01

Osteosarcoma (OS) is the most common primary bone cancer exhibiting high genomic instability. This genomic instability affects multiple genes and microRNAs to a varying extent depending on patient and tumor subtype. Massive research is ongoing to identify genes including their gene products and microRNAs that correlate with disease progression and might be used as biomarkers for OS. However, the genomic complexity hampers the identification of reliable biomarkers. Up to now, clinico-pathological factors are the key determinants to guide prognosis and therapeutic treatments. Each day, new studies about OS are published and complicate the acquisition of information to support biomarker discovery and therapeutic improvements. Thus, it is necessary to provide a structured and annotated view on the current OS knowledge that is quick and easily accessible to researchers of the field. Therefore, we developed a publicly available database and Web interface that serves as resource for OS-associated genes and microRNAs. Genes and microRNAs were collected using an automated dictionary-based gene recognition procedure followed by manual review and annotation by experts of the field. In total, 911 genes and 81 microRNAs related to 1331 PubMed abstracts were collected (last update: 29 October 2013). Users can evaluate genes and microRNAs according to their potential prognostic and therapeutic impact, the experimental procedures, the sample types, the biological contexts and microRNA target gene interactions. Additionally, a pathway enrichment analysis of the collected genes highlights different aspects of OS progression. OS requires pathways commonly deregulated in cancer but also features OS-specific alterations like deregulated osteoclast differentiation. To our knowledge, this is the first effort of an OS database containing manual reviewed and annotated up-to-date OS knowledge. It might be a useful resource especially for the bone tumor research community, as specific information about genes or microRNAs is quick and easily accessible. Hence, this platform can support the ongoing OS research and biomarker discovery. Database URL: http://osteosarcoma-db.uni-muenster.de. © The Author(s) 2014. Published by Oxford University Press.

Structuring osteosarcoma knowledge: an osteosarcoma-gene association database based on literature mining and manual annotation

PubMed Central

Poos, Kathrin; Smida, Jan; Nathrath, Michaela; Maugg, Doris; Baumhoer, Daniel; Neumann, Anna; Korsching, Eberhard

2014-01-01

Osteosarcoma (OS) is the most common primary bone cancer exhibiting high genomic instability. This genomic instability affects multiple genes and microRNAs to a varying extent depending on patient and tumor subtype. Massive research is ongoing to identify genes including their gene products and microRNAs that correlate with disease progression and might be used as biomarkers for OS. However, the genomic complexity hampers the identification of reliable biomarkers. Up to now, clinico-pathological factors are the key determinants to guide prognosis and therapeutic treatments. Each day, new studies about OS are published and complicate the acquisition of information to support biomarker discovery and therapeutic improvements. Thus, it is necessary to provide a structured and annotated view on the current OS knowledge that is quick and easily accessible to researchers of the field. Therefore, we developed a publicly available database and Web interface that serves as resource for OS-associated genes and microRNAs. Genes and microRNAs were collected using an automated dictionary-based gene recognition procedure followed by manual review and annotation by experts of the field. In total, 911 genes and 81 microRNAs related to 1331 PubMed abstracts were collected (last update: 29 October 2013). Users can evaluate genes and microRNAs according to their potential prognostic and therapeutic impact, the experimental procedures, the sample types, the biological contexts and microRNA target gene interactions. Additionally, a pathway enrichment analysis of the collected genes highlights different aspects of OS progression. OS requires pathways commonly deregulated in cancer but also features OS-specific alterations like deregulated osteoclast differentiation. To our knowledge, this is the first effort of an OS database containing manual reviewed and annotated up-to-date OS knowledge. It might be a useful resource especially for the bone tumor research community, as specific information about genes or microRNAs is quick and easily accessible. Hence, this platform can support the ongoing OS research and biomarker discovery. Database URL: http://osteosarcoma-db.uni-muenster.de PMID:24865352

Enhanced annotations and features for comparing thousands of Pseudomonas genomes in the Pseudomonas genome database.

PubMed

Winsor, Geoffrey L; Griffiths, Emma J; Lo, Raymond; Dhillon, Bhavjinder K; Shay, Julie A; Brinkman, Fiona S L

2016-01-04

The Pseudomonas Genome Database (http://www.pseudomonas.com) is well known for the application of community-based annotation approaches for producing a high-quality Pseudomonas aeruginosa PAO1 genome annotation, and facilitating whole-genome comparative analyses with other Pseudomonas strains. To aid analysis of potentially thousands of complete and draft genome assemblies, this database and analysis platform was upgraded to integrate curated genome annotations and isolate metadata with enhanced tools for larger scale comparative analysis and visualization. Manually curated gene annotations are supplemented with improved computational analyses that help identify putative drug targets and vaccine candidates or assist with evolutionary studies by identifying orthologs, pathogen-associated genes and genomic islands. The database schema has been updated to integrate isolate metadata that will facilitate more powerful analysis of genomes across datasets in the future. We continue to place an emphasis on providing high-quality updates to gene annotations through regular review of the scientific literature and using community-based approaches including a major new Pseudomonas community initiative for the assignment of high-quality gene ontology terms to genes. As we further expand from thousands of genomes, we plan to provide enhancements that will aid data visualization and analysis arising from whole-genome comparative studies including more pan-genome and population-based approaches. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

SurvExpress: an online biomarker validation tool and database for cancer gene expression data using survival analysis.

PubMed

Aguirre-Gamboa, Raul; Gomez-Rueda, Hugo; Martínez-Ledesma, Emmanuel; Martínez-Torteya, Antonio; Chacolla-Huaringa, Rafael; Rodriguez-Barrientos, Alberto; Tamez-Peña, José G; Treviño, Victor

2013-01-01

Validation of multi-gene biomarkers for clinical outcomes is one of the most important issues for cancer prognosis. An important source of information for virtual validation is the high number of available cancer datasets. Nevertheless, assessing the prognostic performance of a gene expression signature along datasets is a difficult task for Biologists and Physicians and also time-consuming for Statisticians and Bioinformaticians. Therefore, to facilitate performance comparisons and validations of survival biomarkers for cancer outcomes, we developed SurvExpress, a cancer-wide gene expression database with clinical outcomes and a web-based tool that provides survival analysis and risk assessment of cancer datasets. The main input of SurvExpress is only the biomarker gene list. We generated a cancer database collecting more than 20,000 samples and 130 datasets with censored clinical information covering tumors over 20 tissues. We implemented a web interface to perform biomarker validation and comparisons in this database, where a multivariate survival analysis can be accomplished in about one minute. We show the utility and simplicity of SurvExpress in two biomarker applications for breast and lung cancer. Compared to other tools, SurvExpress is the largest, most versatile, and quickest free tool available. SurvExpress web can be accessed in http://bioinformatica.mty.itesm.mx/SurvExpress (a tutorial is included). The website was implemented in JSP, JavaScript, MySQL, and R.

SurvExpress: An Online Biomarker Validation Tool and Database for Cancer Gene Expression Data Using Survival Analysis

PubMed Central

Aguirre-Gamboa, Raul; Gomez-Rueda, Hugo; Martínez-Ledesma, Emmanuel; Martínez-Torteya, Antonio; Chacolla-Huaringa, Rafael; Rodriguez-Barrientos, Alberto; Tamez-Peña, José G.; Treviño, Victor

2013-01-01

Validation of multi-gene biomarkers for clinical outcomes is one of the most important issues for cancer prognosis. An important source of information for virtual validation is the high number of available cancer datasets. Nevertheless, assessing the prognostic performance of a gene expression signature along datasets is a difficult task for Biologists and Physicians and also time-consuming for Statisticians and Bioinformaticians. Therefore, to facilitate performance comparisons and validations of survival biomarkers for cancer outcomes, we developed SurvExpress, a cancer-wide gene expression database with clinical outcomes and a web-based tool that provides survival analysis and risk assessment of cancer datasets. The main input of SurvExpress is only the biomarker gene list. We generated a cancer database collecting more than 20,000 samples and 130 datasets with censored clinical information covering tumors over 20 tissues. We implemented a web interface to perform biomarker validation and comparisons in this database, where a multivariate survival analysis can be accomplished in about one minute. We show the utility and simplicity of SurvExpress in two biomarker applications for breast and lung cancer. Compared to other tools, SurvExpress is the largest, most versatile, and quickest free tool available. SurvExpress web can be accessed in http://bioinformatica.mty.itesm.mx/SurvExpress (a tutorial is included). The website was implemented in JSP, JavaScript, MySQL, and R. PMID:24066126

Database for High Throughput Screening Hits (dHITS): a simple tool to retrieve gene specific phenotypes from systematic screens done in yeast.

PubMed

Chuartzman, Silvia G; Schuldiner, Maya

2018-03-25

In the last decade several collections of Saccharomyces cerevisiae yeast strains have been created. In these collections every gene is modified in a similar manner such as by a deletion or the addition of a protein tag. Such libraries have enabled a diversity of systematic screens, giving rise to large amounts of information regarding gene functions. However, often papers describing such screens focus on a single gene or a small set of genes and all other loci affecting the phenotype of choice ('hits') are only mentioned in tables that are provided as supplementary material and are often hard to retrieve or search. To help unify and make such data accessible, we have created a Database of High Throughput Screening Hits (dHITS). The dHITS database enables information to be obtained about screens in which genes of interest were found as well as the other genes that came up in that screen - all in a readily accessible and downloadable format. The ability to query large lists of genes at the same time provides a platform to easily analyse hits obtained from transcriptional analyses or other screens. We hope that this platform will serve as a tool to facilitate investigation of protein functions to the yeast community. © 2018 The Authors Yeast Published by John Wiley & Sons Ltd.

Large-Scale Collection and Analysis of Full-Length cDNAs from Brachypodium distachyon and Integration with Pooideae Sequence Resources

PubMed Central

Mochida, Keiichi; Uehara-Yamaguchi, Yukiko; Takahashi, Fuminori; Yoshida, Takuhiro; Sakurai, Tetsuya; Shinozaki, Kazuo

2013-01-01

A comprehensive collection of full-length cDNAs is essential for correct structural gene annotation and functional analyses of genes. We constructed a mixed full-length cDNA library from 21 different tissues of Brachypodium distachyon Bd21, and obtained 78,163 high quality expressed sequence tags (ESTs) from both ends of ca. 40,000 clones (including 16,079 contigs). We updated gene structure annotations of Brachypodium genes based on full-length cDNA sequences in comparison with the latest publicly available annotations. About 10,000 non-redundant gene models were supported by full-length cDNAs; ca. 6,000 showed some transcription unit modifications. We also found ca. 580 novel gene models, including 362 newly identified in Bd21. Using the updated transcription start sites, we searched a total of 580 plant cis-motifs in the −3 kb promoter regions and determined a genome-wide Brachypodium promoter architecture. Furthermore, we integrated the Brachypodium full-length cDNAs and updated gene structures with available sequence resources in wheat and barley in a web-accessible database, the RIKEN Brachypodium FL cDNA database. The database represents a “one-stop” information resource for all genomic information in the Pooideae, facilitating functional analysis of genes in this model grass plant and seamless knowledge transfer to the Triticeae crops. PMID:24130698

DDMGD: the database of text-mined associations between genes methylated in diseases from different species.

PubMed

Bin Raies, Arwa; Mansour, Hicham; Incitti, Roberto; Bajic, Vladimir B

2015-01-01

Gathering information about associations between methylated genes and diseases is important for diseases diagnosis and treatment decisions. Recent advancements in epigenetics research allow for large-scale discoveries of associations of genes methylated in diseases in different species. Searching manually for such information is not easy, as it is scattered across a large number of electronic publications and repositories. Therefore, we developed DDMGD database (http://www.cbrc.kaust.edu.sa/ddmgd/) to provide a comprehensive repository of information related to genes methylated in diseases that can be found through text mining. DDMGD's scope is not limited to a particular group of genes, diseases or species. Using the text mining system DEMGD we developed earlier and additional post-processing, we extracted associations of genes methylated in different diseases from PubMed Central articles and PubMed abstracts. The accuracy of extracted associations is 82% as estimated on 2500 hand-curated entries. DDMGD provides a user-friendly interface facilitating retrieval of these associations ranked according to confidence scores. Submission of new associations to DDMGD is provided. A comparison analysis of DDMGD with several other databases focused on genes methylated in diseases shows that DDMGD is comprehensive and includes most of the recent information on genes methylated in diseases. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

A combined strategy involving Sanger and 454 pyrosequencing increases genomic resources to aid in the management of reproduction, disease control and genetic selection in the turbot (Scophthalmus maximus).

PubMed

Ribas, Laia; Pardo, Belén G; Fernández, Carlos; Alvarez-Diós, José Antonio; Gómez-Tato, Antonio; Quiroga, María Isabel; Planas, Josep V; Sitjà-Bobadilla, Ariadna; Martínez, Paulino; Piferrer, Francesc

2013-03-15

Genomic resources for plant and animal species that are under exploitation primarily for human consumption are increasingly important, among other things, for understanding physiological processes and for establishing adequate genetic selection programs. Current available techniques for high-throughput sequencing have been implemented in a number of species, including fish, to obtain a proper description of the transcriptome. The objective of this study was to generate a comprehensive transcriptomic database in turbot, a highly priced farmed fish species in Europe, with potential expansion to other areas of the world, for which there are unsolved production bottlenecks, to understand better reproductive- and immune-related functions. This information is essential to implement marker assisted selection programs useful for the turbot industry. Expressed sequence tags were generated by Sanger sequencing of cDNA libraries from different immune-related tissues after several parasitic challenges. The resulting database ("Turbot 2 database") was enlarged with sequences generated from a 454 sequencing run of brain-hypophysis-gonadal axis-derived RNA obtained from turbot at different development stages. The assembly of Sanger and 454 sequences generated 52,427 consensus sequences ("Turbot 3 database"), of which 23,661 were successfully annotated. A total of 1,410 sequences were confirmed to be related to reproduction and key genes involved in sex differentiation and maturation were identified for the first time in turbot (AR, AMH, SRY-related genes, CYP19A, ZPGs, STAR FSHR, etc.). Similarly, 2,241 sequences were related to the immune system and several novel key immune genes were identified (BCL, TRAF, NCK, CD28 and TOLLIP, among others). The number of genes of many relevant reproduction- and immune-related pathways present in the database was 50-90% of the total gene count of each pathway. In addition, 1,237 microsatellites and 7,362 single nucleotide polymorphisms (SNPs) were also compiled. Further, 2,976 putative natural antisense transcripts (NATs) including microRNAs were also identified. The combined sequencing strategies employed here significantly increased the turbot genomic resources available, including 34,400 novel sequences. The generated database contains a larger number of genes relevant for reproduction- and immune-associated studies, with an excellent coverage of most genes present in many relevant physiological pathways. This database also allowed the identification of many microsatellites and SNP markers that will be very useful for population and genome screening and a valuable aid in marker assisted selection programs.

TranscriptomeBrowser 3.0: introducing a new compendium of molecular interactions and a new visualization tool for the study of gene regulatory networks.

PubMed

Lepoivre, Cyrille; Bergon, Aurélie; Lopez, Fabrice; Perumal, Narayanan B; Nguyen, Catherine; Imbert, Jean; Puthier, Denis

2012-01-31

Deciphering gene regulatory networks by in silico approaches is a crucial step in the study of the molecular perturbations that occur in diseases. The development of regulatory maps is a tedious process requiring the comprehensive integration of various evidences scattered over biological databases. Thus, the research community would greatly benefit from having a unified database storing known and predicted molecular interactions. Furthermore, given the intrinsic complexity of the data, the development of new tools offering integrated and meaningful visualizations of molecular interactions is necessary to help users drawing new hypotheses without being overwhelmed by the density of the subsequent graph. We extend the previously developed TranscriptomeBrowser database with a set of tables containing 1,594,978 human and mouse molecular interactions. The database includes: (i) predicted regulatory interactions (computed by scanning vertebrate alignments with a set of 1,213 position weight matrices), (ii) potential regulatory interactions inferred from systematic analysis of ChIP-seq experiments, (iii) regulatory interactions curated from the literature, (iv) predicted post-transcriptional regulation by micro-RNA, (v) protein kinase-substrate interactions and (vi) physical protein-protein interactions. In order to easily retrieve and efficiently analyze these interactions, we developed In-teractomeBrowser, a graph-based knowledge browser that comes as a plug-in for Transcriptome-Browser. The first objective of InteractomeBrowser is to provide a user-friendly tool to get new insight into any gene list by providing a context-specific display of putative regulatory and physical interactions. To achieve this, InteractomeBrowser relies on a "cell compartments-based layout" that makes use of a subset of the Gene Ontology to map gene products onto relevant cell compartments. This layout is particularly powerful for visual integration of heterogeneous biological information and is a productive avenue in generating new hypotheses. The second objective of InteractomeBrowser is to fill the gap between interaction databases and dynamic modeling. It is thus compatible with the network analysis software Cytoscape and with the Gene Interaction Network simulation software (GINsim). We provide examples underlying the benefits of this visualization tool for large gene set analysis related to thymocyte differentiation. The InteractomeBrowser plugin is a powerful tool to get quick access to a knowledge database that includes both predicted and validated molecular interactions. InteractomeBrowser is available through the TranscriptomeBrowser framework and can be found at: http://tagc.univ-mrs.fr/tbrowser/. Our database is updated on a regular basis.

Signature Verification Based on Handwritten Text Recognition

NASA Astrophysics Data System (ADS)

Viriri, Serestina; Tapamo, Jules-R.

Signatures continue to be an important biometric trait because it remains widely used primarily for authenticating the identity of human beings. This paper presents an efficient text-based directional signature recognition algorithm which verifies signatures, even when they are composed of special unconstrained cursive characters which are superimposed and embellished. This algorithm extends the character-based signature verification technique. The experiments carried out on the GPDS signature database and an additional database created from signatures captured using the ePadInk tablet, show that the approach is effective and efficient, with a positive verification rate of 94.95%.

Detection of Trace Gases in Biomass Burning Plumes via Infrared Spectroscopy: Updates and Uses of the Northwest Infrared Database (NWIR)

NASA Astrophysics Data System (ADS)

Brauer, C. S.; Johnson, T. J.; Blake, T. A.; Sharpe, S. W.; Sams, R. L.; Tonkyn, R. G.

2014-12-01

The Northwest Infrared Database (NWIR) contains quantitative, gas-phase infrared spectra of nearly 500 pure chemical species, including over 60 molecules that are known or suspected biomass-burning effluents. The data, recorded at 0.1 cm-1 resolution, are pressure broadened to one atmosphere (N2) and each 25 oC spectrum is a composite composed of a minimum of ten individual measurements. Examples from this set of measurements will be presented and experimental details will be discussed in the context of the utility of NWIR for biomass-burning studies.

Plant Reactome: a resource for plant pathways and comparative analysis

PubMed Central

Naithani, Sushma; Preece, Justin; D'Eustachio, Peter; Gupta, Parul; Amarasinghe, Vindhya; Dharmawardhana, Palitha D.; Wu, Guanming; Fabregat, Antonio; Elser, Justin L.; Weiser, Joel; Keays, Maria; Fuentes, Alfonso Munoz-Pomer; Petryszak, Robert; Stein, Lincoln D.; Ware, Doreen; Jaiswal, Pankaj

2017-01-01

Plant Reactome (http://plantreactome.gramene.org/) is a free, open-source, curated plant pathway database portal, provided as part of the Gramene project. The database provides intuitive bioinformatics tools for the visualization, analysis and interpretation of pathway knowledge to support genome annotation, genome analysis, modeling, systems biology, basic research and education. Plant Reactome employs the structural framework of a plant cell to show metabolic, transport, genetic, developmental and signaling pathways. We manually curate molecular details of pathways in these domains for reference species Oryza sativa (rice) supported by published literature and annotation of well-characterized genes. Two hundred twenty-two rice pathways, 1025 reactions associated with 1173 proteins, 907 small molecules and 256 literature references have been curated to date. These reference annotations were used to project pathways for 62 model, crop and evolutionarily significant plant species based on gene homology. Database users can search and browse various components of the database, visualize curated baseline expression of pathway-associated genes provided by the Expression Atlas and upload and analyze their Omics datasets. The database also offers data access via Application Programming Interfaces (APIs) and in various standardized pathway formats, such as SBML and BioPAX. PMID:27799469

Human Ageing Genomic Resources: Integrated databases and tools for the biology and genetics of ageing

PubMed Central

Tacutu, Robi; Craig, Thomas; Budovsky, Arie; Wuttke, Daniel; Lehmann, Gilad; Taranukha, Dmitri; Costa, Joana; Fraifeld, Vadim E.; de Magalhães, João Pedro

2013-01-01

The Human Ageing Genomic Resources (HAGR, http://genomics.senescence.info) is a freely available online collection of research databases and tools for the biology and genetics of ageing. HAGR features now several databases with high-quality manually curated data: (i) GenAge, a database of genes associated with ageing in humans and model organisms; (ii) AnAge, an extensive collection of longevity records and complementary traits for >4000 vertebrate species; and (iii) GenDR, a newly incorporated database, containing both gene mutations that interfere with dietary restriction-mediated lifespan extension and consistent gene expression changes induced by dietary restriction. Since its creation about 10 years ago, major efforts have been undertaken to maintain the quality of data in HAGR, while further continuing to develop, improve and extend it. This article briefly describes the content of HAGR and details the major updates since its previous publications, in terms of both structure and content. The completely redesigned interface, more intuitive and more integrative of HAGR resources, is also presented. Altogether, we hope that through its improvements, the current version of HAGR will continue to provide users with the most comprehensive and accessible resources available today in the field of biogerontology. PMID:23193293

LOVD: easy creation of a locus-specific sequence variation database using an "LSDB-in-a-box" approach.

PubMed

Fokkema, Ivo F A C; den Dunnen, Johan T; Taschner, Peter E M

2005-08-01

The completion of the human genome project has initiated, as well as provided the basis for, the collection and study of all sequence variation between individuals. Direct access to up-to-date information on sequence variation is currently provided most efficiently through web-based, gene-centered, locus-specific databases (LSDBs). We have developed the Leiden Open (source) Variation Database (LOVD) software approaching the "LSDB-in-a-Box" idea for the easy creation and maintenance of a fully web-based gene sequence variation database. LOVD is platform-independent and uses PHP and MySQL open source software only. The basic gene-centered and modular design of the database follows the recommendations of the Human Genome Variation Society (HGVS) and focuses on the collection and display of DNA sequence variations. With minimal effort, the LOVD platform is extendable with clinical data. The open set-up should both facilitate and promote functional extension with scripts written by the community. The LOVD software is freely available from the Leiden Muscular Dystrophy pages (www.DMD.nl/LOVD/). To promote the use of LOVD, we currently offer curators the possibility to set up an LSDB on our Leiden server. (c) 2005 Wiley-Liss, Inc.

Weighted gene co-expression network analysis of expression data of monozygotic twins identifies specific modules and hub genes related to BMI.

PubMed

Wang, Weijing; Jiang, Wenjie; Hou, Lin; Duan, Haiping; Wu, Yili; Xu, Chunsheng; Tan, Qihua; Li, Shuxia; Zhang, Dongfeng

2017-11-13

The therapeutic management of obesity is challenging, hence further elucidating the underlying mechanisms of obesity development and identifying new diagnostic biomarkers and therapeutic targets are urgent and necessary. Here, we performed differential gene expression analysis and weighted gene co-expression network analysis (WGCNA) to identify significant genes and specific modules related to BMI based on gene expression profile data of 7 discordant monozygotic twins. In the differential gene expression analysis, it appeared that 32 differentially expressed genes (DEGs) were with a trend of up-regulation in twins with higher BMI when compared to their siblings. Categories of positive regulation of nitric-oxide synthase biosynthetic process, positive regulation of NF-kappa B import into nucleus, and peroxidase activity were significantly enriched within GO database and NF-kappa B signaling pathway within KEGG database. DEGs of NAMPT, TLR9, PTGS2, HBD, and PCSK1N might be associated with obesity. In the WGCNA, among the total 20 distinct co-expression modules identified, coral1 module (68 genes) had the strongest positive correlation with BMI (r = 0.56, P = 0.04) and disease status (r = 0.56, P = 0.04). Categories of positive regulation of phospholipase activity, high-density lipoprotein particle clearance, chylomicron remnant clearance, reverse cholesterol transport, intermediate-density lipoprotein particle, chylomicron, low-density lipoprotein particle, very-low-density lipoprotein particle, voltage-gated potassium channel complex, cholesterol transporter activity, and neuropeptide hormone activity were significantly enriched within GO database for this module. And alcoholism and cell adhesion molecules pathways were significantly enriched within KEGG database. Several hub genes, such as GAL, ASB9, NPPB, TBX2, IL17C, APOE, ABCG4, and APOC2 were also identified. The module eigengene of saddlebrown module (212 genes) was also significantly correlated with BMI (r = 0.56, P = 0.04), and hub genes of KCNN1 and AQP10 were differentially expressed. We identified significant genes and specific modules potentially related to BMI based on the gene expression profile data of monozygotic twins. The findings may help further elucidate the underlying mechanisms of obesity development and provide novel insights to research potential gene biomarkers and signaling pathways for obesity treatment. Further analysis and validation of the findings reported here are important and necessary when more sample size is acquired.

Databases in the Area of Pharmacogenetics

PubMed Central

Sim, Sarah C.; Altman, Russ B.; Ingelman-Sundberg, Magnus

2012-01-01

In the area of pharmacogenetics and personalized health care it is obvious that databases, providing important information of the occurrence and consequences of variant genes encoding drug metabolizing enzymes, drug transporters, drug targets, and other proteins of importance for drug response or toxicity, are of critical value for scientists, physicians, and industry. The primary outcome of the pharmacogenomic field is the identification of biomarkers that can predict drug toxicity and drug response, thereby individualizing and improving drug treatment of patients. The drug in question and the polymorphic gene exerting the impact are the main issues to be searched for in the databases. Here, we review the databases that provide useful information in this respect, of benefit for the development of the pharmacogenomic field. PMID:21309040

Identification of Novel Tissue-Specific Genes by Analysis of Microarray Databases: A Human and Mouse Model

PubMed Central

Suh, Yeunsu; Davis, Michael E.; Lee, Kichoon

2013-01-01

Understanding the tissue-specific pattern of gene expression is critical in elucidating the molecular mechanisms of tissue development, gene function, and transcriptional regulations of biological processes. Although tissue-specific gene expression information is available in several databases, follow-up strategies to integrate and use these data are limited. The objective of the current study was to identify and evaluate novel tissue-specific genes in human and mouse tissues by performing comparative microarray database analysis and semi-quantitative PCR analysis. We developed a powerful approach to predict tissue-specific genes by analyzing existing microarray data from the NCBI′s Gene Expression Omnibus (GEO) public repository. We investigated and confirmed tissue-specific gene expression in the human and mouse kidney, liver, lung, heart, muscle, and adipose tissue. Applying our novel comparative microarray approach, we confirmed 10 kidney, 11 liver, 11 lung, 11 heart, 8 muscle, and 8 adipose specific genes. The accuracy of this approach was further verified by employing semi-quantitative PCR reaction and by searching for gene function information in existing publications. Three novel tissue-specific genes were discovered by this approach including AMDHD1 (amidohydrolase domain containing 1) in the liver, PRUNE2 (prune homolog 2) in the heart, and ACVR1C (activin A receptor, type IC) in adipose tissue. We further confirmed the tissue-specific expression of these 3 novel genes by real-time PCR. Among them, ACVR1C is adipose tissue-specific and adipocyte-specific in adipose tissue, and can be used as an adipocyte developmental marker. From GEO profiles, we predicted the processes in which AMDHD1 and PRUNE2 may participate. Our approach provides a novel way to identify new sets of tissue-specific genes and to predict functions in which they may be involved. PMID:23741331

HIVsirDB: a database of HIV inhibiting siRNAs.

PubMed

Tyagi, Atul; Ahmed, Firoz; Thakur, Nishant; Sharma, Arun; Raghava, Gajendra P S; Kumar, Manoj

2011-01-01

Human immunodeficiency virus (HIV) is responsible for millions of deaths every year. The current treatment involves the use of multiple antiretroviral agents that may harm patients due to their toxic nature. RNA interference (RNAi) is a potent candidate for the future treatment of HIV, uses short interfering RNA (siRNA/shRNA) for silencing HIV genes. In this study, attempts have been made to create a database HIVsirDB of siRNAs responsible for silencing HIV genes. HIVsirDB is a manually curated database of HIV inhibiting siRNAs that provides comprehensive information about each siRNA or shRNA. Information was collected and compiled from literature and public resources. This database contains around 750 siRNAs that includes 75 partially complementary siRNAs differing by one or more bases with the target sites and over 100 escape mutant sequences. HIVsirDB structure contains sixteen fields including siRNA sequence, HIV strain, targeted genome region, efficacy and conservation of target sequences. In order to facilitate user, many tools have been integrated in this database that includes; i) siRNAmap for mapping siRNAs on target sequence, ii) HIVsirblast for BLAST search against database, iii) siRNAalign for aligning siRNAs. HIVsirDB is a freely accessible database of siRNAs which can silence or degrade HIV genes. It covers 26 types of HIV strains and 28 cell types. This database will be very useful for developing models for predicting efficacy of HIV inhibiting siRNAs. In summary this is a useful resource for researchers working in the field of siRNA based HIV therapy. HIVsirDB database is accessible at http://crdd.osdd.net/raghava/hivsir/.

Genome-wide identification of lineage-specific genes in Arabidopsis, Oryza and Populus

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Xiaohan; Jawdy, Sara; Tschaplinski, Timothy J

2009-01-01

Protein sequences were compared among Arabidopsis, Oryza and Populus to identify differential gene (DG) sets that are in one but not the other two genomes. The DG sets were screened against a plant transcript database, the NR protein database and six newly-sequenced genomes (Carica, Glycine, Medicago, Sorghum, Vitis and Zea) to identify a set of species-specific genes (SS). Gene expression, protein motif and intron number were examined. 192, 641 and 109 SS genes were identified in Arabidopsis, Oryza and Populus, respectively. Some SS genes were preferentially expressed in flowers, roots, xylem and cambium or up-regulated by stress. Six conserved motifsmore » in Arabidopsis and Oryza SS proteins were found in other distant lineages. The SS gene sets were enriched with intronless genes. The results reflect functional and/or anatomical differences between monocots and eudicots or between herbaceous and woody plants. The Populus-specific genes are candidates for carbon sequestration and biofuel research.« less

Whole Transcriptome Analysis Provides Insights into Molecular Mechanisms for Molting in Litopenaeus vannamei

PubMed Central

Gao, Yi; Zhang, Xiaojun; Wei, Jiankai; Sun, Xiaoqing; Yuan, Jianbo; Li, Fuhua; Xiang, Jianhai

2015-01-01

Molting is one of the most important biological processes in shrimp growth and development. All shrimp undergo cyclic molting periodically to shed and replace their exoskeletons. This process is essential for growth, metamorphosis, and reproduction in shrimp. However, the molecular mechanisms underlying shrimp molting remain poorly understood. In this study, we investigated global expression changes in the transcriptomes of the Pacific white shrimp, Litopenaeus vannamei, the most commonly cultured shrimp species worldwide. The transcriptome of whole L. vannamei was investigated by RNA-sequencing (RNA-seq) throughout the molting cycle, including the inter-molt (C), pre-molt (D0, D1, D2, D3, D4), and post-molt (P1 and P2) stages, and 93,756 unigenes were identified. Among these genes, we identified 5,117 genes differentially expressed (log2ratio ≥1 and FDR ≤0.001) in adjacent molt stages. The results were compared against the National Center for Biotechnology Information (NCBI) non-redundant protein/nucleotide sequence database, Swiss-Prot, PFAM database, the Gene Ontology database, and the Kyoto Encyclopedia of Genes and Genomes database in order to annotate gene descriptions, associate them with gene ontology terms, and assign them to pathways. The expression patterns for genes involved in several molecular events critical for molting, such as hormone regulation, triggering events, implementation phases, skelemin, immune responses were characterized and considered as mechanisms underlying molting in L. vannamei. Comparisons with transcriptomic analyses in other arthropods were also performed. The characterization of major transcriptional changes in genes involved in the molting cycle provides candidates for future investigation of the molecular mechanisms. The data generated in this study will serve as an important transcriptomic resource for the shrimp research community to facilitate gene and genome annotation and to characterize key molecular processes underlying shrimp development. PMID:26650402

Molecular signatures database (MSigDB) 3.0.

PubMed

Liberzon, Arthur; Subramanian, Aravind; Pinchback, Reid; Thorvaldsdóttir, Helga; Tamayo, Pablo; Mesirov, Jill P

2011-06-15

Well-annotated gene sets representing the universe of the biological processes are critical for meaningful and insightful interpretation of large-scale genomic data. The Molecular Signatures Database (MSigDB) is one of the most widely used repositories of such sets. We report the availability of a new version of the database, MSigDB 3.0, with over 6700 gene sets, a complete revision of the collection of canonical pathways and experimental signatures from publications, enhanced annotations and upgrades to the web site. MSigDB is freely available for non-commercial use at http://www.broadinstitute.org/msigdb.

New tools and methods for direct programmatic access to the dbSNP relational database.

PubMed

Saccone, Scott F; Quan, Jiaxi; Mehta, Gaurang; Bolze, Raphael; Thomas, Prasanth; Deelman, Ewa; Tischfield, Jay A; Rice, John P

2011-01-01

Genome-wide association studies often incorporate information from public biological databases in order to provide a biological reference for interpreting the results. The dbSNP database is an extensive source of information on single nucleotide polymorphisms (SNPs) for many different organisms, including humans. We have developed free software that will download and install a local MySQL implementation of the dbSNP relational database for a specified organism. We have also designed a system for classifying dbSNP tables in terms of common tasks we wish to accomplish using the database. For each task we have designed a small set of custom tables that facilitate task-related queries and provide entity-relationship diagrams for each task composed from the relevant dbSNP tables. In order to expose these concepts and methods to a wider audience we have developed web tools for querying the database and browsing documentation on the tables and columns to clarify the relevant relational structure. All web tools and software are freely available to the public at http://cgsmd.isi.edu/dbsnpq. Resources such as these for programmatically querying biological databases are essential for viably integrating biological information into genetic association experiments on a genome-wide scale.

The MAR databases: development and implementation of databases specific for marine metagenomics

PubMed Central

Klemetsen, Terje; Raknes, Inge A; Fu, Juan; Agafonov, Alexander; Balasundaram, Sudhagar V; Tartari, Giacomo; Robertsen, Espen

2018-01-01

Abstract We introduce the marine databases; MarRef, MarDB and MarCat (https://mmp.sfb.uit.no/databases/), which are publicly available resources that promote marine research and innovation. These data resources, which have been implemented in the Marine Metagenomics Portal (MMP) (https://mmp.sfb.uit.no/), are collections of richly annotated and manually curated contextual (metadata) and sequence databases representing three tiers of accuracy. While MarRef is a database for completely sequenced marine prokaryotic genomes, which represent a marine prokaryote reference genome database, MarDB includes all incomplete sequenced prokaryotic genomes regardless level of completeness. The last database, MarCat, represents a gene (protein) catalog of uncultivable (and cultivable) marine genes and proteins derived from marine metagenomics samples. The first versions of MarRef and MarDB contain 612 and 3726 records, respectively. Each record is built up of 106 metadata fields including attributes for sampling, sequencing, assembly and annotation in addition to the organism and taxonomic information. Currently, MarCat contains 1227 records with 55 metadata fields. Ontologies and controlled vocabularies are used in the contextual databases to enhance consistency. The user-friendly web interface lets the visitors browse, filter and search in the contextual databases and perform BLAST searches against the corresponding sequence databases. All contextual and sequence databases are freely accessible and downloadable from https://s1.sfb.uit.no/public/mar/. PMID:29106641

NeuroTransDB: highly curated and structured transcriptomic metadata for neurodegenerative diseases.

PubMed

Bagewadi, Shweta; Adhikari, Subash; Dhrangadhariya, Anjani; Irin, Afroza Khanam; Ebeling, Christian; Namasivayam, Aishwarya Alex; Page, Matthew; Hofmann-Apitius, Martin; Senger, Philipp

2015-01-01

Neurodegenerative diseases are chronic debilitating conditions, characterized by progressive loss of neurons that represent a significant health care burden as the global elderly population continues to grow. Over the past decade, high-throughput technologies such as the Affymetrix GeneChip microarrays have provided new perspectives into the pathomechanisms underlying neurodegeneration. Public transcriptomic data repositories, namely Gene Expression Omnibus and curated ArrayExpress, enable researchers to conduct integrative meta-analysis; increasing the power to detect differentially regulated genes in disease and explore patterns of gene dysregulation across biologically related studies. The reliability of retrospective, large-scale integrative analyses depends on an appropriate combination of related datasets, in turn requiring detailed meta-annotations capturing the experimental setup. In most cases, we observe huge variation in compliance to defined standards for submitted metadata in public databases. Much of the information to complete, or refine meta-annotations are distributed in the associated publications. For example, tissue preparation or comorbidity information is frequently described in an article's supplementary tables. Several value-added databases have employed additional manual efforts to overcome this limitation. However, none of these databases explicate annotations that distinguish human and animal models in neurodegeneration context. Therefore, adopting a more specific disease focus, in combination with dedicated disease ontologies, will better empower the selection of comparable studies with refined annotations to address the research question at hand. In this article, we describe the detailed development of NeuroTransDB, a manually curated database containing metadata annotations for neurodegenerative studies. The database contains more than 20 dimensions of metadata annotations within 31 mouse, 5 rat and 45 human studies, defined in collaboration with domain disease experts. We elucidate the step-by-step guidelines used to critically prioritize studies from public archives and their metadata curation and discuss the key challenges encountered. Curated metadata for Alzheimer's disease gene expression studies are available for download. Database URL: www.scai.fraunhofer.de/NeuroTransDB.html. © The Author(s) 2015. Published by Oxford University Press.

NeuroTransDB: highly curated and structured transcriptomic metadata for neurodegenerative diseases

PubMed Central

Bagewadi, Shweta; Adhikari, Subash; Dhrangadhariya, Anjani; Irin, Afroza Khanam; Ebeling, Christian; Namasivayam, Aishwarya Alex; Page, Matthew; Hofmann-Apitius, Martin

2015-01-01

Neurodegenerative diseases are chronic debilitating conditions, characterized by progressive loss of neurons that represent a significant health care burden as the global elderly population continues to grow. Over the past decade, high-throughput technologies such as the Affymetrix GeneChip microarrays have provided new perspectives into the pathomechanisms underlying neurodegeneration. Public transcriptomic data repositories, namely Gene Expression Omnibus and curated ArrayExpress, enable researchers to conduct integrative meta-analysis; increasing the power to detect differentially regulated genes in disease and explore patterns of gene dysregulation across biologically related studies. The reliability of retrospective, large-scale integrative analyses depends on an appropriate combination of related datasets, in turn requiring detailed meta-annotations capturing the experimental setup. In most cases, we observe huge variation in compliance to defined standards for submitted metadata in public databases. Much of the information to complete, or refine meta-annotations are distributed in the associated publications. For example, tissue preparation or comorbidity information is frequently described in an article’s supplementary tables. Several value-added databases have employed additional manual efforts to overcome this limitation. However, none of these databases explicate annotations that distinguish human and animal models in neurodegeneration context. Therefore, adopting a more specific disease focus, in combination with dedicated disease ontologies, will better empower the selection of comparable studies with refined annotations to address the research question at hand. In this article, we describe the detailed development of NeuroTransDB, a manually curated database containing metadata annotations for neurodegenerative studies. The database contains more than 20 dimensions of metadata annotations within 31 mouse, 5 rat and 45 human studies, defined in collaboration with domain disease experts. We elucidate the step-by-step guidelines used to critically prioritize studies from public archives and their metadata curation and discuss the key challenges encountered. Curated metadata for Alzheimer’s disease gene expression studies are available for download. Database URL: www.scai.fraunhofer.de/NeuroTransDB.html PMID:26475471

The Gene Expression Omnibus Database.

PubMed

Clough, Emily; Barrett, Tanya

2016-01-01

The Gene Expression Omnibus (GEO) database is an international public repository that archives and freely distributes high-throughput gene expression and other functional genomics data sets. Created in 2000 as a worldwide resource for gene expression studies, GEO has evolved with rapidly changing technologies and now accepts high-throughput data for many other data applications, including those that examine genome methylation, chromatin structure, and genome-protein interactions. GEO supports community-derived reporting standards that specify provision of several critical study elements including raw data, processed data, and descriptive metadata. The database not only provides access to data for tens of thousands of studies, but also offers various Web-based tools and strategies that enable users to locate data relevant to their specific interests, as well as to visualize and analyze the data. This chapter includes detailed descriptions of methods to query and download GEO data and use the analysis and visualization tools. The GEO homepage is at http://www.ncbi.nlm.nih.gov/geo/.

Estrogen alters the profile of the transcriptome in river snail Bellamya aeruginosa.

PubMed

Lei, Kun; Liu, Ruizhi; An, Li-Hui; Luo, Ying-Feng; LeBlanc, Gerald A

2015-03-01

We evaluated the transcriptome dynamics of the freshwater river snail Bellamya aeruginosa exposed to 17β-estradiol (E2) using the Roche/454 GS-FLX platform. In total, 41,869 unigenes, with an average length of 586 bp, representing 36,181 contigs and 5,688 singlets were obtained. Among them, 18.08, 36.85, and 25.47 % matched sequences in the GenBank non-redundant nucleic acid database, non-redundant protein database, and Swiss protein database, respectively. Annotation of the unigenes with gene ontology, and then mapping them to biological pathways, revealed large groups of genes related to growth, development, reproduction, signal transduction, and defense mechanisms. Significant differences were found in gene expression in both liver and testicular tissues between control and E2-exposed organisms. These changes in gene expression will help in understanding the molecular mechanisms of the response to physiological stress in the river snail exposed to estrogen, and will facilitate research into biological processes and underlying physiological adaptations to xenoestrogen exposure in gastropods.

PubSearch and PubFetch: a simple management system for semiautomated retrieval and annotation of biological information from the literature.

PubMed

Yoo, Danny; Xu, Iris; Berardini, Tanya Z; Rhee, Seung Yon; Narayanasamy, Vijay; Twigger, Simon

2006-03-01

For most systems in biology, a large body of literature exists that describes the complexity of the system based on experimental results. Manual review of this literature to extract targeted information into biological databases is difficult and time consuming. To address this problem, we developed PubSearch and PubFetch, which store literature, keyword, and gene information in a relational database, index the literature with keywords and gene names, and provide a Web user interface for annotating the genes from experimental data found in the associated literature. A set of protocols is provided in this unit for installing, populating, running, and using PubSearch and PubFetch. In addition, we provide support protocols for performing controlled vocabulary annotations. Intended users of PubSearch and PubFetch are database curators and biology researchers interested in tracking the literature and capturing information about genes of interest in a more effective way than with conventional spreadsheets and lab notebooks.

The Gene Expression Omnibus database

PubMed Central

Clough, Emily; Barrett, Tanya

2016-01-01

The Gene Expression Omnibus (GEO) database is an international public repository that archives and freely distributes high-throughput gene expression and other functional genomics data sets. Created in 2000 as a worldwide resource for gene expression studies, GEO has evolved with rapidly changing technologies and now accepts high-throughput data for many other data applications, including those that examine genome methylation, chromatin structure, and genome–protein interactions. GEO supports community-derived reporting standards that specify provision of several critical study elements including raw data, processed data, and descriptive metadata. The database not only provides access to data for tens of thousands of studies, but also offers various Web-based tools and strategies that enable users to locate data relevant to their specific interests, as well as to visualize and analyze the data. This chapter includes detailed descriptions of methods to query and download GEO data and use the analysis and visualization tools. The GEO homepage is at http://www.ncbi.nlm.nih.gov/geo/. PMID:27008011

Online Mendelian Inheritance in Man (OMIM), a knowledgebase of human genes and genetic disorders.

PubMed

Hamosh, Ada; Scott, Alan F; Amberger, Joanna S; Bocchini, Carol A; McKusick, Victor A

2005-01-01

Online Mendelian Inheritance in Man (OMIM) is a comprehensive, authoritative and timely knowledgebase of human genes and genetic disorders compiled to support human genetics research and education and the practice of clinical genetics. Started by Dr Victor A. McKusick as the definitive reference Mendelian Inheritance in Man, OMIM (http://www.ncbi.nlm.nih.gov/omim/) is now distributed electronically by the National Center for Biotechnology Information, where it is integrated with the Entrez suite of databases. Derived from the biomedical literature, OMIM is written and edited at Johns Hopkins University with input from scientists and physicians around the world. Each OMIM entry has a full-text summary of a genetically determined phenotype and/or gene and has numerous links to other genetic databases such as DNA and protein sequence, PubMed references, general and locus-specific mutation databases, HUGO nomenclature, MapViewer, GeneTests, patient support groups and many others. OMIM is an easy and straightforward portal to the burgeoning information in human genetics.

Database of cattle candidate genes and genetic markers for milk production and mastitis

PubMed Central

Ogorevc, J; Kunej, T; Razpet, A; Dovc, P

2009-01-01

A cattle database of candidate genes and genetic markers for milk production and mastitis has been developed to provide an integrated research tool incorporating different types of information supporting a genomic approach to study lactation, udder development and health. The database contains 943 genes and genetic markers involved in mammary gland development and function, representing candidates for further functional studies. The candidate loci were drawn on a genetic map to reveal positional overlaps. For identification of candidate loci, data from seven different research approaches were exploited: (i) gene knockouts or transgenes in mice that result in specific phenotypes associated with mammary gland (143 loci); (ii) cattle QTL for milk production (344) and mastitis related traits (71); (iii) loci with sequence variations that show specific allele-phenotype interactions associated with milk production (24) or mastitis (10) in cattle; (iv) genes with expression profiles associated with milk production (207) or mastitis (107) in cattle or mouse; (v) cattle milk protein genes that exist in different genetic variants (9); (vi) miRNAs expressed in bovine mammary gland (32) and (vii) epigenetically regulated cattle genes associated with mammary gland function (1). Fourty-four genes found by multiple independent analyses were suggested as the most promising candidates and were further in silico analysed for expression levels in lactating mammary gland, genetic variability and top biological functions in functional networks. A miRNA target search for mammary gland expressed miRNAs identified 359 putative binding sites in 3′UTRs of candidate genes. PMID:19508288

Identification of functional enolase genes of the silkworm Bombyx mori from public databases with a combination of dry and wet bench processes.

PubMed

Kikuchi, Akira; Nakazato, Takeru; Ito, Katsuhiko; Nojima, Yosui; Yokoyama, Takeshi; Iwabuchi, Kikuo; Bono, Hidemasa; Toyoda, Atsushi; Fujiyama, Asao; Sato, Ryoichi; Tabunoki, Hiroko

2017-01-13

Various insect species have been added to genomic databases over the years. Thus, researchers can easily obtain online genomic information on invertebrates and insects. However, many incorrectly annotated genes are included in these databases, which can prevent the correct interpretation of subsequent functional analyses. To address this problem, we used a combination of dry and wet bench processes to select functional genes from public databases. Enolase is an important glycolytic enzyme in all organisms. We used a combination of dry and wet bench processes to identify functional enolases in the silkworm Bombyx mori (BmEno). First, we detected five annotated enolases from public databases using a Hidden Markov Model (HMM) search, and then through cDNA cloning, Northern blotting, and RNA-seq analysis, we revealed three functional enolases in B. mori: BmEno1, BmEno2, and BmEnoC. BmEno1 contained a conserved key amino acid residue for metal binding and substrate binding in other species. However, BmEno2 and BmEnoC showed a change in this key amino acid. Phylogenetic analysis showed that BmEno2 and BmEnoC were distinct from BmEno1 and other enolases, and were distributed only in lepidopteran clusters. BmEno1 was expressed in all of the tissues used in our study. In contrast, BmEno2 was mainly expressed in the testis with some expression in the ovary and suboesophageal ganglion. BmEnoC was weakly expressed in the testis. Quantitative RT-PCR showed that the mRNA expression of BmEno2 and BmEnoC correlated with testis development; thus, BmEno2 and BmEnoC may be related to lepidopteran-specific spermiogenesis. We identified and characterized three functional enolases from public databases with a combination of dry and wet bench processes in the silkworm B. mori. In addition, we determined that BmEno2 and BmEnoC had species-specific functions. Our strategy could be helpful for the detection of minor genes and functional genes in non-model organisms from public databases.

ATGC database and ATGC-COGs: an updated resource for micro- and macro-evolutionary studies of prokaryotic genomes and protein family annotation

PubMed Central

Kristensen, David M.; Wolf, Yuri I.; Koonin, Eugene V.

2017-01-01

The Alignable Tight Genomic Clusters (ATGCs) database is a collection of closely related bacterial and archaeal genomes that provides several tools to aid research into evolutionary processes in the microbial world. Each ATGC is a taxonomy-independent cluster of 2 or more completely sequenced genomes that meet the objective criteria of a high degree of local gene order (synteny) and a small number of synonymous substitutions in the protein-coding genes. As such, each ATGC is suited for analysis of microevolutionary variations within a cohesive group of organisms (e.g. species), whereas the entire collection of ATGCs is useful for macroevolutionary studies. The ATGC database includes many forms of pre-computed data, in particular ATGC-COGs (Clusters of Orthologous Genes), multiple sequence alignments, a set of ‘index’ orthologs representing the most well-conserved members of each ATGC-COG, the phylogenetic tree of the organisms within each ATGC, etc. Although the ATGC database contains several million proteins from thousands of genomes organized into hundreds of clusters (roughly a 4-fold increase since the last version of the ATGC database), it is now built with completely automated methods and will be regularly updated following new releases of the NCBI RefSeq database. The ATGC database is hosted jointly at the University of Iowa at dmk-brain.ecn.uiowa.edu/ATGC/ and the NCBI at ftp.ncbi.nlm.nih.gov/pub/kristensen/ATGC/atgc_home.html. PMID:28053163

cMapper: gene-centric connectivity mapper for EBI-RDF platform.

PubMed

Shoaib, Muhammad; Ansari, Adnan Ahmad; Ahn, Sung-Min

2017-01-15

In this era of biological big data, data integration has become a common task and a challenge for biologists. The Resource Description Framework (RDF) was developed to enable interoperability of heterogeneous datasets. The EBI-RDF platform enables an efficient data integration of six independent biological databases using RDF technologies and shared ontologies. However, to take advantage of this platform, biologists need to be familiar with RDF technologies and SPARQL query language. To overcome this practical limitation of the EBI-RDF platform, we developed cMapper, a web-based tool that enables biologists to search the EBI-RDF databases in a gene-centric manner without a thorough knowledge of RDF and SPARQL. cMapper allows biologists to search data entities in the EBI-RDF platform that are connected to genes or small molecules of interest in multiple biological contexts. The input to cMapper consists of a set of genes or small molecules, and the output are data entities in six independent EBI-RDF databases connected with the given genes or small molecules in the user's query. cMapper provides output to users in the form of a graph in which nodes represent data entities and the edges represent connections between data entities and inputted set of genes or small molecules. Furthermore, users can apply filters based on database, taxonomy, organ and pathways in order to focus on a core connectivity graph of their interest. Data entities from multiple databases are differentiated based on background colors. cMapper also enables users to investigate shared connections between genes or small molecules of interest. Users can view the output graph on a web browser or download it in either GraphML or JSON formats. cMapper is available as a web application with an integrated MySQL database. The web application was developed using Java and deployed on Tomcat server. We developed the user interface using HTML5, JQuery and the Cytoscape Graph API. cMapper can be accessed at http://cmapper.ewostech.net Readers can download the development manual from the website http://cmapper.ewostech.net/docs/cMapperDocumentation.pdf. Source Code is available at https://github.com/muhammadshoaib/cmapperContact:smahn@gachon.ac.krSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

AOP-DB Frontend: A user interface for the Adverse Outcome Pathways Database.

EPA Science Inventory

The EPA Adverse Outcome Pathway Database (AOP-DB) is a database resource that aggregates association relationships between AOPs, genes, chemicals, diseases, pathways, species orthology information, ontologies. The AOP-DB frontend is a simple yet powerful AOP-DB user interface in...

AOP-DB Frontend: A user interface for the Adverse Outcome Pathways Database

EPA Science Inventory

The EPA Adverse Outcome Pathway Database (AOP-DB) is a database resource that aggregates association relationships between AOPs, genes, chemicals, diseases, pathways, species orthology information, ontologies. The AOP-DB frontend is a simple yet powerful user interface in the for...

An expression database for roots of the model legume Medicago truncatula under salt stress

PubMed Central

2009-01-01

Background Medicago truncatula is a model legume whose genome is currently being sequenced by an international consortium. Abiotic stresses such as salt stress limit plant growth and crop productivity, including those of legumes. We anticipate that studies on M. truncatula will shed light on other economically important legumes across the world. Here, we report the development of a database called MtED that contains gene expression profiles of the roots of M. truncatula based on time-course salt stress experiments using the Affymetrix Medicago GeneChip. Our hope is that MtED will provide information to assist in improving abiotic stress resistance in legumes. Description The results of our microarray experiment with roots of M. truncatula under 180 mM sodium chloride were deposited in the MtED database. Additionally, sequence and annotation information regarding microarray probe sets were included. MtED provides functional category analysis based on Gene and GeneBins Ontology, and other Web-based tools for querying and retrieving query results, browsing pathways and transcription factor families, showing metabolic maps, and comparing and visualizing expression profiles. Utilities like mapping probe sets to genome of M. truncatula and In-Silico PCR were implemented by BLAT software suite, which were also available through MtED database. Conclusion MtED was built in the PHP script language and as a MySQL relational database system on a Linux server. It has an integrated Web interface, which facilitates ready examination and interpretation of the results of microarray experiments. It is intended to help in selecting gene markers to improve abiotic stress resistance in legumes. MtED is available at http://bioinformatics.cau.edu.cn/MtED/. PMID:19906315

An expression database for roots of the model legume Medicago truncatula under salt stress.

PubMed

Li, Daofeng; Su, Zhen; Dong, Jiangli; Wang, Tao

2009-11-11

Medicago truncatula is a model legume whose genome is currently being sequenced by an international consortium. Abiotic stresses such as salt stress limit plant growth and crop productivity, including those of legumes. We anticipate that studies on M. truncatula will shed light on other economically important legumes across the world. Here, we report the development of a database called MtED that contains gene expression profiles of the roots of M. truncatula based on time-course salt stress experiments using the Affymetrix Medicago GeneChip. Our hope is that MtED will provide information to assist in improving abiotic stress resistance in legumes. The results of our microarray experiment with roots of M. truncatula under 180 mM sodium chloride were deposited in the MtED database. Additionally, sequence and annotation information regarding microarray probe sets were included. MtED provides functional category analysis based on Gene and GeneBins Ontology, and other Web-based tools for querying and retrieving query results, browsing pathways and transcription factor families, showing metabolic maps, and comparing and visualizing expression profiles. Utilities like mapping probe sets to genome of M. truncatula and In-Silico PCR were implemented by BLAT software suite, which were also available through MtED database. MtED was built in the PHP script language and as a MySQL relational database system on a Linux server. It has an integrated Web interface, which facilitates ready examination and interpretation of the results of microarray experiments. It is intended to help in selecting gene markers to improve abiotic stress resistance in legumes. MtED is available at http://bioinformatics.cau.edu.cn/MtED/.

DoOPSearch: a web-based tool for finding and analysing common conserved motifs in the promoter regions of different chordate and plant genes

PubMed Central

Sebestyén, Endre; Nagy, Tibor; Suhai, Sándor; Barta, Endre

2009-01-01

Background The comparative genomic analysis of a large number of orthologous promoter regions of the chordate and plant genes from the DoOP databases shows thousands of conserved motifs. Most of these motifs differ from any known transcription factor binding site (TFBS). To identify common conserved motifs, we need a specific tool to be able to search amongst them. Since conserved motifs from the DoOP databases are linked to genes, the result of such a search can give a list of genes that are potentially regulated by the same transcription factor(s). Results We have developed a new tool called DoOPSearch for the analysis of the conserved motifs in the promoter regions of chordate or plant genes. We used the orthologous promoters of the DoOP database to extract thousands of conserved motifs from different taxonomic groups. The advantage of this approach is that different sets of conserved motifs might be found depending on how broad the taxonomic coverage of the underlying orthologous promoter sequence collection is (consider e.g. primates vs. mammals or Brassicaceae vs. Viridiplantae). The DoOPSearch tool allows the users to search these motif collections or the promoter regions of DoOP with user supplied query sequences or any of the conserved motifs from the DoOP database. To find overrepresented gene ontologies, the gene lists obtained can be analysed further using a modified version of the GeneMerge program. Conclusion We present here a comparative genomics based promoter analysis tool. Our system is based on a unique collection of conserved promoter motifs characteristic of different taxonomic groups. We offer both a command line and a web-based tool for searching in these motif collections using user specified queries. These can be either short promoter sequences or consensus sequences of known transcription factor binding sites. The GeneMerge analysis of the search results allows the user to identify statistically overrepresented Gene Ontology terms that might provide a clue on the function of the motifs and genes. PMID:19534755

PhamDB: a web-based application for building Phamerator databases.

PubMed

Lamine, James G; DeJong, Randall J; Nelesen, Serita M

2016-07-01

PhamDB is a web application which creates databases of bacteriophage genes, grouped by gene similarity. It is backwards compatible with the existing Phamerator desktop software while providing an improved database creation workflow. Key features include a graphical user interface, validation of uploaded GenBank files, and abilities to import phages from existing databases, modify existing databases and queue multiple jobs. Source code and installation instructions for Linux, Windows and Mac OSX are freely available at https://github.com/jglamine/phage PhamDB is also distributed as a docker image which can be managed via Kitematic. This docker image contains the application and all third party software dependencies as a pre-configured system, and is freely available via the installation instructions provided. snelesen@calvin.edu. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

GreenPhylDB v2.0: comparative and functional genomics in plants.

PubMed

Rouard, Mathieu; Guignon, Valentin; Aluome, Christelle; Laporte, Marie-Angélique; Droc, Gaëtan; Walde, Christian; Zmasek, Christian M; Périn, Christophe; Conte, Matthieu G

2011-01-01

GreenPhylDB is a database designed for comparative and functional genomics based on complete genomes. Version 2 now contains sixteen full genomes of members of the plantae kingdom, ranging from algae to angiosperms, automatically clustered into gene families. Gene families are manually annotated and then analyzed phylogenetically in order to elucidate orthologous and paralogous relationships. The database offers various lists of gene families including plant, phylum and species specific gene families. For each gene cluster or gene family, easy access to gene composition, protein domains, publications, external links and orthologous gene predictions is provided. Web interfaces have been further developed to improve the navigation through information related to gene families. New analysis tools are also available, such as a gene family ontology browser that facilitates exploration. GreenPhylDB is a component of the South Green Bioinformatics Platform (http://southgreen.cirad.fr/) and is accessible at http://greenphyl.cirad.fr. It enables comparative genomics in a broad taxonomy context to enhance the understanding of evolutionary processes and thus tends to speed up gene discovery.

Constitutive equations for the cyclic behaviour of short carbon fibre-reinforced thermoplastics and identification on a uniaxial database

NASA Astrophysics Data System (ADS)

Leveuf, Louis; Navrátil, Libor; Le Saux, Vincent; Marco, Yann; Olhagaray, Jérôme; Leclercq, Sylvain

2018-01-01

A constitutive model for the cyclic behaviour of short carbon fibre-reinforced thermoplastics for aeronautical applications is proposed. First, an extended experimental database is generated in order to highlight the specificities of the studied material. This database is composed of complex tests and is used to design a relevant constitutive model able to capture the cyclic behaviour of the material. A general 3D formulation of the model is then proposed, and an identification strategy is defined to identify its parameters. Finally, a validation of the identification is performed by challenging the prediction of the model to the tests that were not used for the identification. An excellent agreement between the numerical results and the experimental data is observed revealing the capabilities of the model.

Quantitative comparison of microarray experiments with published leukemia related gene expression signatures.

PubMed

Klein, Hans-Ulrich; Ruckert, Christian; Kohlmann, Alexander; Bullinger, Lars; Thiede, Christian; Haferlach, Torsten; Dugas, Martin

2009-12-15

Multiple gene expression signatures derived from microarray experiments have been published in the field of leukemia research. A comparison of these signatures with results from new experiments is useful for verification as well as for interpretation of the results obtained. Currently, the percentage of overlapping genes is frequently used to compare published gene signatures against a signature derived from a new experiment. However, it has been shown that the percentage of overlapping genes is of limited use for comparing two experiments due to the variability of gene signatures caused by different array platforms or assay-specific influencing parameters. Here, we present a robust approach for a systematic and quantitative comparison of published gene expression signatures with an exemplary query dataset. A database storing 138 leukemia-related published gene signatures was designed. Each gene signature was manually annotated with terms according to a leukemia-specific taxonomy. Two analysis steps are implemented to compare a new microarray dataset with the results from previous experiments stored and curated in the database. First, the global test method is applied to assess gene signatures and to constitute a ranking among them. In a subsequent analysis step, the focus is shifted from single gene signatures to chromosomal aberrations or molecular mutations as modeled in the taxonomy. Potentially interesting disease characteristics are detected based on the ranking of gene signatures associated with these aberrations stored in the database. Two example analyses are presented. An implementation of the approach is freely available as web-based application. The presented approach helps researchers to systematically integrate the knowledge derived from numerous microarray experiments into the analysis of a new dataset. By means of example leukemia datasets we demonstrate that this approach detects related experiments as well as related molecular mutations and may help to interpret new microarray data.

The Comparative Toxicogenomics Database (CTD): A Resource for Comparative Toxicological Studies

PubMed Central

CJ, Mattingly; MC, Rosenstein; GT, Colby; JN, Forrest; JL, Boyer

2006-01-01

The etiology of most chronic diseases involves interactions between environmental factors and genes that modulate important biological processes (Olden and Wilson, 2000). We are developing the publicly available Comparative Toxicogenomics Database (CTD) to promote understanding about the effects of environmental chemicals on human health. CTD identifies interactions between chemicals and genes and facilitates cross-species comparative studies of these genes. The use of diverse animal models and cross-species comparative sequence studies has been critical for understanding basic physiological mechanisms and gene and protein functions. Similarly, these approaches will be valuable for exploring the molecular mechanisms of action of environmental chemicals and the genetic basis of differential susceptibility. PMID:16902965

Sequencing of cDNA Clones from the Genetic Map of Tomato (Lycopersicon esculentum)

PubMed Central

Ganal, Martin W.; Czihal, Rosemarie; Hannappel, Ulrich; Kloos, Dorothee-U.; Polley, Andreas; Ling, Hong-Qing

1998-01-01

The dense RFLP linkage map of tomato (Lycopersicon esculentum) contains >300 anonymous cDNA clones. Of those clones, 272 were partially or completely sequenced. The sequences were compared at the DNA and protein level to known genes in databases. For 57% of the clones, a significant match to previously described genes was found. The information will permit the conversion of those markers to STS markers and allow their use in PCR-based mapping experiments. Furthermore, it will facilitate the comparative mapping of genes across distantly related plant species by direct comparison of DNA sequences and map positions. [cDNA sequence data reported in this paper have been submitted to the EMBL database under accession nos. AA824695–AA825005 and the dbEST_Id database under accession nos. 1546519–1546862.] PMID:9724330

Micro-optical coherence tomography tracking of magnetic gene transfection via Au-Fe3O4 dumbbell nanoparticles

NASA Astrophysics Data System (ADS)

Shi, Wei; Liu, Xinyu; Wei, Chao; Xu, Zhichuan J.; Sim, Stanley Siong Wei; Liu, Linbo; Xu, Chenjie

2015-10-01

Heterogeneous Au-Fe3O4 dumbbell nanoparticles (NPs) are composed of Au NPs and Fe3O4 NPs that bring in optical and magnetic properties respectively. This article reports the engineering of Au-Fe3O4 NPs as gene carriers for magnetic gene transfection as well as contrast agents for micro-optical coherence tomography (μOCT). As a proof-of-concept, Au-Fe3O4 NPs are used to deliver the green fluorescent protein to HEK 293T cells and their entrance into the cells is monitored through μOCT.Heterogeneous Au-Fe3O4 dumbbell nanoparticles (NPs) are composed of Au NPs and Fe3O4 NPs that bring in optical and magnetic properties respectively. This article reports the engineering of Au-Fe3O4 NPs as gene carriers for magnetic gene transfection as well as contrast agents for micro-optical coherence tomography (μOCT). As a proof-of-concept, Au-Fe3O4 NPs are used to deliver the green fluorescent protein to HEK 293T cells and their entrance into the cells is monitored through μOCT. Electronic supplementary information (ESI) available. See DOI: 10.1039/c5nr05459a

Dictionary-driven prokaryotic gene finding.

PubMed

Shibuya, Tetsuo; Rigoutsos, Isidore

2002-06-15

Gene identification, also known as gene finding or gene recognition, is among the important problems of molecular biology that have been receiving increasing attention with the advent of large scale sequencing projects. Previous strategies for solving this problem can be categorized into essentially two schools of thought: one school employs sequence composition statistics, whereas the other relies on database similarity searches. In this paper, we propose a new gene identification scheme that combines the best characteristics from each of these two schools. In particular, our method determines gene candidates among the ORFs that can be identified in a given DNA strand through the use of the Bio-Dictionary, a database of patterns that covers essentially all of the currently available sample of the natural protein sequence space. Our approach relies entirely on the use of redundant patterns as the agents on which the presence or absence of genes is predicated and does not employ any additional evidence, e.g. ribosome-binding site signals. The Bio-Dictionary Gene Finder (BDGF), the algorithm's implementation, is a single computational engine able to handle the gene identification task across distinct archaeal and bacterial genomes. The engine exhibits performance that is characterized by simultaneous very high values of sensitivity and specificity, and a high percentage of correctly predicted start sites. Using a collection of patterns derived from an old (June 2000) release of the Swiss-Prot/TrEMBL database that contained 451 602 proteins and fragments, we demonstrate our method's generality and capabilities through an extensive analysis of 17 complete archaeal and bacterial genomes. Examples of previously unreported genes are also shown and discussed in detail.

The gene expression database for mouse development (GXD): putting developmental expression information at your fingertips.

PubMed

Smith, Constance M; Finger, Jacqueline H; Kadin, James A; Richardson, Joel E; Ringwald, Martin

2014-10-01

Because molecular mechanisms of development are extraordinarily complex, the understanding of these processes requires the integration of pertinent research data. Using the Gene Expression Database for Mouse Development (GXD) as an example, we illustrate the progress made toward this goal, and discuss relevant issues that apply to developmental databases and developmental research in general. Since its first release in 1998, GXD has served the scientific community by integrating multiple types of expression data from publications and electronic submissions and by making these data freely and widely available. Focusing on endogenous gene expression in wild-type and mutant mice and covering data from RNA in situ hybridization, in situ reporter (knock-in), immunohistochemistry, reverse transcriptase-polymerase chain reaction, Northern blot, and Western blot experiments, the database has grown tremendously over the years in terms of data content and search utilities. Currently, GXD includes over 1.4 million annotated expression results and over 260,000 images. All these data and images are readily accessible to many types of database searches. Here we describe the data and search tools of GXD; explain how to use the database most effectively; discuss how we acquire, curate, and integrate developmental expression information; and describe how the research community can help in this process. Copyright © 2014 The Authors Developmental Dynamics published by Wiley Periodicals, Inc. on behalf of American Association of Anatomists.

The Plant Structure Ontology, a Unified Vocabulary of Anatomy and Morphology of a Flowering Plant1[W][OA

PubMed Central

Ilic, Katica; Kellogg, Elizabeth A.; Jaiswal, Pankaj; Zapata, Felipe; Stevens, Peter F.; Vincent, Leszek P.; Avraham, Shulamit; Reiser, Leonore; Pujar, Anuradha; Sachs, Martin M.; Whitman, Noah T.; McCouch, Susan R.; Schaeffer, Mary L.; Ware, Doreen H.; Stein, Lincoln D.; Rhee, Seung Y.

2007-01-01

Formal description of plant phenotypes and standardized annotation of gene expression and protein localization data require uniform terminology that accurately describes plant anatomy and morphology. This facilitates cross species comparative studies and quantitative comparison of phenotypes and expression patterns. A major drawback is variable terminology that is used to describe plant anatomy and morphology in publications and genomic databases for different species. The same terms are sometimes applied to different plant structures in different taxonomic groups. Conversely, similar structures are named by their species-specific terms. To address this problem, we created the Plant Structure Ontology (PSO), the first generic ontological representation of anatomy and morphology of a flowering plant. The PSO is intended for a broad plant research community, including bench scientists, curators in genomic databases, and bioinformaticians. The initial releases of the PSO integrated existing ontologies for Arabidopsis (Arabidopsis thaliana), maize (Zea mays), and rice (Oryza sativa); more recent versions of the ontology encompass terms relevant to Fabaceae, Solanaceae, additional cereal crops, and poplar (Populus spp.). Databases such as The Arabidopsis Information Resource, Nottingham Arabidopsis Stock Centre, Gramene, MaizeGDB, and SOL Genomics Network are using the PSO to describe expression patterns of genes and phenotypes of mutants and natural variants and are regularly contributing new annotations to the Plant Ontology database. The PSO is also used in specialized public databases, such as BRENDA, GENEVESTIGATOR, NASCArrays, and others. Over 10,000 gene annotations and phenotype descriptions from participating databases can be queried and retrieved using the Plant Ontology browser. The PSO, as well as contributed gene associations, can be obtained at www.plantontology.org. PMID:17142475

Graph Databases for Large-Scale Healthcare Systems: A Framework for Efficient Data Management and Data Services

DOE Office of Scientific and Technical Information (OSTI.GOV)

Park, Yubin; Shankar, Mallikarjun; Park, Byung H.

Designing a database system for both efficient data management and data services has been one of the enduring challenges in the healthcare domain. In many healthcare systems, data services and data management are often viewed as two orthogonal tasks; data services refer to retrieval and analytic queries such as search, joins, statistical data extraction, and simple data mining algorithms, while data management refers to building error-tolerant and non-redundant database systems. The gap between service and management has resulted in rigid database systems and schemas that do not support effective analytics. We compose a rich graph structure from an abstracted healthcaremore » RDBMS to illustrate how we can fill this gap in practice. We show how a healthcare graph can be automatically constructed from a normalized relational database using the proposed 3NF Equivalent Graph (3EG) transformation.We discuss a set of real world graph queries such as finding self-referrals, shared providers, and collaborative filtering, and evaluate their performance over a relational database and its 3EG-transformed graph. Experimental results show that the graph representation serves as multiple de-normalized tables, thus reducing complexity in a database and enhancing data accessibility of users. Based on this finding, we propose an ensemble framework of databases for healthcare applications.« less

From 20th century metabolic wall charts to 21st century systems biology: database of mammalian metabolic enzymes.

PubMed

Corcoran, Callan C; Grady, Cameron R; Pisitkun, Trairak; Parulekar, Jaya; Knepper, Mark A

2017-03-01

The organization of the mammalian genome into gene subsets corresponding to specific functional classes has provided key tools for systems biology research. Here, we have created a web-accessible resource called the Mammalian Metabolic Enzyme Database ( https://hpcwebapps.cit.nih.gov/ESBL/Database/MetabolicEnzymes/MetabolicEnzymeDatabase.html) keyed to the biochemical reactions represented on iconic metabolic pathway wall charts created in the previous century. Overall, we have mapped 1,647 genes to these pathways, representing ~7 percent of the protein-coding genome. To illustrate the use of the database, we apply it to the area of kidney physiology. In so doing, we have created an additional database ( Database of Metabolic Enzymes in Kidney Tubule Segments: https://hpcwebapps.cit.nih.gov/ESBL/Database/MetabolicEnzymes/), mapping mRNA abundance measurements (mined from RNA-Seq studies) for all metabolic enzymes to each of 14 renal tubule segments. We carry out bioinformatics analysis of the enzyme expression pattern among renal tubule segments and mine various data sources to identify vasopressin-regulated metabolic enzymes in the renal collecting duct. Copyright © 2017 the American Physiological Society.

The 24th annual Nucleic Acids Research database issue: a look back and upcoming changes

PubMed Central

Rigden, Daniel J

2017-01-01

Abstract This year's Database Issue of Nucleic Acids Research contains 152 papers that include descriptions of 54 new databases and update papers on 98 databases, of which 16 have not been previously featured in NAR. As always, these databases cover a broad range of molecular biology subjects, including genome structure, gene expression and its regulation, proteins, protein domains, and protein–protein interactions. Following the recent trend, an increasing number of new and established databases deal with the issues of human health, from cancer-causing mutations to drugs and drug targets. In accordance with this trend, three recently compiled databases that have been selected by NAR reviewers and editors as ‘breakthrough’ contributions, denovo-db, the Monarch Initiative, and Open Targets, cover human de novo gene variants, disease-related phenotypes in model organisms, and a bioinformatics platform for therapeutic target identification and validation, respectively. We expect these databases to attract the attention of numerous researchers working in various areas of genetics and genomics. Looking back at the past 12 years, we present here the ‘golden set’ of databases that have consistently served as authoritative, comprehensive, and convenient data resources widely used by the entire community and offer some lessons on what makes a successful database. The Database Issue is freely available online at the https://academic.oup.com/nar web site. An updated version of the NAR Molecular Biology Database Collection is available at http://www.oxfordjournals.org/nar/database/a/. PMID:28053160

Gene function prediction with gene interaction networks: a context graph kernel approach.

PubMed

Li, Xin; Chen, Hsinchun; Li, Jiexun; Zhang, Zhu

2010-01-01

Predicting gene functions is a challenge for biologists in the postgenomic era. Interactions among genes and their products compose networks that can be used to infer gene functions. Most previous studies adopt a linkage assumption, i.e., they assume that gene interactions indicate functional similarities between connected genes. In this study, we propose to use a gene's context graph, i.e., the gene interaction network associated with the focal gene, to infer its functions. In a kernel-based machine-learning framework, we design a context graph kernel to capture the information in context graphs. Our experimental study on a testbed of p53-related genes demonstrates the advantage of using indirect gene interactions and shows the empirical superiority of the proposed approach over linkage-assumption-based methods, such as the algorithm to minimize inconsistent connected genes and diffusion kernels.

An Integrated Molecular Database on Indian Insects.

PubMed

Pratheepa, Maria; Venkatesan, Thiruvengadam; Gracy, Gandhi; Jalali, Sushil Kumar; Rangheswaran, Rajagopal; Antony, Jomin Cruz; Rai, Anil

2018-01-01

MOlecular Database on Indian Insects (MODII) is an online database linking several databases like Insect Pest Info, Insect Barcode Information System (IBIn), Insect Whole Genome sequence, Other Genomic Resources of National Bureau of Agricultural Insect Resources (NBAIR), Whole Genome sequencing of Honey bee viruses, Insecticide resistance gene database and Genomic tools. This database was developed with a holistic approach for collecting information about phenomic and genomic information of agriculturally important insects. This insect resource database is available online for free at http://cib.res.in. http://cib.res.in/.

Comparative Transcriptional Analysis of Loquat Fruit Identifies Major Signal Networks Involved in Fruit Development and Ripening Process.

PubMed

Song, Huwei; Zhao, Xiangxiang; Hu, Weicheng; Wang, Xinfeng; Shen, Ting; Yang, Liming

2016-11-04

Loquat ( Eriobotrya japonica Lindl.) is an important non-climacteric fruit and rich in essential nutrients such as minerals and carotenoids. During fruit development and ripening, thousands of the differentially expressed genes (DEGs) from various metabolic pathways cause a series of physiological and biochemical changes. To better understand the underlying mechanism of fruit development, the Solexa/Illumina RNA-seq high-throughput sequencing was used to evaluate the global changes of gene transcription levels. More than 51,610,234 high quality reads from ten runs of fruit development were sequenced and assembled into 48,838 unigenes. Among 3256 DEGs, 2304 unigenes could be annotated to the Gene Ontology database. These DEGs were distributed into 119 pathways described in the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. A large number of DEGs were involved in carbohydrate metabolism, hormone signaling, and cell-wall degradation. The real-time reverse transcription (qRT)-PCR analyses revealed that several genes related to cell expansion, auxin signaling and ethylene response were differentially expressed during fruit development. Other members of transcription factor families were also identified. There were 952 DEGs considered as novel genes with no annotation in any databases. These unigenes will serve as an invaluable genetic resource for loquat molecular breeding and postharvest storage.

Release of (and lessons learned from mining) a pioneering large toxicogenomics database.

PubMed

Sandhu, Komal S; Veeramachaneni, Vamsi; Yao, Xiang; Nie, Alex; Lord, Peter; Amaratunga, Dhammika; McMillian, Michael K; Verheyen, Geert R

2015-07-01

We release the Janssen Toxicogenomics database. This rat liver gene-expression database was generated using Codelink microarrays, and has been used over the past years within Janssen to derive signatures for multiple end points and to classify proprietary compounds. The release consists of gene-expression responses to 124 compounds, selected to give a broad coverage of liver-active compounds. A selection of the compounds were also analyzed on Affymetrix microarrays. The release includes results of an in-house reannotation pipeline to Entrez gene annotations, to classify probes into different confidence classes. High confidence unambiguously annotated probes were used to create gene-level data which served as starting point for cross-platform comparisons. Connectivity map-based similarity methods show excellent agreement between Codelink and Affymetrix runs of the same samples. We also compared our dataset with the Japanese Toxicogenomics Project and observed reasonable agreement, especially for compounds with stronger gene signatures. We describe an R-package containing the gene-level data and show how it can be used for expression-based similarity searches. Comparing the same biological samples run on the Affymetrix and the Codelink platform, good correspondence is observed using connectivity mapping approaches. As expected, this correspondence is smaller when the data are compared with an independent dataset such as TG-GATE. We hope that this collection of gene-expression profiles will be incorporated in toxicogenomics pipelines of users.

Combining Evidence of Preferential Gene-Tissue Relationships from Multiple Sources

PubMed Central

Guo, Jing; Hammar, Mårten; Öberg, Lisa; Padmanabhuni, Shanmukha S.; Bjäreland, Marcus; Dalevi, Daniel

2013-01-01

An important challenge in drug discovery and disease prognosis is to predict genes that are preferentially expressed in one or a few tissues, i.e. showing a considerably higher expression in one tissue(s) compared to the others. Although several data sources and methods have been published explicitly for this purpose, they often disagree and it is not evident how to retrieve these genes and how to distinguish true biological findings from those that are due to choice-of-method and/or experimental settings. In this work we have developed a computational approach that combines results from multiple methods and datasets with the aim to eliminate method/study-specific biases and to improve the predictability of preferentially expressed human genes. A rule-based score is used to merge and assign support to the results. Five sets of genes with known tissue specificity were used for parameter pruning and cross-validation. In total we identify 3434 tissue-specific genes. We compare the genes of highest scores with the public databases: PaGenBase (microarray), TiGER (EST) and HPA (protein expression data). The results have 85% overlap to PaGenBase, 71% to TiGER and only 28% to HPA. 99% of our predictions have support from at least one of these databases. Our approach also performs better than any of the databases on identifying drug targets and biomarkers with known tissue-specificity. PMID:23950964

Pleurochrysome: A Web Database of Pleurochrysis Transcripts and Orthologs Among Heterogeneous Algae

PubMed Central

Fujiwara, Shoko; Takatsuka, Yukiko; Hirokawa, Yasutaka; Tsuzuki, Mikio; Takano, Tomoyuki; Kobayashi, Masaaki; Suda, Kunihiro; Asamizu, Erika; Yokoyama, Koji; Shibata, Daisuke; Tabata, Satoshi; Yano, Kentaro

2016-01-01

Pleurochrysis is a coccolithophorid genus, which belongs to the Coccolithales in the Haptophyta. The genus has been used extensively for biological research, together with Emiliania in the Isochrysidales, to understand distinctive features between the two coccolithophorid-including orders. However, molecular biological research on Pleurochrysis such as elucidation of the molecular mechanism behind coccolith formation has not made great progress at least in part because of lack of comprehensive gene information. To provide such information to the research community, we built an open web database, the Pleurochrysome (http://bioinf.mind.meiji.ac.jp/phapt/), which currently stores 9,023 unique gene sequences (designated as UNIGENEs) assembled from expressed sequence tag sequences of P. haptonemofera as core information. The UNIGENEs were annotated with gene sequences sharing significant homology, conserved domains, Gene Ontology, KEGG Orthology, predicted subcellular localization, open reading frames and orthologous relationship with genes of 10 other algal species, a cyanobacterium and the yeast Saccharomyces cerevisiae. This sequence and annotation information can be easily accessed via several search functions. Besides fundamental functions such as BLAST and keyword searches, this database also offers search functions to explore orthologous genes in the 12 organisms and to seek novel genes. The Pleurochrysome will promote molecular biological and phylogenetic research on coccolithophorids and other haptophytes by helping scientists mine data from the primary transcriptome of P. haptonemofera. PMID:26746174

Taking It to the Streets: Mobile CD-ROM Workshops on Campus.

ERIC Educational Resources Information Center

Parker-Gibson, Necia

1994-01-01

Librarians at the University of Arkansas (Fayetteville) offer CD-ROM database and online catalog training using a portable unit composed of a laptop computer, modem, LCD panel, and overhead projector. This unit allows librarians to make presentations to large groups and to demonstrate to faculty and students the relevancy of library technology.…

The Ned IIS project - forest ecosystem management

Treesearch

W. Potter; D. Nute; J. Wang; F. Maier; Michael Twery; H. Michael Rauscher; P. Knopp; S. Thomasma; M. Dass; H. Uchiyama

2002-01-01

For many years we have held to the notion that an Intelligent Information System (IIS) is composed of a unified knowledge base, database, and model base. The main idea behind this notion is the transparent processing of user queries. The system is responsible for "deciding" which information sources to access in order to fulfil a query regardless of whether...

NED-IIS: An Intelligent Information System for Forest Ecosystem Management

Treesearch

W.D. Potter; S. Somasekar; R. Kommineni; H.M. Rauscher

1999-01-01

We view Intelligent Information System (IIS) as composed of a unified knowledge base, database, and model base. The model base includes decision support models, forecasting models, and cvsualization models for example. In addition, we feel that the model base should include domain specific porblems solving modules as well as decision support models. This, then,...

Review of the Composability Problem for System Evaluation

DTIC Science & Technology

2004-11-01

burden estimate or any other aspect of this collection of information, including suggestions for reducing this burden, to Washington Headquarters Services ...directory services (e.g., the Lightweight Directory Access Protocol (LDAP)), authentication (e.g., Kerberos), databases, user interface (e.g...exemplifies this type of development, by its use of commercial components and systems for authentication, access management, directory services

Music Interventions for Children with Autism: Narrative Review of the Literature

ERIC Educational Resources Information Center

Simpson, Kate; Keen, Deb

2011-01-01

It is widely reported that music can be beneficial to individuals with autism. This review was undertaken to determine the evidence base for the use of music as an intervention for children with autism. After searching relevant databases, 128 articles were identified of which 20 articles met the study's inclusion criteria. Composed songs and…

Feature genes in metastatic breast cancer identified by MetaDE and SVM classifier methods.

PubMed

Tuo, Youlin; An, Ning; Zhang, Ming

2018-03-01

The aim of the present study was to investigate the feature genes in metastatic breast cancer samples. A total of 5 expression profiles of metastatic breast cancer samples were downloaded from the Gene Expression Omnibus database, which were then analyzed using the MetaQC and MetaDE packages in R language. The feature genes between metastasis and non‑metastasis samples were screened under the threshold of P<0.05. Based on the protein‑protein interactions (PPIs) in the Biological General Repository for Interaction Datasets, Human Protein Reference Database and Biomolecular Interaction Network Database, the PPI network of the feature genes was constructed. The feature genes identified by topological characteristics were then used for support vector machine (SVM) classifier training and verification. The accuracy of the SVM classifier was then evaluated using another independent dataset from The Cancer Genome Atlas database. Finally, function and pathway enrichment analyses for genes in the SVM classifier were performed. A total of 541 feature genes were identified between metastatic and non‑metastatic samples. The top 10 genes with the highest betweenness centrality values in the PPI network of feature genes were Nuclear RNA Export Factor 1, cyclin‑dependent kinase 2 (CDK2), myelocytomatosis proto‑oncogene protein (MYC), Cullin 5, SHC Adaptor Protein 1, Clathrin heavy chain, Nucleolin, WD repeat domain 1, proteasome 26S subunit non‑ATPase 2 and telomeric repeat binding factor 2. The cyclin‑dependent kinase inhibitor 1A (CDKN1A), E2F transcription factor 1 (E2F1), and MYC interacted with CDK2. The SVM classifier constructed by the top 30 feature genes was able to distinguish metastatic samples from non‑metastatic samples [correct rate, specificity, positive predictive value and negative predictive value >0.89; sensitivity >0.84; area under the receiver operating characteristic curve (AUROC) >0.96]. The verification of the SVM classifier in an independent dataset (35 metastatic samples and 143 non‑metastatic samples) revealed an accuracy of 94.38% and AUROC of 0.958. Cell cycle associated functions and pathways were the most significant terms of the 30 feature genes. A SVM classifier was constructed to assess the possibility of breast cancer metastasis, which presented high accuracy in several independent datasets. CDK2, CDKN1A, E2F1 and MYC were indicated as the potential feature genes in metastatic breast cancer.

Software and database for the analysis of mutations in the human FBN1 gene.

PubMed Central

Collod, G; Béroud, C; Soussi, T; Junien, C; Boileau, C

1996-01-01

Fibrillin is the major component of extracellular microfibrils. Mutations in the fibrillin gene on chromosome 15 (FBN1) were described at first in the heritable connective tissue disorder, Marfan syndrome (MFS). More recently, FBN1 has also been shown to harbor mutations related to a spectrum of conditions phenotypically related to MFS and many mutations will have to be accumulated before genotype/phenotype relationships emerge. To facilitate mutational analysis of the FBN1 gene, a software package along with a computerized database (currently listing 63 entries) have been created. PMID:8594563

LAILAPS: the plant science search engine.

PubMed

Esch, Maria; Chen, Jinbo; Colmsee, Christian; Klapperstück, Matthias; Grafahrend-Belau, Eva; Scholz, Uwe; Lange, Matthias

2015-01-01

With the number of sequenced plant genomes growing, the number of predicted genes and functional annotations is also increasing. The association between genes and phenotypic traits is currently of great interest. Unfortunately, the information available today is widely scattered over a number of different databases. Information retrieval (IR) has become an all-encompassing bioinformatics methodology for extracting knowledge from complex, heterogeneous and distributed databases, and therefore can be a useful tool for obtaining a comprehensive view of plant genomics, from genes to traits. Here we describe LAILAPS (http://lailaps.ipk-gatersleben.de), an IR system designed to link plant genomic data in the context of phenotypic attributes for a detailed forward genetic research. LAILAPS comprises around 65 million indexed documents, encompassing >13 major life science databases with around 80 million links to plant genomic resources. The LAILAPS search engine allows fuzzy querying for candidate genes linked to specific traits over a loosely integrated system of indexed and interlinked genome databases. Query assistance and an evidence-based annotation system enable time-efficient and comprehensive information retrieval. An artificial neural network incorporating user feedback and behavior tracking allows relevance sorting of results. We fully describe LAILAPS's functionality and capabilities by comparing this system's performance with other widely used systems and by reporting both a validation in maize and a knowledge discovery use-case focusing on candidate genes in barley. © The Author 2014. Published by Oxford University Press on behalf of Japanese Society of Plant Physiologists.

MicroRNA Gene Regulatory Networks in Peripheral Nerve Sheath Tumors

DTIC Science & Technology

2012-09-01

chondrosarcoma are identified based on the unique histology, cell of origin, clinical features and site distribution. The following are the major... Chondrosarcoma Chondrosarcoma is a cancer composed of cells derived from transformed cells that produce cartilage. Peripheral chondrosarcoma is a malignant...biosynthesis. This is in line with gene expression analyses previously performed in osteochondroma and chondrosarcoma samples showing modulation of

Draft Genome Sequence of Mycobacterium neoaurum Strain DSM 44074T.

PubMed

Phelippeau, Michael; Robert, Catherine; Croce, Olivier; Raoult, Didier; Drancourt, Michel

2014-07-10

We report the draft genome sequence of Mycobacterium neoaurum strain DSM 44074(T), a nontuberculosis species responsible for opportunistic infections in immunocompromised patients. The strain described here is composed of 5,536,033 bp, with a G+C content of 66.24%, and carries 5,274 protein-coding genes and 72 RNA genes. Copyright © 2014 Phelippeau et al.

High-Throughput Sequence Analysis of Turbot (Scophthalmus maximus) Transcriptome Using 454-Pyrosequencing for the Discovery of Antiviral Immune Genes

PubMed Central

Pereiro, Patricia; Balseiro, Pablo; Romero, Alejandro; Dios, Sonia; Forn-Cuni, Gabriel; Fuste, Berta; Planas, Josep V.; Beltran, Sergi; Novoa, Beatriz; Figueras, Antonio

2012-01-01

Background Turbot (Scophthalmus maximus L.) is an important aquacultural resource both in Europe and Asia. However, there is little information on gene sequences available in public databases. Currently, one of the main problems affecting the culture of this flatfish is mortality due to several pathogens, especially viral diseases which are not treatable. In order to identify new genes involved in immune defense, we conducted 454-pyrosequencing of the turbot transcriptome after different immune stimulations. Methodology/Principal Findings Turbot were injected with viral stimuli to increase the expression level of immune-related genes. High-throughput deep sequencing using 454-pyrosequencing technology yielded 915,256 high-quality reads. These sequences were assembled into 55,404 contigs that were subjected to annotation steps. Intriguingly, 55.16% of the deduced protein was not significantly similar to any sequences in the databases used for the annotation and only 0.85% of the BLASTx top-hits matched S. maximus protein sequences. This relatively low level of annotation is possibly due to the limited information for this specie and other flatfish in the database. These results suggest the identification of a large number of new genes in turbot and in fish in general. A more detailed analysis showed the presence of putative members of several innate and specific immune pathways. Conclusions/Significance To our knowledge, this study is the first transcriptome analysis using 454-pyrosequencing for turbot. Previously, there were only 12,471 EST and less of 1,500 nucleotide sequences for S. maximus in NCBI database. Our results provide a rich source of data (55,404 contigs and 181,845 singletons) for discovering and identifying new genes, which will serve as a basis for microarray construction, gene expression characterization and for identification of genetic markers to be used in several applications. Immune stimulation in turbot was very effective, obtaining an enormous variety of sequences belonging to genes involved in the defense mechanisms. PMID:22629298

DNetDB: The human disease network database based on dysfunctional regulation mechanism.

PubMed

Yang, Jing; Wu, Su-Juan; Yang, Shao-You; Peng, Jia-Wei; Wang, Shi-Nuo; Wang, Fu-Yan; Song, Yu-Xing; Qi, Ting; Li, Yi-Xue; Li, Yuan-Yuan

2016-05-21

Disease similarity study provides new insights into disease taxonomy, pathogenesis, which plays a guiding role in diagnosis and treatment. The early studies were limited to estimate disease similarities based on clinical manifestations, disease-related genes, medical vocabulary concepts or registry data, which were inevitably biased to well-studied diseases and offered small chance of discovering novel findings in disease relationships. In other words, genome-scale expression data give us another angle to address this problem since simultaneous measurement of the expression of thousands of genes allows for the exploration of gene transcriptional regulation, which is believed to be crucial to biological functions. Although differential expression analysis based methods have the potential to explore new disease relationships, it is difficult to unravel the upstream dysregulation mechanisms of diseases. We therefore estimated disease similarities based on gene expression data by using differential coexpression analysis, a recently emerging method, which has been proved to be more potential to capture dysfunctional regulation mechanisms than differential expression analysis. A total of 1,326 disease relationships among 108 diseases were identified, and the relevant information constituted the human disease network database (DNetDB). Benefiting from the use of differential coexpression analysis, the potential common dysfunctional regulation mechanisms shared by disease pairs (i.e. disease relationships) were extracted and presented. Statistical indicators, common disease-related genes and drugs shared by disease pairs were also included in DNetDB. In total, 1,326 disease relationships among 108 diseases, 5,598 pathways, 7,357 disease-related genes and 342 disease drugs are recorded in DNetDB, among which 3,762 genes and 148 drugs are shared by at least two diseases. DNetDB is the first database focusing on disease similarity from the viewpoint of gene regulation mechanism. It provides an easy-to-use web interface to search and browse the disease relationships and thus helps to systematically investigate etiology and pathogenesis, perform drug repositioning, and design novel therapeutic interventions.Database URL: http://app.scbit.org/DNetDB/ #.

Proteomic Analysis and Identification of the Structural and Regulatory Proteins of the Rhodobacter capsulatus Gene Transfer Agent

PubMed Central

Chen, Frank; Spano, Anthony; Goodman, Benjamin E.; Blasier, Kiev R.; Sabat, Agnes; Jeffery, Erin; Norris, Andrew; Shabanowitz, Jeffrey; Hunt, Donald F.; Lebedev, Nikolai

2010-01-01

The gene transfer agent of Rhodobacter capsulatus (GTA) is a unique phage-like particle that exchanges genetic information between members of this same species of bacterium. Besides being an excellent tool for genetic mapping, the GTA has a number of advantages for biotechnological and nanoengineering purposes. To facilitate the GTA purification and identify the proteins involved in GTA expression, assembly and regulation, in the present work we construct and transform into R. capsulatus Y262 a gene coding for a C-terminally His-tagged capsid protein. The constructed protein was expressed in the cells, assembled into chimeric GTA particles inside the cells and excreted from the cells into surrounding medium. Transmission electron micrographs of phosphotungstate-stained, NiNTA-purified chimeric GTA confirm that its structure is similar to normal GTA particles, with many particles composed both of a head and a tail. The mass spectrometric proteomic analysis of polypeptides present in the GTA recovered outside the cells shows that GTA is composed of at least 9 proteins represented in the GTA gene cluster including proteins coded for by Orf’s 3, 5, 6–9, 11, 13, and 15. PMID:19105630

Proteomic analysis and identification of the structural and regulatory proteins of the Rhodobacter capsulatus gene transfer agent.

PubMed

Chen, Frank; Spano, Anthony; Goodman, Benjamin E; Blasier, Kiev R; Sabat, Agnes; Jeffery, Erin; Norris, Andrew; Shabanowitz, Jeffrey; Hunt, Donald F; Lebedev, Nikolai

2009-02-01

The gene transfer agent of Rhodobacter capsulatus (GTA) is a unique phage-like particle that exchanges genetic information between members of this same species of bacterium. Besides being an excellent tool for genetic mapping, the GTA has a number of advantages for biotechnological and nanoengineering purposes. To facilitate the GTA purification and identify the proteins involved in GTA expression, assembly and regulation, in the present work we construct and transform into R. capsulatus Y262 a gene coding for a C-terminally His-tagged capsid protein. The constructed protein was expressed in the cells, assembled into chimeric GTA particles inside the cells and excreted from the cells into surrounding medium. Transmission electron micrographs of phosphotungstate-stained, NiNTA-purified chimeric GTA confirm that its structure is similar to normal GTA particles, with many particles composed both of a head and a tail. The mass spectrometric proteomic analysis of polypeptides present in the GTA recovered outside the cells shows that GTA is composed of at least 9 proteins represented in the GTA gene cluster including proteins coded for by Orf's 3, 5, 6-9, 11, 13, and 15.

Analysis of gene expression profile microarray data in complex regional pain syndrome.

PubMed

Tan, Wulin; Song, Yiyan; Mo, Chengqiang; Jiang, Shuangjian; Wang, Zhongxing

2017-09-01

The aim of the present study was to predict key genes and proteins associated with complex regional pain syndrome (CRPS) using bioinformatics analysis. The gene expression profiling microarray data, GSE47603, which included peripheral blood samples from 4 patients with CRPS and 5 healthy controls, was obtained from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) in CRPS patients compared with healthy controls were identified using the GEO2R online tool. Functional enrichment analysis was then performed using The Database for Annotation Visualization and Integrated Discovery online tool. Protein‑protein interaction (PPI) network analysis was subsequently performed using Search Tool for the Retrieval of Interaction Genes database and analyzed with Cytoscape software. A total of 257 DEGs were identified, including 243 upregulated genes and 14 downregulated ones. Genes in the human leukocyte antigen (HLA) family were most significantly differentially expressed. Enrichment analysis demonstrated that signaling pathways, including immune response, cell motion, adhesion and angiogenesis were associated with CRPS. PPI network analysis revealed that key genes, including early region 1A binding protein p300 (EP300), CREB‑binding protein (CREBBP), signal transducer and activator of transcription (STAT)3, STAT5A and integrin α M were associated with CRPS. The results suggest that the immune response may therefore serve an important role in CRPS development. In addition, genes in the HLA family, such as HLA‑DQB1 and HLA‑DRB1, may present potential biomarkers for the diagnosis of CRPS. Furthermore, EP300, its paralog CREBBP, and the STAT family genes, STAT3 and STAT5 may be important in the development of CRPS.

MicroRNA expression, target genes, and signaling pathways in infants with a ventricular septal defect.

PubMed

Chai, Hui; Yan, Zhaoyuan; Huang, Ke; Jiang, Yuanqing; Zhang, Lin

2018-02-01

This study aimed to systematically investigate the relationship between miRNA expression and the occurrence of ventricular septal defect (VSD), and characterize the miRNA target genes and pathways that can lead to VSD. The miRNAs that were differentially expressed in blood samples from VSD and normal infants were screened and validated by implementing miRNA microarrays and qRT-PCR. The target genes regulated by differentially expressed miRNAs were predicted using three target gene databases. The functions and signaling pathways of the target genes were enriched using the GO database and KEGG database, respectively. The transcription and protein expression of specific target genes in critical pathways were compared in the VSD and normal control groups using qRT-PCR and western blotting, respectively. Compared with the normal control group, the VSD group had 22 differentially expressed miRNAs; 19 were downregulated and three were upregulated. The 10,677 predicted target genes participated in many biological functions related to cardiac development and morphogenesis. Four target genes (mGLUR, Gq, PLC, and PKC) were involved in the PKC pathway and four (ECM, FAK, PI3 K, and PDK1) were involved in the PI3 K-Akt pathway. The transcription and protein expression of these eight target genes were significantly upregulated in the VSD group. The 22 miRNAs that were dysregulated in the VSD group were mainly downregulated, which may result in the dysregulation of several key genes and biological functions related to cardiac development. These effects could also be exerted via the upregulation of eight specific target genes, the subsequent over-activation of the PKC and PI3 K-Akt pathways, and the eventual abnormal cardiac development and VSD.

Errors in CGAP xProfiler and cDNA DGED: the importance of library parsing and gene selection algorithms.

PubMed

Milnthorpe, Andrew T; Soloviev, Mikhail

2011-04-15

The Cancer Genome Anatomy Project (CGAP) xProfiler and cDNA Digital Gene Expression Displayer (DGED) have been made available to the scientific community over a decade ago and since then were used widely to find genes which are differentially expressed between cancer and normal tissues. The tissue types are usually chosen according to the ontology hierarchy developed by NCBI. The xProfiler uses an internally available flat file database to determine the presence or absence of genes in the chosen libraries, while cDNA DGED uses the publicly available UniGene Expression and Gene relational databases to count the sequences found for each gene in the presented libraries. We discovered that the CGAP approach often includes libraries from dependent or irrelevant tissues (one third of libraries were incorrect on average, with some tissue searches no correct libraries being selected at all). We also discovered that the CGAP approach reported genes from outside the selected libraries and may omit genes found within the libraries. Other errors include the incorrect estimation of the significance values and inaccurate settings for the library size cut-off values. We advocated a revised approach to finding libraries associated with tissues. In doing so, libraries from dependent or irrelevant tissues do not get included in the final library pool. We also revised the method for determining the presence or absence of a gene by searching the UniGene relational database, revised calculation of statistical significance and sorted the library cut-off filter. Our results justify re-evaluation of all previously reported results where NCBI CGAP expression data and tools were used.

Errors in CGAP xProfiler and cDNA DGED: the importance of library parsing and gene selection algorithms

PubMed Central

2011-01-01

Background The Cancer Genome Anatomy Project (CGAP) xProfiler and cDNA Digital Gene Expression Displayer (DGED) have been made available to the scientific community over a decade ago and since then were used widely to find genes which are differentially expressed between cancer and normal tissues. The tissue types are usually chosen according to the ontology hierarchy developed by NCBI. The xProfiler uses an internally available flat file database to determine the presence or absence of genes in the chosen libraries, while cDNA DGED uses the publicly available UniGene Expression and Gene relational databases to count the sequences found for each gene in the presented libraries. Results We discovered that the CGAP approach often includes libraries from dependent or irrelevant tissues (one third of libraries were incorrect on average, with some tissue searches no correct libraries being selected at all). We also discovered that the CGAP approach reported genes from outside the selected libraries and may omit genes found within the libraries. Other errors include the incorrect estimation of the significance values and inaccurate settings for the library size cut-off values. We advocated a revised approach to finding libraries associated with tissues. In doing so, libraries from dependent or irrelevant tissues do not get included in the final library pool. We also revised the method for determining the presence or absence of a gene by searching the UniGene relational database, revised calculation of statistical significance and sorted the library cut-off filter. Conclusion Our results justify re-evaluation of all previously reported results where NCBI CGAP expression data and tools were used. PMID:21496233

Sequencing artifacts in the type A influenza database and attempts to correct them

USDA-ARS?s Scientific Manuscript database

Currently over 300,000 Type A influenza gene sequences representing over 50,000 strains are available in publicly available databases. However, the quality of the sequences submitted are determined by the contributor and many sequence errors are present in the databases, which can affect the result...

BioImaging Database

DOE Office of Scientific and Technical Information (OSTI.GOV)

David Nix, Lisa Simirenko

2006-10-25

The Biolmaging Database (BID) is a relational database developed to store the data and meta-data for the 3D gene expression in early Drosophila embryo development on a cellular level. The schema was written to be used with the MySQL DBMS but with minor modifications can be used on any SQL compliant relational DBMS.

The porcine translational research database: A manually curated, genomics and proteomics-based research resource

USDA-ARS?s Scientific Manuscript database

The use of swine in biomedical research has increased dramatically in the last decade. Diverse genomic- and proteomic databases have been developed to facilitate research using human and rodent models. Current porcine gene databases, however, lack the robust annotation to study pig models that are...

Feasibility of Genome-Wide Screening for Biosafety Assessment of Probiotics: A Case Study of Lactobacillus helveticus MTCC 5463.

PubMed

Senan, S; Prajapati, J B; Joshi, C G

2015-12-01

Recent years have witnessed an explosion in genome sequencing of probiotic strains for accurate identification and characterization. Regulatory bodies are emphasizing on the need for performing phase I safety studies for probiotics. The main hypothesis of this study was to explore the feasibility of using genome databases for safety screening of strains. In this study, we attempted to develop a framework for the safety assessment of a potential probiotic strain, Lactobacillus helveticus MTCC 5463 based on genome mining for genes associated with antibiotic resistance, production of harmful metabolites, and virulence. The sequencing of MTCC 5463 was performed using GS-FLX Titanium reagents. Genes coding for antibiotic resistance and virulence were identified using Antibiotic Resistance Genes Database and Virulence Factors Database. Results indicated that MTCC 5463 carried antibiotic resistance genes associated with beta-lactam and fluoroquinolone. There is no threat of transfer of these genes to host gut commensals because the genes are not plasmid encoded. The presence of genes for adhesion, biofilm, surface proteins, and stress-related proteins provides robustness to the strain. The presence of hemolysin gene in the genome revealed a theoretical risk of virulence. The results of in silico analysis complemented the in vitro studies and human clinical trials, confirming the safety of the probiotic strain. We propose that the safety assessment of probiotic strains administered live at high doses using a genome-wide screening could be an effective and time-saving tool for identifying prognostic biomarkers of biosafety.

dictyExpress: a Dictyostelium discoideum gene expression database with an explorative data analysis web-based interface.

PubMed

Rot, Gregor; Parikh, Anup; Curk, Tomaz; Kuspa, Adam; Shaulsky, Gad; Zupan, Blaz

2009-08-25

Bioinformatics often leverages on recent advancements in computer science to support biologists in their scientific discovery process. Such efforts include the development of easy-to-use web interfaces to biomedical databases. Recent advancements in interactive web technologies require us to rethink the standard submit-and-wait paradigm, and craft bioinformatics web applications that share analytical and interactive power with their desktop relatives, while retaining simplicity and availability. We have developed dictyExpress, a web application that features a graphical, highly interactive explorative interface to our database that consists of more than 1000 Dictyostelium discoideum gene expression experiments. In dictyExpress, the user can select experiments and genes, perform gene clustering, view gene expression profiles across time, view gene co-expression networks, perform analyses of Gene Ontology term enrichment, and simultaneously display expression profiles for a selected gene in various experiments. Most importantly, these tasks are achieved through web applications whose components are seamlessly interlinked and immediately respond to events triggered by the user, thus providing a powerful explorative data analysis environment. dictyExpress is a precursor for a new generation of web-based bioinformatics applications with simple but powerful interactive interfaces that resemble that of the modern desktop. While dictyExpress serves mainly the Dictyostelium research community, it is relatively easy to adapt it to other datasets. We propose that the design ideas behind dictyExpress will influence the development of similar applications for other model organisms.

dictyExpress: a Dictyostelium discoideum gene expression database with an explorative data analysis web-based interface

PubMed Central

Rot, Gregor; Parikh, Anup; Curk, Tomaz; Kuspa, Adam; Shaulsky, Gad; Zupan, Blaz

2009-01-01

Background Bioinformatics often leverages on recent advancements in computer science to support biologists in their scientific discovery process. Such efforts include the development of easy-to-use web interfaces to biomedical databases. Recent advancements in interactive web technologies require us to rethink the standard submit-and-wait paradigm, and craft bioinformatics web applications that share analytical and interactive power with their desktop relatives, while retaining simplicity and availability. Results We have developed dictyExpress, a web application that features a graphical, highly interactive explorative interface to our database that consists of more than 1000 Dictyostelium discoideum gene expression experiments. In dictyExpress, the user can select experiments and genes, perform gene clustering, view gene expression profiles across time, view gene co-expression networks, perform analyses of Gene Ontology term enrichment, and simultaneously display expression profiles for a selected gene in various experiments. Most importantly, these tasks are achieved through web applications whose components are seamlessly interlinked and immediately respond to events triggered by the user, thus providing a powerful explorative data analysis environment. Conclusion dictyExpress is a precursor for a new generation of web-based bioinformatics applications with simple but powerful interactive interfaces that resemble that of the modern desktop. While dictyExpress serves mainly the Dictyostelium research community, it is relatively easy to adapt it to other datasets. We propose that the design ideas behind dictyExpress will influence the development of similar applications for other model organisms. PMID:19706156

Updated regulation curation model at the Saccharomyces Genome Database

PubMed Central

Engel, Stacia R; Skrzypek, Marek S; Hellerstedt, Sage T; Wong, Edith D; Nash, Robert S; Weng, Shuai; Binkley, Gail; Sheppard, Travis K; Karra, Kalpana; Cherry, J Michael

2018-01-01

Abstract The Saccharomyces Genome Database (SGD) provides comprehensive, integrated biological information for the budding yeast Saccharomyces cerevisiae, along with search and analysis tools to explore these data, enabling the discovery of functional relationships between sequence and gene products in fungi and higher organisms. We have recently expanded our data model for regulation curation to address regulation at the protein level in addition to transcription, and are presenting the expanded data on the ‘Regulation’ pages at SGD. These pages include a summary describing the context under which the regulator acts, manually curated and high-throughput annotations showing the regulatory relationships for that gene and a graphical visualization of its regulatory network and connected networks. For genes whose products regulate other genes or proteins, the Regulation page includes Gene Ontology enrichment analysis of the biological processes in which those targets participate. For DNA-binding transcription factors, we also provide other information relevant to their regulatory function, such as DNA binding site motifs and protein domains. As with other data types at SGD, all regulatory relationships and accompanying data are available through YeastMine, SGD’s data warehouse based on InterMine. Database URL: http://www.yeastgenome.org PMID:29688362

STOPGAP: a database for systematic target opportunity assessment by genetic association predictions.

PubMed

Shen, Judong; Song, Kijoung; Slater, Andrew J; Ferrero, Enrico; Nelson, Matthew R

2017-09-01

We developed the STOPGAP (Systematic Target OPportunity assessment by Genetic Association Predictions) database, an extensive catalog of human genetic associations mapped to effector gene candidates. STOPGAP draws on a variety of publicly available GWAS associations, linkage disequilibrium (LD) measures, functional genomic and variant annotation sources. Algorithms were developed to merge the association data, partition associations into non-overlapping LD clusters, map variants to genes and produce a variant-to-gene score used to rank the relative confidence among potential effector genes. This database can be used for a multitude of investigations into the genes and genetic mechanisms underlying inter-individual variation in human traits, as well as supporting drug discovery applications. Shell, R, Perl and Python scripts and STOPGAP R data files (version 2.5.1 at publication) are available at https://github.com/StatGenPRD/STOPGAP . Some of the most useful STOPGAP fields can be queried through an R Shiny web application at http://stopgapwebapp.com . matthew.r.nelson@gsk.com. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

A large scale analysis of cDNA in Arabidopsis thaliana: generation of 12,028 non-redundant expressed sequence tags from normalized and size-selected cDNA libraries.

PubMed

Asamizu, E; Nakamura, Y; Sato, S; Tabata, S

2000-06-30

For comprehensive analysis of genes expressed in the model dicotyledonous plant, Arabidopsis thaliana, expressed sequence tags (ESTs) were accumulated. Normalized and size-selected cDNA libraries were constructed from aboveground organs, flower buds, roots, green siliques and liquid-cultured seedlings, respectively, and a total of 14,026 5'-end ESTs and 39,207 3'-end ESTs were obtained. The 3'-end ESTs could be clustered into 12,028 non-redundant groups. Similarity search of the non-redundant ESTs against the public non-redundant protein database indicated that 4816 groups show similarity to genes of known function, 1864 to hypothetical genes, and the remaining 5348 are novel sequences. Gene coverage by the non-redundant ESTs was analyzed using the annotated genomic sequences of approximately 10 Mb on chromosomes 3 and 5. A total of 923 regions were hit by at least one EST, among which only 499 regions were hit by the ESTs deposited in the public database. The result indicates that the EST source generated in this project complements the EST data in the public database and facilitates new gene discovery.

BGD: a database of bat genomes.

PubMed

Fang, Jianfei; Wang, Xuan; Mu, Shuo; Zhang, Shuyi; Dong, Dong

2015-01-01

Bats account for ~20% of mammalian species, and are the only mammals with true powered flight. For the sake of their specialized phenotypic traits, many researches have been devoted to examine the evolution of bats. Until now, some whole genome sequences of bats have been assembled and annotated, however, a uniform resource for the annotated bat genomes is still unavailable. To make the extensive data associated with the bat genomes accessible to the general biological communities, we established a Bat Genome Database (BGD). BGD is an open-access, web-available portal that integrates available data of bat genomes and genes. It hosts data from six bat species, including two megabats and four microbats. Users can query the gene annotations using efficient searching engine, and it offers browsable tracks of bat genomes. Furthermore, an easy-to-use phylogenetic analysis tool was also provided to facilitate online phylogeny study of genes. To the best of our knowledge, BGD is the first database of bat genomes. It will extend our understanding of the bat evolution and be advantageous to the bat sequences analysis. BGD is freely available at: http://donglab.ecnu.edu.cn/databases/BatGenome/.

Relax with CouchDB--into the non-relational DBMS era of bioinformatics.

PubMed

Manyam, Ganiraju; Payton, Michelle A; Roth, Jack A; Abruzzo, Lynne V; Coombes, Kevin R

2012-07-01

With the proliferation of high-throughput technologies, genome-level data analysis has become common in molecular biology. Bioinformaticians are developing extensive resources to annotate and mine biological features from high-throughput data. The underlying database management systems for most bioinformatics software are based on a relational model. Modern non-relational databases offer an alternative that has flexibility, scalability, and a non-rigid design schema. Moreover, with an accelerated development pace, non-relational databases like CouchDB can be ideal tools to construct bioinformatics utilities. We describe CouchDB by presenting three new bioinformatics resources: (a) geneSmash, which collates data from bioinformatics resources and provides automated gene-centric annotations, (b) drugBase, a database of drug-target interactions with a web interface powered by geneSmash, and (c) HapMap-CN, which provides a web interface to query copy number variations from three SNP-chip HapMap datasets. In addition to the web sites, all three systems can be accessed programmatically via web services. Copyright © 2012 Elsevier Inc. All rights reserved.

A Novel Paramyxovirus?

PubMed Central

García-Sastre, Adolfo; Palese, Peter

2005-01-01

In public databases, we identified sequences reported as human genes expressed in kidney mesangial cells. The similarity of these genes to paramyxovirus matrix, fusion, and phosphoprotein genes suggests that they are derived from a novel paramyxovirus. These genes are sufficiently unique to suggest the existence of a novel paramyxovirus genus. PMID:15705331

Validated MicroRNA Target Databases: An Evaluation.

PubMed

Lee, Yun Ji Diana; Kim, Veronica; Muth, Dillon C; Witwer, Kenneth W

2015-11-01

Preclinical Research Positive findings from preclinical and clinical studies involving depletion or supplementation of microRNA (miRNA) engender optimism about miRNA-based therapeutics. However, off-target effects must be considered. Predicting these effects is complicated. Each miRNA may target many gene transcripts, and the rules governing imperfectly complementary miRNA: target interactions are incompletely understood. Several databases provide lists of the relatively small number of experimentally confirmed miRNA: target pairs. Although incomplete, this information might allow assessment of at least some of the off-target effects. We evaluated the performance of four databases of experimentally validated miRNA: target interactions (miRWalk 2.0, miRTarBase, miRecords, and TarBase 7.0) using a list of 50 alphabetically consecutive genes. We examined the provided citations to determine the degree to which each interaction was experimentally supported. To assess stability, we tested at the beginning and end of a five-month period. Results varied widely by database. Two of the databases changed significantly over the course of 5 months. Most reported evidence for miRNA: target interactions were indirect or otherwise weak, and relatively few interactions were supported by more than one publication. Some returned results appear to arise from simplistic text searches that offer no insight into the relationship of the search terms, may not even include the reported gene or miRNA, and may thus, be invalid. We conclude that validation databases provide important information, but not all information in all extant databases is up-to-date or accurate. Nevertheless, the more comprehensive validation databases may provide useful starting points for investigation of off-target effects of proposed small RNA therapies. © 2015 Wiley Periodicals, Inc.

Genome-wide association study for rotator cuff tears identifies two significant single-nucleotide polymorphisms.

PubMed

Tashjian, Robert Z; Granger, Erin K; Farnham, James M; Cannon-Albright, Lisa A; Teerlink, Craig C

2016-02-01

The precise etiology of rotator cuff disease is unknown, but prior evidence suggests a role for genetic factors. Limited data exist identifying specific genes associated with rotator cuff tearing. The purpose of this study was to identify specific genes or genetic variants associated with rotator cuff tearing by a genome-wide association study with an independent set of rotator cuff tear cases. A set of 311 full-thickness rotator cuff tear cases genotyped on the Illumina 5M single-nucleotide polymorphism (SNP) platform were used in a genome-wide association study with 2641 genetically matched white population controls available from the Illumina iControls database. Tests of association were performed with GEMMA software at 257,558 SNPs that compose the intersection of Illumina SNP platforms and that passed general quality control metrics. SNPs were considered significant if P < 1.94 × 10(-7) (Bonferroni correction: 0.05/257,558). Tests of association revealed 2 significantly associated SNPs, one occurring in SAP30BP (rs820218; P = 3.8E-9) on chromosome 17q25 and another occurring in SASH1 (rs12527089; P = 1.9E-7) on chromosome 6q24. This study represents the first attempt to identify genetic factors influencing rotator cuff tearing by a genome-wide association study using a dense/complete set of SNPs. Two SNPs were significantly associated with rotator cuff tearing, residing in SAP30BP on chromosome 17 and SASH1 on chromosome 6. Both genes are associated with the cellular process of apoptosis. Identification of potential genes or genetic variants associated with rotator cuff tearing may help in identifying individuals at risk for the development of rotator cuff tearing. Copyright © 2016 Journal of Shoulder and Elbow Surgery Board of Trustees. Published by Elsevier Inc. All rights reserved.

The MAR databases: development and implementation of databases specific for marine metagenomics.

PubMed

Klemetsen, Terje; Raknes, Inge A; Fu, Juan; Agafonov, Alexander; Balasundaram, Sudhagar V; Tartari, Giacomo; Robertsen, Espen; Willassen, Nils P

2018-01-04

We introduce the marine databases; MarRef, MarDB and MarCat (https://mmp.sfb.uit.no/databases/), which are publicly available resources that promote marine research and innovation. These data resources, which have been implemented in the Marine Metagenomics Portal (MMP) (https://mmp.sfb.uit.no/), are collections of richly annotated and manually curated contextual (metadata) and sequence databases representing three tiers of accuracy. While MarRef is a database for completely sequenced marine prokaryotic genomes, which represent a marine prokaryote reference genome database, MarDB includes all incomplete sequenced prokaryotic genomes regardless level of completeness. The last database, MarCat, represents a gene (protein) catalog of uncultivable (and cultivable) marine genes and proteins derived from marine metagenomics samples. The first versions of MarRef and MarDB contain 612 and 3726 records, respectively. Each record is built up of 106 metadata fields including attributes for sampling, sequencing, assembly and annotation in addition to the organism and taxonomic information. Currently, MarCat contains 1227 records with 55 metadata fields. Ontologies and controlled vocabularies are used in the contextual databases to enhance consistency. The user-friendly web interface lets the visitors browse, filter and search in the contextual databases and perform BLAST searches against the corresponding sequence databases. All contextual and sequence databases are freely accessible and downloadable from https://s1.sfb.uit.no/public/mar/. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

DoOP: Databases of Orthologous Promoters, collections of clusters of orthologous upstream sequences from chordates and plants

PubMed Central

Barta, Endre; Sebestyén, Endre; Pálfy, Tamás B.; Tóth, Gábor; Ortutay, Csaba P.; Patthy, László

2005-01-01

DoOP (http://doop.abc.hu/) is a database of eukaryotic promoter sequences (upstream regions) aiming to facilitate the recognition of regulatory sites conserved between species. The annotated first exons of human and Arabidopsis thaliana genes were used as queries in BLAST searches to collect the most closely related orthologous first exon sequences from Chordata and Viridiplantae species. Up to 3000 bp DNA segments upstream from these first exons constitute the clusters in the chordate and plant sections of the Database of Orthologous Promoters. Release 1.0 of DoOP contains 21 061 chordate clusters from 284 different species and 7548 plant clusters from 269 different species. The database can be used to find and retrieve promoter sequences of a given gene from various species and it is also suitable to see the most trivial conserved sequence blocks in the orthologous upstream regions. Users can search DoOP with either sequence or text (annotation) to find promoter clusters of various genes. In addition to the sequence data, the positions of the conserved sequence blocks derived from multiple alignments, the positions of repetitive elements and the positions of transcription start sites known from the Eukaryotic Promoter Database (EPD) can be viewed graphically. PMID:15608291

DoOP: Databases of Orthologous Promoters, collections of clusters of orthologous upstream sequences from chordates and plants.

PubMed

Barta, Endre; Sebestyén, Endre; Pálfy, Tamás B; Tóth, Gábor; Ortutay, Csaba P; Patthy, László

2005-01-01

DoOP (http://doop.abc.hu/) is a database of eukaryotic promoter sequences (upstream regions) aiming to facilitate the recognition of regulatory sites conserved between species. The annotated first exons of human and Arabidopsis thaliana genes were used as queries in BLAST searches to collect the most closely related orthologous first exon sequences from Chordata and Viridiplantae species. Up to 3000 bp DNA segments upstream from these first exons constitute the clusters in the chordate and plant sections of the Database of Orthologous Promoters. Release 1.0 of DoOP contains 21,061 chordate clusters from 284 different species and 7548 plant clusters from 269 different species. The database can be used to find and retrieve promoter sequences of a given gene from various species and it is also suitable to see the most trivial conserved sequence blocks in the orthologous upstream regions. Users can search DoOP with either sequence or text (annotation) to find promoter clusters of various genes. In addition to the sequence data, the positions of the conserved sequence blocks derived from multiple alignments, the positions of repetitive elements and the positions of transcription start sites known from the Eukaryotic Promoter Database (EPD) can be viewed graphically.

De novo assembly and characterization of the garlic (Allium sativum) bud transcriptome by Illumina sequencing.

PubMed

Sun, Xiudong; Zhou, Shumei; Meng, Fanlu; Liu, Shiqi

2012-10-01

Garlic is widely used as a spice throughout the world for the culinary value of its flavor and aroma, which are created by the chemical transformation of a series of organic sulfur compounds. To analyze the transcriptome of Allium sativum and discover the genes involved in sulfur metabolism, cDNAs derived from the total RNA of Allium sativum buds were analyzed by Illumina sequencing. Approximately 26.67 million 90 bp paired-end clean reads were achieved in two libraries. A total of 127,933 unigenes were generated by de novo assembly and were compared with the sequences in public databases. Of these, 45,286 unigenes had significant hits to the sequences in the Nr database, 29,514 showed significant similarity to known proteins in the Swiss-Prot database and, 20,706 and 21,952 unigenes had significant similarity to existing sequences in the KEGG and COG databases, respectively. Moreover, genes involved in organic sulfur biosynthesis were identified. These unigenes data will provide the foundation for research on gene expression, genomics and functional genomics in Allium sativum. Key message The obtained unigenes will provide the foundation for research on functional genomics in Allium sativum and its closely related species, and fill the gap of the existing plant EST database.

IMGT, the International ImMunoGeneTics database.

PubMed Central

Lefranc, M P; Giudicelli, V; Busin, C; Bodmer, J; Müller, W; Bontrop, R; Lemaitre, M; Malik, A; Chaume, D

1998-01-01

IMGT, the international ImMunoGeneTics database, is an integrated database specialising in Immunoglobulins (Ig), T cell Receptors (TcR) and Major Histocompatibility Complex (MHC) of all vertebrate species, created by Marie-Paule Lefranc, CNRS, Montpellier II University, Montpellier, France (lefranc@ligm.crbm.cnrs-mop.fr). IMGT includes three databases: LIGM-DB (for Ig and TcR), MHC/HLA-DB and PRIMER-DB (the last two in development). IMGT comprises expertly annotated sequences and alignment tables. LIGM-DB contains more than 23 000 Immunoglobulin and T cell Receptor sequences from 78 species. MHC/HLA-DB contains Class I and Class II Human Leucocyte Antigen alignment tables. An IMGT tool, DNAPLOT, developed for Ig, TcR and MHC sequence alignments, is also available. IMGT works in close collaboration with the EMBL database. IMGT goals are to establish a common data access to all immunogenetics data, including nucleotide and protein sequences, oligonucleotide primers, gene maps and other genetic data of Ig, TcR and MHC molecules, and to provide a graphical user friendly data access. IMGT has important implications in medical research (repertoire in autoimmune diseases, AIDS, leukemias, lymphomas), therapeutical approaches (antibody engineering), genome diversity and genome evolution studies. IMGT is freely available at http://imgt.cnusc.fr:8104 PMID:9399859

Plant Reactome: a resource for plant pathways and comparative analysis.

PubMed

Naithani, Sushma; Preece, Justin; D'Eustachio, Peter; Gupta, Parul; Amarasinghe, Vindhya; Dharmawardhana, Palitha D; Wu, Guanming; Fabregat, Antonio; Elser, Justin L; Weiser, Joel; Keays, Maria; Fuentes, Alfonso Munoz-Pomer; Petryszak, Robert; Stein, Lincoln D; Ware, Doreen; Jaiswal, Pankaj

2017-01-04

Plant Reactome (http://plantreactome.gramene.org/) is a free, open-source, curated plant pathway database portal, provided as part of the Gramene project. The database provides intuitive bioinformatics tools for the visualization, analysis and interpretation of pathway knowledge to support genome annotation, genome analysis, modeling, systems biology, basic research and education. Plant Reactome employs the structural framework of a plant cell to show metabolic, transport, genetic, developmental and signaling pathways. We manually curate molecular details of pathways in these domains for reference species Oryza sativa (rice) supported by published literature and annotation of well-characterized genes. Two hundred twenty-two rice pathways, 1025 reactions associated with 1173 proteins, 907 small molecules and 256 literature references have been curated to date. These reference annotations were used to project pathways for 62 model, crop and evolutionarily significant plant species based on gene homology. Database users can search and browse various components of the database, visualize curated baseline expression of pathway-associated genes provided by the Expression Atlas and upload and analyze their Omics datasets. The database also offers data access via Application Programming Interfaces (APIs) and in various standardized pathway formats, such as SBML and BioPAX. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Specialized microbial databases for inductive exploration of microbial genome sequences

PubMed Central

Fang, Gang; Ho, Christine; Qiu, Yaowu; Cubas, Virginie; Yu, Zhou; Cabau, Cédric; Cheung, Frankie; Moszer, Ivan; Danchin, Antoine

2005-01-01

Background The enormous amount of genome sequence data asks for user-oriented databases to manage sequences and annotations. Queries must include search tools permitting function identification through exploration of related objects. Methods The GenoList package for collecting and mining microbial genome databases has been rewritten using MySQL as the database management system. Functions that were not available in MySQL, such as nested subquery, have been implemented. Results Inductive reasoning in the study of genomes starts from "islands of knowledge", centered around genes with some known background. With this concept of "neighborhood" in mind, a modified version of the GenoList structure has been used for organizing sequence data from prokaryotic genomes of particular interest in China. GenoChore , a set of 17 specialized end-user-oriented microbial databases (including one instance of Microsporidia, Encephalitozoon cuniculi, a member of Eukarya) has been made publicly available. These databases allow the user to browse genome sequence and annotation data using standard queries. In addition they provide a weekly update of searches against the world-wide protein sequences data libraries, allowing one to monitor annotation updates on genes of interest. Finally, they allow users to search for patterns in DNA or protein sequences, taking into account a clustering of genes into formal operons, as well as providing extra facilities to query sequences using predefined sequence patterns. Conclusion This growing set of specialized microbial databases organize data created by the first Chinese bacterial genome programs (ThermaList, Thermoanaerobacter tencongensis, LeptoList, with two different genomes of Leptospira interrogans and SepiList, Staphylococcus epidermidis) associated to related organisms for comparison. PMID:15698474

AgdbNet – antigen sequence database software for bacterial typing

PubMed Central

Jolley, Keith A; Maiden, Martin CJ

2006-01-01

Background Bacterial typing schemes based on the sequences of genes encoding surface antigens require databases that provide a uniform, curated, and widely accepted nomenclature of the variants identified. Due to the differences in typing schemes, imposed by the diversity of genes targeted, creating these databases has typically required the writing of one-off code to link the database to a web interface. Here we describe agdbNet, widely applicable web database software that facilitates simultaneous BLAST querying of multiple loci using either nucleotide or peptide sequences. Results Databases are described by XML files that are parsed by a Perl CGI script. Each database can have any number of loci, which may be defined by nucleotide and/or peptide sequences. The software is currently in use on at least five public databases for the typing of Neisseria meningitidis, Campylobacter jejuni and Streptococcus equi and can be set up to query internal isolate tables or suitably-configured external isolate databases, such as those used for multilocus sequence typing. The style of the resulting website can be fully configured by modifying stylesheets and through the use of customised header and footer files that surround the output of the script. Conclusion The software provides a rapid means of setting up customised Internet antigen sequence databases. The flexible configuration options enable typing schemes with differing requirements to be accommodated. PMID:16790057

GeneSigDB: a manually curated database and resource for analysis of gene expression signatures

PubMed Central

Culhane, Aedín C.; Schröder, Markus S.; Sultana, Razvan; Picard, Shaita C.; Martinelli, Enzo N.; Kelly, Caroline; Haibe-Kains, Benjamin; Kapushesky, Misha; St Pierre, Anne-Alyssa; Flahive, William; Picard, Kermshlise C.; Gusenleitner, Daniel; Papenhausen, Gerald; O'Connor, Niall; Correll, Mick; Quackenbush, John

2012-01-01

GeneSigDB (http://www.genesigdb.org or http://compbio.dfci.harvard.edu/genesigdb/) is a database of gene signatures that have been extracted and manually curated from the published literature. It provides a standardized resource of published prognostic, diagnostic and other gene signatures of cancer and related disease to the community so they can compare the predictive power of gene signatures or use these in gene set enrichment analysis. Since GeneSigDB release 1.0, we have expanded from 575 to 3515 gene signatures, which were collected and transcribed from 1604 published articles largely focused on gene expression in cancer, stem cells, immune cells, development and lung disease. We have made substantial upgrades to the GeneSigDB website to improve accessibility and usability, including adding a tag cloud browse function, facetted navigation and a ‘basket’ feature to store genes or gene signatures of interest. Users can analyze GeneSigDB gene signatures, or upload their own gene list, to identify gene signatures with significant gene overlap and results can be viewed on a dynamic editable heatmap that can be downloaded as a publication quality image. All data in GeneSigDB can be downloaded in numerous formats including .gmt file format for gene set enrichment analysis or as a R/Bioconductor data file. GeneSigDB is available from http://www.genesigdb.org. PMID:22110038

Automated Identification of Medically Important Bacteria by 16S rRNA Gene Sequencing Using a Novel Comprehensive Database, 16SpathDB▿

PubMed Central

Woo, Patrick C. Y.; Teng, Jade L. L.; Yeung, Juilian M. Y.; Tse, Herman; Lau, Susanna K. P.; Yuen, Kwok-Yung

2011-01-01

Despite the increasing use of 16S rRNA gene sequencing, interpretation of 16S rRNA gene sequence results is one of the most difficult problems faced by clinical microbiologists and technicians. To overcome the problems we encountered in the existing databases during 16S rRNA gene sequence interpretation, we built a comprehensive database, 16SpathDB (http://147.8.74.24/16SpathDB) based on the 16S rRNA gene sequences of all medically important bacteria listed in the Manual of Clinical Microbiology and evaluated its use for automated identification of these bacteria. Among 91 nonduplicated bacterial isolates collected in our clinical microbiology laboratory, 71 (78%) were reported by 16SpathDB as a single bacterial species having >98.0% nucleotide identity with the query sequence, 19 (20.9%) were reported as more than one bacterial species having >98.0% nucleotide identity with the query sequence, and 1 (1.1%) was reported as no match. For the 71 bacterial isolates reported as a single bacterial species, all results were identical to their true identities as determined by a polyphasic approach. For the 19 bacterial isolates reported as more than one bacterial species, all results contained their true identities as determined by a polyphasic approach and all of them had their true identities as the “best match in 16SpathDB.” For the isolate (Gordonibacter pamelaeae) reported as no match, the bacterium has never been reported to be associated with human disease and was not included in the Manual of Clinical Microbiology. 16SpathDB is an automated, user-friendly, efficient, accurate, and regularly updated database for 16S rRNA gene sequence interpretation in clinical microbiology laboratories. PMID:21389154

Identification of candidate genes in Populus cell wall biosynthesis using text-mining, co-expression network and comparative genomics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Xiaohan; Ye, Chuyu; Bisaria, Anjali

2011-01-01

Populus is an important bioenergy crop for bioethanol production. A greater understanding of cell wall biosynthesis processes is critical in reducing biomass recalcitrance, a major hindrance in efficient generation of ethanol from lignocellulosic biomass. Here, we report the identification of candidate cell wall biosynthesis genes through the development and application of a novel bioinformatics pipeline. As a first step, via text-mining of PubMed publications, we obtained 121 Arabidopsis genes that had the experimental evidences supporting their involvement in cell wall biosynthesis or remodeling. The 121 genes were then used as bait genes to query an Arabidopsis co-expression database and additionalmore » genes were identified as neighbors of the bait genes in the network, increasing the number of genes to 548. The 548 Arabidopsis genes were then used to re-query the Arabidopsis co-expression database and re-construct a network that captured additional network neighbors, expanding to a total of 694 genes. The 694 Arabidopsis genes were computationally divided into 22 clusters. Queries of the Populus genome using the Arabidopsis genes revealed 817 Populus orthologs. Functional analysis of gene ontology and tissue-specific gene expression indicated that these Arabidopsis and Populus genes are high likelihood candidates for functional genomics in relation to cell wall biosynthesis.« less

Towards G2G: Systems of Technology Database Systems

NASA Technical Reports Server (NTRS)

Maluf, David A.; Bell, David

2005-01-01

We present an approach and methodology for developing Government-to-Government (G2G) Systems of Technology Database Systems. G2G will deliver technologies for distributed and remote integration of technology data for internal use in analysis and planning as well as for external communications. G2G enables NASA managers, engineers, operational teams and information systems to "compose" technology roadmaps and plans by selecting, combining, extending, specializing and modifying components of technology database systems. G2G will interoperate information and knowledge that is distributed across organizational entities involved that is ideal for NASA future Exploration Enterprise. Key contributions of the G2G system will include the creation of an integrated approach to sustain effective management of technology investments that supports the ability of various technology database systems to be independently managed. The integration technology will comply with emerging open standards. Applications can thus be customized for local needs while enabling an integrated management of technology approach that serves the global needs of NASA. The G2G capabilities will use NASA s breakthrough in database "composition" and integration technology, will use and advance emerging open standards, and will use commercial information technologies to enable effective System of Technology Database systems.

Dictionary-driven prokaryotic gene finding

PubMed Central

Shibuya, Tetsuo; Rigoutsos, Isidore

2002-01-01

Gene identification, also known as gene finding or gene recognition, is among the important problems of molecular biology that have been receiving increasing attention with the advent of large scale sequencing projects. Previous strategies for solving this problem can be categorized into essentially two schools of thought: one school employs sequence composition statistics, whereas the other relies on database similarity searches. In this paper, we propose a new gene identification scheme that combines the best characteristics from each of these two schools. In particular, our method determines gene candidates among the ORFs that can be identified in a given DNA strand through the use of the Bio-Dictionary, a database of patterns that covers essentially all of the currently available sample of the natural protein sequence space. Our approach relies entirely on the use of redundant patterns as the agents on which the presence or absence of genes is predicated and does not employ any additional evidence, e.g. ribosome-binding site signals. The Bio-Dictionary Gene Finder (BDGF), the algorithm’s implementation, is a single computational engine able to handle the gene identification task across distinct archaeal and bacterial genomes. The engine exhibits performance that is characterized by simultaneous very high values of sensitivity and specificity, and a high percentage of correctly predicted start sites. Using a collection of patterns derived from an old (June 2000) release of the Swiss-Prot/TrEMBL database that contained 451 602 proteins and fragments, we demonstrate our method’s generality and capabilities through an extensive analysis of 17 complete archaeal and bacterial genomes. Examples of previously unreported genes are also shown and discussed in detail. PMID:12060689

Identification of Biological Targets of Therapeutic Intervention for Hepatocellular Carcinoma by Integrated Bioinformatical Analysis.

PubMed

Hu, Wei Qi; Wang, Wei; Fang, Di Long; Yin, Xue Feng

2018-05-24

BACKGROUND We screened the potential molecular targets and investigated the molecular mechanisms of hepatocellular carcinoma (HCC). MATERIAL AND METHODS Microarray data of GSE47786, including the 40 μM berberine-treated HepG2 human hepatoma cell line and 0.08% DMSO-treated as control cells samples, was downloaded from the GEO database. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analyses were performed; the protein-protein interaction (PPI) networks were constructed using STRING database and Cytoscape; the genetic alteration, neighboring genes networks, and survival analysis of hub genes were explored by cBio portal; and the expression of mRNA level of hub genes was obtained from the Oncomine databases. RESULTS A total of 56 upregulated and 8 downregulated DEGs were identified. The GO analysis results were significantly enriched in cell-cycle arrest, regulation of transcription, DNA-dependent, protein amino acid phosphorylation, cell cycle, and apoptosis. The KEGG pathway analysis showed that DEGs were enriched in MAPK signaling pathway, ErbB signaling pathway, and p53 signaling pathway. JUN, EGR1, MYC, and CDKN1A were identified as hub genes in PPI networks. The genetic alteration of hub genes was mainly concentrated in amplification. TP53, NDRG1, and MAPK15 were found in neighboring genes networks. Altered genes had worse overall survival and disease-free survival than unaltered genes. The expressions of EGR1, MYC, and CDKN1A were significantly increased, but expression of JUN was not, in the Roessler Liver datasets. CONCLUSIONS We found that JUN, EGR1, MYC, and CDKN1A might be used as diagnostic and therapeutic molecular biomarkers and broaden our understanding of the molecular mechanisms of HCC.