Science.gov

Sample records for annotation databases improves

  1. Considerations to improve functional annotations in biological databases.

    PubMed

    Benítez-Páez, Alfonso

    2009-12-01

    Despite the great effort to design efficient systems allowing the electronic indexation of information concerning genes, proteins, structures, and interactions published daily in scientific journals, some problems are still observed in specific tasks such as functional annotation. The annotation of function is a critical issue for bioinformatic routines, such as for instance, in functional genomics and the further prediction of unknown protein function, which are highly dependent of the quality of existing annotations. Some information management systems evolve to efficiently incorporate information from large-scale projects, but often, annotation of single records from the literature is difficult and slow. In this short report, functional characterizations of a representative sample of the entire set of uncharacterized proteins from Escherichia coli K12 was compiled from Swiss-Prot, PubMed, and EcoCyc and demonstrate a functional annotation deficit in biological databases. Some issues are postulated as causes of the lack of annotation, and different solutions are evaluated and proposed to avoid them. The hope is that as a consequence of these observations, there will be new impetus to improve the speed and quality of functional annotation and ultimately provide updated, reliable information to the scientific community. PMID:20050264

  2. STANDARDIZATION AND STRUCTURAL ANNOTATION OF PUBLIC TOXICITY DATABASES: IMPROVING SAR CAPABILITIES AND LINKAGE TO 'OMICS DATA

    EPA Science Inventory

    Standardization and structural annotation of public toxicity databases: Improving SAR capabilities and linkage to 'omics data
    Ann M. Richard', ClarLynda Williams', Jamie Burch2
    'Nat Health & Environ Res Lab, US EPA, RTP, NC 27711; 2EPA/NC Central Univ Student COOP Trainee<...

  3. The annotation and the usage of scientific databases could be improved with public issue tracker software

    PubMed Central

    Dall'Olio, Giovanni Marco; Bertranpetit, Jaume; Laayouni, Hafid

    2010-01-01

    Since the publication of their longtime predecessor The Atlas of Protein Sequences and Structures in 1965 by Margaret Dayhoff, scientific databases have become a key factor in the organization of modern science. All the information and knowledge described in the novel scientific literature is translated into entries in many different scientific databases, making it possible to obtain very accurate information on a biological entity like genes or proteins without having to manually review the literature on it. However, even for the databases with the finest annotation procedures, errors or unclear parts sometimes appear in the publicly released version and influence the research of unaware scientists using them. The researcher that finds an error in a database is often left in a uncertain state, and often abandons the effort of reporting it because of a lack of a standard procedure to do so. In the present work, we propose that the simple adoption of a public error tracker application, as in many open software projects, could improve the quality of the annotations in many databases and encourage feedback from the scientific community on the data annotated publicly. In order to illustrate the situation, we describe a series of errors that we found and helped solve on the genes of a very well-known pathway in various biomedically relevant databases. We would like to show that, even if a majority of the most important scientific databases have procedures for reporting errors, these are usually not publicly visible, making the process of reporting errors time consuming and not useful. Also, the effort made by the user that reports the error often goes unacknowledged, putting him in a discouraging position. PMID:21186182

  4. Expanded microbial genome coverage and improved protein family annotation in the COG database

    PubMed Central

    Galperin, Michael Y.; Makarova, Kira S.; Wolf, Yuri I.; Koonin, Eugene V.

    2015-01-01

    Microbial genome sequencing projects produce numerous sequences of deduced proteins, only a small fraction of which have been or will ever be studied experimentally. This leaves sequence analysis as the only feasible way to annotate these proteins and assign to them tentative functions. The Clusters of Orthologous Groups of proteins (COGs) database (http://www.ncbi.nlm.nih.gov/COG/), first created in 1997, has been a popular tool for functional annotation. Its success was largely based on (i) its reliance on complete microbial genomes, which allowed reliable assignment of orthologs and paralogs for most genes; (ii) orthology-based approach, which used the function(s) of the characterized member(s) of the protein family (COG) to assign function(s) to the entire set of carefully identified orthologs and describe the range of potential functions when there were more than one; and (iii) careful manual curation of the annotation of the COGs, aimed at detailed prediction of the biological function(s) for each COG while avoiding annotation errors and overprediction. Here we present an update of the COGs, the first since 2003, and a comprehensive revision of the COG annotations and expansion of the genome coverage to include representative complete genomes from all bacterial and archaeal lineages down to the genus level. This re-analysis of the COGs shows that the original COG assignments had an error rate below 0.5% and allows an assessment of the progress in functional genomics in the past 12 years. During this time, functions of many previously uncharacterized COGs have been elucidated and tentative functional assignments of many COGs have been validated, either by targeted experiments or through the use of high-throughput methods. A particularly important development is the assignment of functions to several widespread, conserved proteins many of which turned out to participate in translation, in particular rRNA maturation and tRNA modification. The new version of the

  5. How well are protein structures annotated in secondary databases?

    PubMed

    Rother, Kristian; Michalsky, Elke; Leser, Ulf

    2005-09-01

    We investigated to what extent Protein Data Bank (PDB) entries are annotated with second-party information based on existing cross-references between PDB and 15 other databases. We report 2 interesting findings. First, there is a clear "annotation gap" for structures less than 7 years old for secondary databases that are manually curated. Second, the examined databases overlap with each other quite well, dividing the PDB into 2 well-annotated thirds and one poorly annotated third. Both observations should be taken into account in any study depending on the selection of protein structures by their annotation.

  6. Hymenoptera Genome Database: integrating genome annotations in HymenopteraMine

    PubMed Central

    Elsik, Christine G.; Tayal, Aditi; Diesh, Colin M.; Unni, Deepak R.; Emery, Marianne L.; Nguyen, Hung N.; Hagen, Darren E.

    2016-01-01

    We report an update of the Hymenoptera Genome Database (HGD) (http://HymenopteraGenome.org), a model organism database for insect species of the order Hymenoptera (ants, bees and wasps). HGD maintains genomic data for 9 bee species, 10 ant species and 1 wasp, including the versions of genome and annotation data sets published by the genome sequencing consortiums and those provided by NCBI. A new data-mining warehouse, HymenopteraMine, based on the InterMine data warehousing system, integrates the genome data with data from external sources and facilitates cross-species analyses based on orthology. New genome browsers and annotation tools based on JBrowse/WebApollo provide easy genome navigation, and viewing of high throughput sequence data sets and can be used for collaborative genome annotation. All of the genomes and annotation data sets are combined into a single BLAST server that allows users to select and combine sequence data sets to search. PMID:26578564

  7. Hymenoptera Genome Database: integrating genome annotations in HymenopteraMine.

    PubMed

    Elsik, Christine G; Tayal, Aditi; Diesh, Colin M; Unni, Deepak R; Emery, Marianne L; Nguyen, Hung N; Hagen, Darren E

    2016-01-01

    We report an update of the Hymenoptera Genome Database (HGD) (http://HymenopteraGenome.org), a model organism database for insect species of the order Hymenoptera (ants, bees and wasps). HGD maintains genomic data for 9 bee species, 10 ant species and 1 wasp, including the versions of genome and annotation data sets published by the genome sequencing consortiums and those provided by NCBI. A new data-mining warehouse, HymenopteraMine, based on the InterMine data warehousing system, integrates the genome data with data from external sources and facilitates cross-species analyses based on orthology. New genome browsers and annotation tools based on JBrowse/WebApollo provide easy genome navigation, and viewing of high throughput sequence data sets and can be used for collaborative genome annotation. All of the genomes and annotation data sets are combined into a single BLAST server that allows users to select and combine sequence data sets to search. PMID:26578564

  8. Hymenoptera Genome Database: integrating genome annotations in HymenopteraMine.

    PubMed

    Elsik, Christine G; Tayal, Aditi; Diesh, Colin M; Unni, Deepak R; Emery, Marianne L; Nguyen, Hung N; Hagen, Darren E

    2016-01-01

    We report an update of the Hymenoptera Genome Database (HGD) (http://HymenopteraGenome.org), a model organism database for insect species of the order Hymenoptera (ants, bees and wasps). HGD maintains genomic data for 9 bee species, 10 ant species and 1 wasp, including the versions of genome and annotation data sets published by the genome sequencing consortiums and those provided by NCBI. A new data-mining warehouse, HymenopteraMine, based on the InterMine data warehousing system, integrates the genome data with data from external sources and facilitates cross-species analyses based on orthology. New genome browsers and annotation tools based on JBrowse/WebApollo provide easy genome navigation, and viewing of high throughput sequence data sets and can be used for collaborative genome annotation. All of the genomes and annotation data sets are combined into a single BLAST server that allows users to select and combine sequence data sets to search.

  9. Large-scale annotation of small-molecule libraries using public databases.

    PubMed

    Zhou, Yingyao; Zhou, Bin; Chen, Kaisheng; Yan, S Frank; King, Frederick J; Jiang, Shumei; Winzeler, Elizabeth A

    2007-01-01

    While many large publicly accessible databases provide excellent annotation for biological macromolecules, the same is not true for small chemical compounds. Commercial data sources also fail to encompass an annotation interface for large numbers of compounds and tend to be cost prohibitive to be widely available to biomedical researchers. Therefore, using annotation information for the selection of lead compounds from a modern day high-throughput screening (HTS) campaign presently occurs only under a very limited scale. The recent rapid expansion of the NIH PubChem database provides an opportunity to link existing biological databases with compound catalogs and provides relevant information that potentially could improve the information garnered from large-scale screening efforts. Using the 2.5 million compound collection at the Genomics Institute of the Novartis Research Foundation (GNF) as a model, we determined that approximately 4% of the library contained compounds with potential annotation in such databases as PubChem and the World Drug Index (WDI) as well as related databases such as the Kyoto Encyclopedia of Genes and Genomes (KEGG) and ChemIDplus. Furthermore, the exact structure match analysis showed 32% of GNF compounds can be linked to third party databases via PubChem. We also showed annotations such as MeSH (medical subject headings) terms can be applied to in-house HTS databases in identifying signature biological inhibition profiles of interest as well as expediting the assay validation process. The automated annotation of thousands of screening hits in batch is becoming feasible and has the potential to play an essential role in the hit-to-lead decision making process.

  10. [Identifying phosphopeptide by searching a site annotated protein database].

    PubMed

    Cheng, Kai; Wang, Fangjun; Bian, Yangyang; Ye, Mingling; Zou, Hanfa

    2015-01-01

    Phosphoproteome analysis is one of the important research fields in proteomics. In shotgun proteomics, phosphopeptides could be identified directly by setting phosphorylation as variable modifications in database search. However, search space increases significantly when variable modifications are set in post-translation modifications (PTMs) analysis, which will decrease the identification sensitivity. Because setting a variable modification on a specific type of amino acid residue means all of this amino acid residues in the database might be modified, which is not consistent with actual conditions. Phosphorylation and dephosphorylation are regulated by protein kinases and phosphatases, which can only occur on particular substrates. Therefore only residues within specific sequence are potential sites which may be modified. To address this issue, we extracted the characteristic sequence from the identified phosphorylation sites and created an annotated database containing phosphorylation site information, which allowed the searching engine to set variable modifications only on the serine, threonine and tyrosine residues that were identified to be phosphorylated previously. In this database only annotated serine, threonine and tyrosine can be modified. This strategy significantly reduced the search space. The performance of this new database searching strategy was evaluated by searching different types of data with Mascot, and higher sensitivity for phosphopeptide identification was achieved with high reliability.

  11. 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

    2016-01-01

    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. PMID:26578582

  12. Enhanced annotations and features for comparing thousands of Pseudomonas genomes in the Pseudomonas genome database

    PubMed Central

    Winsor, Geoffrey L.; Griffiths, Emma J.; Lo, Raymond; Dhillon, Bhavjinder K.; Shay, Julie A.; Brinkman, Fiona S. L.

    2016-01-01

    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. PMID:26578582

  13. DIDA: A curated and annotated digenic diseases database.

    PubMed

    Gazzo, Andrea M; Daneels, Dorien; Cilia, Elisa; Bonduelle, Maryse; Abramowicz, Marc; Van Dooren, Sonia; Smits, Guillaume; Lenaerts, Tom

    2016-01-01

    DIDA (DIgenic diseases DAtabase) is a novel database that provides for the first time detailed information on genes and associated genetic variants involved in digenic diseases, the simplest form of oligogenic inheritance. The database is accessible via http://dida.ibsquare.be and currently includes 213 digenic combinations involved in 44 different digenic diseases. These combinations are composed of 364 distinct variants, which are distributed over 136 distinct genes. The web interface provides browsing and search functionalities, as well as documentation and help pages, general database statistics and references to the original publications from which the data have been collected. The possibility to submit novel digenic data to DIDA is also provided. Creating this new repository was essential as current databases do not allow one to retrieve detailed records regarding digenic combinations. Genes, variants, diseases and digenic combinations in DIDA are annotated with manually curated information and information mined from other online resources. Next to providing a unique resource for the development of new analysis methods, DIDA gives clinical and molecular geneticists a tool to find the most comprehensive information on the digenic nature of their diseases of interest. PMID:26481352

  14. 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.

  15. MitoFish and MitoAnnotator: A Mitochondrial Genome Database of Fish with an Accurate and Automatic Annotation Pipeline

    PubMed Central

    Iwasaki, Wataru; Fukunaga, Tsukasa; Isagozawa, Ryota; Yamada, Koichiro; Maeda, Yasunobu; Satoh, Takashi P.; Sado, Tetsuya; Mabuchi, Kohji; Takeshima, Hirohiko; Miya, Masaki; Nishida, Mutsumi

    2013-01-01

    Mitofish is a database of fish mitochondrial genomes (mitogenomes) that includes powerful and precise de novo annotations for mitogenome sequences. Fish occupy an important position in the evolution of vertebrates and the ecology of the hydrosphere, and mitogenomic sequence data have served as a rich source of information for resolving fish phylogenies and identifying new fish species. The importance of a mitogenomic database continues to grow at a rapid pace as massive amounts of mitogenomic data are generated with the advent of new sequencing technologies. A severe bottleneck seems likely to occur with regard to mitogenome annotation because of the overwhelming pace of data accumulation and the intrinsic difficulties in annotating sequences with degenerating transfer RNA structures, divergent start/stop codons of the coding elements, and the overlapping of adjacent elements. To ease this data backlog, we developed an annotation pipeline named MitoAnnotator. MitoAnnotator automatically annotates a fish mitogenome with a high degree of accuracy in approximately 5 min; thus, it is readily applicable to data sets of dozens of sequences. MitoFish also contains re-annotations of previously sequenced fish mitogenomes, enabling researchers to refer to them when they find annotations that are likely to be erroneous or while conducting comparative mitogenomic analyses. For users who need more information on the taxonomy, habitats, phenotypes, or life cycles of fish, MitoFish provides links to related databases. MitoFish and MitoAnnotator are freely available at http://mitofish.aori.u-tokyo.ac.jp/ (last accessed August 28, 2013); all of the data can be batch downloaded, and the annotation pipeline can be used via a web interface. PMID:23955518

  16. MitoFish and MitoAnnotator: a mitochondrial genome database of fish with an accurate and automatic annotation pipeline.

    PubMed

    Iwasaki, Wataru; Fukunaga, Tsukasa; Isagozawa, Ryota; Yamada, Koichiro; Maeda, Yasunobu; Satoh, Takashi P; Sado, Tetsuya; Mabuchi, Kohji; Takeshima, Hirohiko; Miya, Masaki; Nishida, Mutsumi

    2013-11-01

    Mitofish is a database of fish mitochondrial genomes (mitogenomes) that includes powerful and precise de novo annotations for mitogenome sequences. Fish occupy an important position in the evolution of vertebrates and the ecology of the hydrosphere, and mitogenomic sequence data have served as a rich source of information for resolving fish phylogenies and identifying new fish species. The importance of a mitogenomic database continues to grow at a rapid pace as massive amounts of mitogenomic data are generated with the advent of new sequencing technologies. A severe bottleneck seems likely to occur with regard to mitogenome annotation because of the overwhelming pace of data accumulation and the intrinsic difficulties in annotating sequences with degenerating transfer RNA structures, divergent start/stop codons of the coding elements, and the overlapping of adjacent elements. To ease this data backlog, we developed an annotation pipeline named MitoAnnotator. MitoAnnotator automatically annotates a fish mitogenome with a high degree of accuracy in approximately 5 min; thus, it is readily applicable to data sets of dozens of sequences. MitoFish also contains re-annotations of previously sequenced fish mitogenomes, enabling researchers to refer to them when they find annotations that are likely to be erroneous or while conducting comparative mitogenomic analyses. For users who need more information on the taxonomy, habitats, phenotypes, or life cycles of fish, MitoFish provides links to related databases. MitoFish and MitoAnnotator are freely available at http://mitofish.aori.u-tokyo.ac.jp/ (last accessed August 28, 2013); all of the data can be batch downloaded, and the annotation pipeline can be used via a web interface.

  17. MannDB: A microbial annotation database for protein characterization

    SciTech Connect

    Zhou, C; Lam, M; Smith, J; Zemla, A; Dyer, M; Kuczmarski, T; Vitalis, E; Slezak, T

    2006-05-19

    MannDB was created to meet a need for rapid, comprehensive automated protein sequence analyses to support selection of proteins suitable as targets for driving the development of reagents for pathogen or protein toxin detection. Because a large number of open-source tools were needed, it was necessary to produce a software system to scale the computations for whole-proteome analysis. Thus, we built a fully automated system for executing software tools and for storage, integration, and display of automated protein sequence analysis and annotation data. MannDB is a relational database that organizes data resulting from fully automated, high-throughput protein-sequence analyses using open-source tools. Types of analyses provided include predictions of cleavage, chemical properties, classification, features, functional assignment, post-translational modifications, motifs, antigenicity, and secondary structure. Proteomes (lists of hypothetical and known proteins) are downloaded and parsed from Genbank and then inserted into MannDB, and annotations from SwissProt are downloaded when identifiers are found in the Genbank entry or when identical sequences are identified. Currently 36 open-source tools are run against MannDB protein sequences either on local systems or by means of batch submission to external servers. In addition, BLAST against protein entries in MvirDB, our database of microbial virulence factors, is performed. A web client browser enables viewing of computational results and downloaded annotations, and a query tool enables structured and free-text search capabilities. When available, links to external databases, including MvirDB, are provided. MannDB contains whole-proteome analyses for at least one representative organism from each category of biological threat organism listed by APHIS, CDC, HHS, NIAID, USDA, USFDA, and WHO. MannDB comprises a large number of genomes and comprehensive protein sequence analyses representing organisms listed as high

  18. GLAD: an Online Database of Gene List Annotation for Drosophila

    PubMed Central

    Hu, Yanhui; Comjean, Aram; Perkins, Lizabeth A.; Perrimon, Norbert; Mohr, Stephanie E.

    2015-01-01

    We present a resource of high quality lists of functionally related Drosophila genes, e.g. based on protein domains (kinases, transcription factors, etc.) or cellular function (e.g. autophagy, signal transduction). To establish these lists, we relied on different inputs, including curation from databases or the literature and mapping from other species. Moreover, as an added curation and quality control step, we asked experts in relevant fields to review many of the lists. The resource is available online for scientists to search and view, and is editable based on community input. Annotation of gene groups is an ongoing effort and scientific need will typically drive decisions regarding which gene lists to pursue. We anticipate that the number of lists will increase over time; that the composition of some lists will grow and/or change over time as new information becomes available; and that the lists will benefit the scientific community, e.g. at experimental design and data analysis stages. Based on this, we present an easily updatable online database, available at www.flyrnai.org/glad, at which gene group lists can be viewed, searched and downloaded. PMID:26157507

  19. An Improved microRNA Annotation of the Canine Genome.

    PubMed

    Penso-Dolfin, Luca; Swofford, Ross; Johnson, Jeremy; Alföldi, Jessica; Lindblad-Toh, Kerstin; Swarbreck, David; Moxon, Simon; Di Palma, Federica

    2016-01-01

    The domestic dog, Canis familiaris, is a valuable model for studying human diseases. The publication of the latest Canine genome build and annotation, CanFam3.1 provides an opportunity to enhance our understanding of gene regulation across tissues in the dog model system. In this study, we used the latest dog genome assembly and small RNA sequencing data from 9 different dog tissues to predict novel miRNAs in the dog genome, as well as to annotate conserved miRNAs from the miRBase database that were missing from the current dog annotation. We used both miRCat and miRDeep2 algorithms to computationally predict miRNA loci. The resulting, putative hairpin sequences were analysed in order to discard false positives, based on predicted secondary structures and patterns of small RNA read alignments. Results were further divided into high and low confidence miRNAs, using the same criteria. We generated tissue specific expression profiles for the resulting set of 811 loci: 720 conserved miRNAs, (207 of which had not been previously annotated in the dog genome) and 91 novel miRNA loci. Comparative analyses revealed 8 putative homologues of some novel miRNA in ferret, and one in microbat. All miRNAs were also classified into the genic and intergenic categories, based on the Ensembl RefSeq gene annotation for CanFam3.1. This additionally allowed us to identify four previously undescribed MiRtrons among our total set of miRNAs. We additionally annotated piRNAs, using proTRAC on the same input data. We thus identified 263 putative clusters, most of which (211 clusters) were found to be expressed in testis. Our results represent an important improvement of the dog genome annotation, paving the way to further research on the evolution of gene regulation, as well as on the contribution of post-transcriptional regulation to pathological conditions. PMID:27119849

  20. An Improved microRNA Annotation of the Canine Genome

    PubMed Central

    Swofford, Ross; Johnson, Jeremy; Alföldi, Jessica; Lindblad-Toh, Kerstin; Swarbreck, David; Moxon, Simon; Di Palma, Federica

    2016-01-01

    The domestic dog, Canis familiaris, is a valuable model for studying human diseases. The publication of the latest Canine genome build and annotation, CanFam3.1 provides an opportunity to enhance our understanding of gene regulation across tissues in the dog model system. In this study, we used the latest dog genome assembly and small RNA sequencing data from 9 different dog tissues to predict novel miRNAs in the dog genome, as well as to annotate conserved miRNAs from the miRBase database that were missing from the current dog annotation. We used both miRCat and miRDeep2 algorithms to computationally predict miRNA loci. The resulting, putative hairpin sequences were analysed in order to discard false positives, based on predicted secondary structures and patterns of small RNA read alignments. Results were further divided into high and low confidence miRNAs, using the same criteria. We generated tissue specific expression profiles for the resulting set of 811 loci: 720 conserved miRNAs, (207 of which had not been previously annotated in the dog genome) and 91 novel miRNA loci. Comparative analyses revealed 8 putative homologues of some novel miRNA in ferret, and one in microbat. All miRNAs were also classified into the genic and intergenic categories, based on the Ensembl RefSeq gene annotation for CanFam3.1. This additionally allowed us to identify four previously undescribed MiRtrons among our total set of miRNAs. We additionally annotated piRNAs, using proTRAC on the same input data. We thus identified 263 putative clusters, most of which (211 clusters) were found to be expressed in testis. Our results represent an important improvement of the dog genome annotation, paving the way to further research on the evolution of gene regulation, as well as on the contribution of post-transcriptional regulation to pathological conditions. PMID:27119849

  1. Combining computational models, semantic annotations and simulation experiments in a graph database

    PubMed Central

    Henkel, Ron; Wolkenhauer, Olaf; Waltemath, Dagmar

    2015-01-01

    Model repositories such as the BioModels Database, the CellML Model Repository or JWS Online are frequently accessed to retrieve computational models of biological systems. However, their storage concepts support only restricted types of queries and not all data inside the repositories can be retrieved. In this article we present a storage concept that meets this challenge. It grounds on a graph database, reflects the models’ structure, incorporates semantic annotations and simulation descriptions and ultimately connects different types of model-related data. The connections between heterogeneous model-related data and bio-ontologies enable efficient search via biological facts and grant access to new model features. The introduced concept notably improves the access of computational models and associated simulations in a model repository. This has positive effects on tasks such as model search, retrieval, ranking, matching and filtering. Furthermore, our work for the first time enables CellML- and Systems Biology Markup Language-encoded models to be effectively maintained in one database. We show how these models can be linked via annotations and queried. Database URL: https://sems.uni-rostock.de/projects/masymos/ PMID:25754863

  2. CycADS: an annotation database system to ease the development and update of BioCyc databases.

    PubMed

    Vellozo, Augusto F; Véron, Amélie S; Baa-Puyoulet, Patrice; Huerta-Cepas, Jaime; Cottret, Ludovic; Febvay, Gérard; Calevro, Federica; Rahbé, Yvan; Douglas, Angela E; Gabaldón, Toni; Sagot, Marie-France; Charles, Hubert; Colella, Stefano

    2011-01-01

    In recent years, genomes from an increasing number of organisms have been sequenced, but their annotation remains a time-consuming process. The BioCyc databases offer a framework for the integrated analysis of metabolic networks. The Pathway tool software suite allows the automated construction of a database starting from an annotated genome, but it requires prior integration of all annotations into a specific summary file or into a GenBank file. To allow the easy creation and update of a BioCyc database starting from the multiple genome annotation resources available over time, we have developed an ad hoc data management system that we called Cyc Annotation Database System (CycADS). CycADS is centred on a specific database model and on a set of Java programs to import, filter and export relevant information. Data from GenBank and other annotation sources (including for example: KAAS, PRIAM, Blast2GO and PhylomeDB) are collected into a database to be subsequently filtered and extracted to generate a complete annotation file. This file is then used to build an enriched BioCyc database using the PathoLogic program of Pathway Tools. The CycADS pipeline for annotation management was used to build the AcypiCyc database for the pea aphid (Acyrthosiphon pisum) whose genome was recently sequenced. The AcypiCyc database webpage includes also, for comparative analyses, two other metabolic reconstruction BioCyc databases generated using CycADS: TricaCyc for Tribolium castaneum and DromeCyc for Drosophila melanogaster. Linked to its flexible design, CycADS offers a powerful software tool for the generation and regular updating of enriched BioCyc databases. The CycADS system is particularly suited for metabolic gene annotation and network reconstruction in newly sequenced genomes. Because of the uniform annotation used for metabolic network reconstruction, CycADS is particularly useful for comparative analysis of the metabolism of different organisms. Database URL: http://www.cycadsys.org.

  3. CycADS: an annotation database system to ease the development and update of BioCyc databases.

    PubMed

    Vellozo, Augusto F; Véron, Amélie S; Baa-Puyoulet, Patrice; Huerta-Cepas, Jaime; Cottret, Ludovic; Febvay, Gérard; Calevro, Federica; Rahbé, Yvan; Douglas, Angela E; Gabaldón, Toni; Sagot, Marie-France; Charles, Hubert; Colella, Stefano

    2011-01-01

    In recent years, genomes from an increasing number of organisms have been sequenced, but their annotation remains a time-consuming process. The BioCyc databases offer a framework for the integrated analysis of metabolic networks. The Pathway tool software suite allows the automated construction of a database starting from an annotated genome, but it requires prior integration of all annotations into a specific summary file or into a GenBank file. To allow the easy creation and update of a BioCyc database starting from the multiple genome annotation resources available over time, we have developed an ad hoc data management system that we called Cyc Annotation Database System (CycADS). CycADS is centred on a specific database model and on a set of Java programs to import, filter and export relevant information. Data from GenBank and other annotation sources (including for example: KAAS, PRIAM, Blast2GO and PhylomeDB) are collected into a database to be subsequently filtered and extracted to generate a complete annotation file. This file is then used to build an enriched BioCyc database using the PathoLogic program of Pathway Tools. The CycADS pipeline for annotation management was used to build the AcypiCyc database for the pea aphid (Acyrthosiphon pisum) whose genome was recently sequenced. The AcypiCyc database webpage includes also, for comparative analyses, two other metabolic reconstruction BioCyc databases generated using CycADS: TricaCyc for Tribolium castaneum and DromeCyc for Drosophila melanogaster. Linked to its flexible design, CycADS offers a powerful software tool for the generation and regular updating of enriched BioCyc databases. The CycADS system is particularly suited for metabolic gene annotation and network reconstruction in newly sequenced genomes. Because of the uniform annotation used for metabolic network reconstruction, CycADS is particularly useful for comparative analysis of the metabolism of different organisms. Database URL: http

  4. Reference sequence (RefSeq) database at NCBI: current status, taxonomic expansion, and functional annotation

    PubMed Central

    O'Leary, Nuala A.; Wright, Mathew W.; Brister, J. Rodney; Ciufo, Stacy; Haddad, Diana; McVeigh, Rich; Rajput, Bhanu; Robbertse, Barbara; Smith-White, Brian; Ako-Adjei, Danso; Astashyn, Alexander; Badretdin, Azat; Bao, Yiming; Blinkova, Olga; Brover, Vyacheslav; Chetvernin, Vyacheslav; Choi, Jinna; Cox, Eric; Ermolaeva, Olga; Farrell, Catherine M.; Goldfarb, Tamara; Gupta, Tripti; Haft, Daniel; Hatcher, Eneida; Hlavina, Wratko; Joardar, Vinita S.; Kodali, Vamsi K.; Li, Wenjun; Maglott, Donna; Masterson, Patrick; McGarvey, Kelly M.; Murphy, Michael R.; O'Neill, Kathleen; Pujar, Shashikant; Rangwala, Sanjida H.; Rausch, Daniel; Riddick, Lillian D.; Schoch, Conrad; Shkeda, Andrei; Storz, Susan S.; Sun, Hanzhen; Thibaud-Nissen, Francoise; Tolstoy, Igor; Tully, Raymond E.; Vatsan, Anjana R.; Wallin, Craig; Webb, David; Wu, Wendy; Landrum, Melissa J.; Kimchi, Avi; Tatusova, Tatiana; DiCuccio, Michael; Kitts, Paul; Murphy, Terence D.; Pruitt, Kim D.

    2016-01-01

    The RefSeq project at the National Center for Biotechnology Information (NCBI) maintains and curates a publicly available database of annotated genomic, transcript, and protein sequence records (http://www.ncbi.nlm.nih.gov/refseq/). The RefSeq project leverages the data submitted to the International Nucleotide Sequence Database Collaboration (INSDC) against a combination of computation, manual curation, and collaboration to produce a standard set of stable, non-redundant reference sequences. The RefSeq project augments these reference sequences with current knowledge including publications, functional features and informative nomenclature. The database currently represents sequences from more than 55 000 organisms (>4800 viruses, >40 000 prokaryotes and >10 000 eukaryotes; RefSeq release 71), ranging from a single record to complete genomes. This paper summarizes the current status of the viral, prokaryotic, and eukaryotic branches of the RefSeq project, reports on improvements to data access and details efforts to further expand the taxonomic representation of the collection. We also highlight diverse functional curation initiatives that support multiple uses of RefSeq data including taxonomic validation, genome annotation, comparative genomics, and clinical testing. We summarize our approach to utilizing available RNA-Seq and other data types in our manual curation process for vertebrate, plant, and other species, and describe a new direction for prokaryotic genomes and protein name management. PMID:26553804

  5. BioBuilder as a database development and functional annotation platform for proteins

    PubMed Central

    Navarro, J Daniel; Talreja, Naveen; Peri, Suraj; Vrushabendra, BM; Rashmi, BP; Padma, N; Surendranath, Vineeth; Jonnalagadda, Chandra Kiran; Kousthub, PS; Deshpande, Nandan; Shanker, K; Pandey, Akhilesh

    2004-01-01

    Background The explosion in biological information creates the need for databases that are easy to develop, easy to maintain and can be easily manipulated by annotators who are most likely to be biologists. However, deployment of scalable and extensible databases is not an easy task and generally requires substantial expertise in database development. Results BioBuilder is a Zope-based software tool that was developed to facilitate intuitive creation of protein databases. Protein data can be entered and annotated through web forms along with the flexibility to add customized annotation features to protein entries. A built-in review system permits a global team of scientists to coordinate their annotation efforts. We have already used BioBuilder to develop Human Protein Reference Database , a comprehensive annotated repository of the human proteome. The data can be exported in the extensible markup language (XML) format, which is rapidly becoming as the standard format for data exchange. Conclusions As the proteomic data for several organisms begins to accumulate, BioBuilder will prove to be an invaluable platform for functional annotation and development of customizable protein centric databases. BioBuilder is open source and is available under the terms of LGPL. PMID:15099404

  6. ASGARD: an open-access database of annotated transcriptomes for emerging model arthropod species.

    PubMed

    Zeng, Victor; Extavour, Cassandra G

    2012-01-01

    The increased throughput and decreased cost of next-generation sequencing (NGS) have shifted the bottleneck genomic research from sequencing to annotation, analysis and accessibility. This is particularly challenging for research communities working on organisms that lack the basic infrastructure of a sequenced genome, or an efficient way to utilize whatever sequence data may be available. Here we present a new database, the Assembled Searchable Giant Arthropod Read Database (ASGARD). This database is a repository and search engine for transcriptomic data from arthropods that are of high interest to multiple research communities but currently lack sequenced genomes. We demonstrate the functionality and utility of ASGARD using de novo assembled transcriptomes from the milkweed bug Oncopeltus fasciatus, the cricket Gryllus bimaculatus and the amphipod crustacean Parhyale hawaiensis. We have annotated these transcriptomes to assign putative orthology, coding region determination, protein domain identification and Gene Ontology (GO) term annotation to all possible assembly products. ASGARD allows users to search all assemblies by orthology annotation, GO term annotation or Basic Local Alignment Search Tool. User-friendly features of ASGARD include search term auto-completion suggestions based on database content, the ability to download assembly product sequences in FASTA format, direct links to NCBI data for predicted orthologs and graphical representation of the location of protein domains and matches to similar sequences from the NCBI non-redundant database. ASGARD will be a useful repository for transcriptome data from future NGS studies on these and other emerging model arthropods, regardless of sequencing platform, assembly or annotation status. This database thus provides easy, one-stop access to multi-species annotated transcriptome information. We anticipate that this database will be useful for members of multiple research communities, including developmental

  7. ASGARD: an open-access database of annotated transcriptomes for emerging model arthropod species.

    PubMed

    Zeng, Victor; Extavour, Cassandra G

    2012-01-01

    The increased throughput and decreased cost of next-generation sequencing (NGS) have shifted the bottleneck genomic research from sequencing to annotation, analysis and accessibility. This is particularly challenging for research communities working on organisms that lack the basic infrastructure of a sequenced genome, or an efficient way to utilize whatever sequence data may be available. Here we present a new database, the Assembled Searchable Giant Arthropod Read Database (ASGARD). This database is a repository and search engine for transcriptomic data from arthropods that are of high interest to multiple research communities but currently lack sequenced genomes. We demonstrate the functionality and utility of ASGARD using de novo assembled transcriptomes from the milkweed bug Oncopeltus fasciatus, the cricket Gryllus bimaculatus and the amphipod crustacean Parhyale hawaiensis. We have annotated these transcriptomes to assign putative orthology, coding region determination, protein domain identification and Gene Ontology (GO) term annotation to all possible assembly products. ASGARD allows users to search all assemblies by orthology annotation, GO term annotation or Basic Local Alignment Search Tool. User-friendly features of ASGARD include search term auto-completion suggestions based on database content, the ability to download assembly product sequences in FASTA format, direct links to NCBI data for predicted orthologs and graphical representation of the location of protein domains and matches to similar sequences from the NCBI non-redundant database. ASGARD will be a useful repository for transcriptome data from future NGS studies on these and other emerging model arthropods, regardless of sequencing platform, assembly or annotation status. This database thus provides easy, one-stop access to multi-species annotated transcriptome information. We anticipate that this database will be useful for members of multiple research communities, including developmental

  8. The H-Invitational Database (H-InvDB), a comprehensive annotation resource for human genes and transcripts*

    PubMed Central

    2008-01-01

    Here we report the new features and improvements in our latest release of the H-Invitational Database (H-InvDB; http://www.h-invitational.jp/), a comprehensive annotation resource for human genes and transcripts. H-InvDB, originally developed as an integrated database of the human transcriptome based on extensive annotation of large sets of full-length cDNA (FLcDNA) clones, now provides annotation for 120 558 human mRNAs extracted from the International Nucleotide Sequence Databases (INSD), in addition to 54 978 human FLcDNAs, in the latest release H-InvDB_4.6. We mapped those human transcripts onto the human genome sequences (NCBI build 36.1) and determined 34 699 human gene clusters, which could define 34 057 (98.1%) protein-coding and 642 (1.9%) non-protein-coding loci; 858 (2.5%) transcribed loci overlapped with predicted pseudogenes. For all these transcripts and genes, we provide comprehensive annotation including gene structures, gene functions, alternative splicing variants, functional non-protein-coding RNAs, functional domains, predicted sub cellular localizations, metabolic pathways, predictions of protein 3D structure, mapping of SNPs and microsatellite repeat motifs, co-localization with orphan diseases, gene expression profiles, orthologous genes, protein–protein interactions (PPI) and annotation for gene families. The current H-InvDB annotation resources consist of two main views: Transcript view and Locus view and eight sub-databases: the DiseaseInfo Viewer, H-ANGEL, the Clustering Viewer, G-integra, the TOPO Viewer, Evola, the PPI view and the Gene family/group. PMID:18089548

  9. Assessment of community-submitted ontology annotations from a novel database-journal partnership.

    PubMed

    Berardini, Tanya Z; Li, Donghui; Muller, Robert; Chetty, Raymond; Ploetz, Larry; Singh, Shanker; Wensel, April; Huala, Eva

    2012-01-01

    As the scientific literature grows, leading to an increasing volume of published experimental data, so does the need to access and analyze this data using computational tools. The most commonly used method to convert published experimental data on gene function into controlled vocabulary annotations relies on a professional curator, employed by a model organism database or a more general resource such as UniProt, to read published articles and compose annotation statements based on the articles' contents. A more cost-effective and scalable approach capable of capturing gene function data across the whole range of biological research organisms in computable form is urgently needed. We have analyzed a set of ontology annotations generated through collaborations between the Arabidopsis Information Resource and several plant science journals. Analysis of the submissions entered using the online submission tool shows that most community annotations were well supported and the ontology terms chosen were at an appropriate level of specificity. Of the 503 individual annotations that were submitted, 97% were approved and community submissions captured 72% of all possible annotations. This new method for capturing experimental results in a computable form provides a cost-effective way to greatly increase the available body of annotations without sacrificing annotation quality. Database URL: www.arabidopsis.org.

  10. BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models

    PubMed Central

    2010-01-01

    Background Quantitative models of biochemical and cellular systems are used to answer a variety of questions in the biological sciences. The number of published quantitative models is growing steadily thanks to increasing interest in the use of models as well as the development of improved software systems and the availability of better, cheaper computer hardware. To maximise the benefits of this growing body of models, the field needs centralised model repositories that will encourage, facilitate and promote model dissemination and reuse. Ideally, the models stored in these repositories should be extensively tested and encoded in community-supported and standardised formats. In addition, the models and their components should be cross-referenced with other resources in order to allow their unambiguous identification. Description BioModels Database http://www.ebi.ac.uk/biomodels/ is aimed at addressing exactly these needs. It is a freely-accessible online resource for storing, viewing, retrieving, and analysing published, peer-reviewed quantitative models of biochemical and cellular systems. The structure and behaviour of each simulation model distributed by BioModels Database are thoroughly checked; in addition, model elements are annotated with terms from controlled vocabularies as well as linked to relevant data resources. Models can be examined online or downloaded in various formats. Reaction network diagrams generated from the models are also available in several formats. BioModels Database also provides features such as online simulation and the extraction of components from large scale models into smaller submodels. Finally, the system provides a range of web services that external software systems can use to access up-to-date data from the database. Conclusions BioModels Database has become a recognised reference resource for systems biology. It is being used by the community in a variety of ways; for example, it is used to benchmark different simulation

  11. TogoTable: cross-database annotation system using the Resource Description Framework (RDF) data model

    PubMed Central

    Kawano, Shin; Watanabe, Tsutomu; Mizuguchi, Sohei; Araki, Norie; Katayama, Toshiaki; Yamaguchi, Atsuko

    2014-01-01

    TogoTable (http://togotable.dbcls.jp/) is a web tool that adds user-specified annotations to a table that a user uploads. Annotations are drawn from several biological databases that use the Resource Description Framework (RDF) data model. TogoTable uses database identifiers (IDs) in the table as a query key for searching. RDF data, which form a network called Linked Open Data (LOD), can be searched from SPARQL endpoints using a SPARQL query language. Because TogoTable uses RDF, it can integrate annotations from not only the reference database to which the IDs originally belong, but also externally linked databases via the LOD network. For example, annotations in the Protein Data Bank can be retrieved using GeneID through links provided by the UniProt RDF. Because RDF has been standardized by the World Wide Web Consortium, any database with annotations based on the RDF data model can be easily incorporated into this tool. We believe that TogoTable is a valuable Web tool, particularly for experimental biologists who need to process huge amounts of data such as high-throughput experimental output. PMID:24829452

  12. GBshape: a genome browser database for DNA shape annotations.

    PubMed

    Chiu, Tsu-Pei; Yang, Lin; Zhou, Tianyin; Main, Bradley J; Parker, Stephen C J; Nuzhdin, Sergey V; Tullius, Thomas D; Rohs, Remo

    2015-01-01

    Many regulatory mechanisms require a high degree of specificity in protein-DNA binding. Nucleotide sequence does not provide an answer to the question of why a protein binds only to a small subset of the many putative binding sites in the genome that share the same core motif. Whereas higher-order effects, such as chromatin accessibility, cooperativity and cofactors, have been described, DNA shape recently gained attention as another feature that fine-tunes the DNA binding specificities of some transcription factor families. Our Genome Browser for DNA shape annotations (GBshape; freely available at http://rohslab.cmb.usc.edu/GBshape/) provides minor groove width, propeller twist, roll, helix twist and hydroxyl radical cleavage predictions for the entire genomes of 94 organisms. Additional genomes can easily be added using the GBshape framework. GBshape can be used to visualize DNA shape annotations qualitatively in a genome browser track format, and to download quantitative values of DNA shape features as a function of genomic position at nucleotide resolution. As biological applications, we illustrate the periodicity of DNA shape features that are present in nucleosome-occupied sequences from human, fly and worm, and we demonstrate structural similarities between transcription start sites in the genomes of four Drosophila species.

  13. 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

  14. 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

  15. The Saccharomyces Genome Database: Exploring Genome Features and Their Annotations.

    PubMed

    Cherry, J Michael

    2015-12-01

    Genomic-scale assays result in data that provide information over the entire genome. Such base pair resolution data cannot be summarized easily except via a graphical viewer. A genome browser is a tool that displays genomic data and experimental results as horizontal tracks. Genome browsers allow searches for a chromosomal coordinate or a feature, such as a gene name, but they do not allow searches by function or upstream binding site. Entry into a genome browser requires that you identify the gene name or chromosomal coordinates for a region of interest. A track provides a representation for genomic results and is displayed as a row of data shown as line segments to indicate regions of the chromosome with a feature. Another type of track presents a graph or wiggle plot that indicates the processed signal intensity computed for a particular experiment or set of experiments. Wiggle plots are typical for genomic assays such as the various next-generation sequencing methods (e.g., chromatin immunoprecipitation [ChIP]-seq or RNA-seq), where it represents a peak of DNA binding, histone modification, or the mapping of an RNA sequence. Here we explore the browser that has been built into the Saccharomyces Genome Database (SGD).

  16. Non-redundant patent sequence databases with value-added annotations at two levels.

    PubMed

    Li, Weizhong; McWilliam, Hamish; de la Torre, Ana Richart; Grodowski, Adam; Benediktovich, Irina; Goujon, Mickael; Nauche, Stephane; Lopez, Rodrigo

    2010-01-01

    The European Bioinformatics Institute (EMBL-EBI) provides public access to patent data, including abstracts, chemical compounds and sequences. Sequences can appear multiple times due to the filing of the same invention with multiple patent offices, or the use of the same sequence by different inventors in different contexts. Information relating to the source invention may be incomplete, and biological information available in patent documents elsewhere may not be reflected in the annotation of the sequence. Search and analysis of these data have become increasingly challenging for both the scientific and intellectual-property communities. Here, we report a collection of non-redundant patent sequence databases, which cover the EMBL-Bank nucleotides patent class and the patent protein databases and contain value-added annotations from patent documents. The databases were created at two levels by the use of sequence MD5 checksums. Sequences within a level-1 cluster are 100% identical over their whole length. Level-2 clusters were defined by sub-grouping level-1 clusters based on patent family information. Value-added annotations, such as publication number corrections, earliest publication dates and feature collations, significantly enhance the quality of the data, allowing for better tracking and cross-referencing. The databases are available format: http://www.ebi.ac.uk/patentdata/nr/.

  17. 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

  18. ABS: a database of Annotated regulatory Binding Sites from orthologous promoters

    PubMed Central

    Blanco, Enrique; Farré, Domènec; Albà, M. Mar; Messeguer, Xavier; Guigó, Roderic

    2006-01-01

    Information about the genomic coordinates and the sequence of experimentally identified transcription factor binding sites is found scattered under a variety of diverse formats. The availability of standard collections of such high-quality data is important to design, evaluate and improve novel computational approaches to identify binding motifs on promoter sequences from related genes. ABS () is a public database of known binding sites identified in promoters of orthologous vertebrate genes that have been manually curated from bibliography. We have annotated 650 experimental binding sites from 68 transcription factors and 100 orthologous target genes in human, mouse, rat or chicken genome sequences. Computational predictions and promoter alignment information are also provided for each entry. A simple and easy-to-use web interface facilitates data retrieval allowing different views of the information. In addition, the release 1.0 of ABS includes a customizable generator of artificial datasets based on the known sites contained in the collection and an evaluation tool to aid during the training and the assessment of motif-finding programs. PMID:16381947

  19. Annotated checklist and database for vascular plants of the Jemez Mountains

    SciTech Connect

    Foxx, T. S.; Pierce, L.; Tierney, G. D.; Hansen, L. A.

    1998-03-01

    Studies done in the last 40 years have provided information to construct a checklist of the Jemez Mountains. The present database and checklist builds on the basic list compiled by Teralene Foxx and Gail Tierney in the early 1980s. The checklist is annotated with taxonomic information, geographic and biological information, economic uses, wildlife cover, revegetation potential, and ethnographic uses. There are nearly 1000 species that have been noted for the Jemez Mountains. This list is cross-referenced with the US Department of Agriculture Natural Resource Conservation Service PLANTS database species names and acronyms. All information will soon be available on a Web Page.

  20. circRNADb: A comprehensive database for human circular RNAs with protein-coding annotations

    PubMed Central

    Chen, Xiaoping; Han, Ping; Zhou, Tao; Guo, Xuejiang; Song, Xiaofeng; Li, Yan

    2016-01-01

    It has been known that circular RNAs are widely expressed in human tissues and cells, and play important regulatory roles in physiological or pathological processes. However, there is lack of comprehensively annotated human circular RNAs database. In this study we established a circRNA database, named as circRNADb, containing 32,914 human exonic circRNAs carefully selected from diversified sources. The detailed information of the circRNA, including genomic information, exon splicing, genome sequence, internal ribosome entry site (IRES), open reading frame (ORF) and references were provided in circRNADb. In addition, circRNAs were found to be able to encode proteins, which have not been reported in any species. 16328 circRNAs were annotated to have ORF longer than 100 amino acids, of which 7170 have IRES elements. 46 circRNAs from 37 genes were found to have their corresponding proteins expressed according mass spectrometry. The database provides the function of data search, browse, download, submit and feedback for the user to study particular circular RNA of interest and update the database continually. circRNADb will be built to be a biological information platform for circRNA molecules and related biological functions in the future. The database can be freely available through the web server at http://reprod.njmu.edu.cn/circrnadb. PMID:27725737

  1. Improving Genome Assemblies and Annotations for Nonhuman Primates

    PubMed Central

    Norgren, Robert B.

    2013-01-01

    The study of nonhuman primates (NHP) is key to understanding human evolution, in addition to being an important model for biomedical research. NHPs are especially important for translational medicine. There are now exciting opportunities to greatly increase the utility of these models by incorporating Next Generation (NextGen) sequencing into study design. Unfortunately, the draft status of nonhuman genomes greatly constrains what can currently be accomplished with available technology. Although all genomes contain errors, draft assemblies and annotations contain so many mistakes that they make currently available nonhuman primate genomes misleading to investigators conducting evolutionary studies; and these genomes are of insufficient quality to serve as references for NextGen studies. Fortunately, NextGen sequencing can be used in the production of greatly improved genomes. Existing Sanger sequences can be supplemented with NextGen whole genome, and exomic genomic sequences to create new, more complete and correct assemblies. Additional physical mapping, and an incorporation of information about gene structure, can be used to improve assignment of scaffolds to chromosomes. In addition, mRNA-sequence data can be used to economically acquire transcriptome information, which can be used for annotation. Some highly polymorphic and complex regions, for example MHC class I and immunoglobulin loci, will require extra effort to properly assemble and annotate. However, for the vast majority of genes, a modest investment in money, and a somewhat greater investment in time, can greatly improve assemblies and annotations sufficient to produce true, reference grade nonhuman primate genomes. Such resources can reasonably be expected to transform nonhuman primate research. PMID:24174438

  2. The Saccharomyces Genome Database: Gene Product Annotation of Function, Process, and Component.

    PubMed

    Cherry, J Michael

    2015-12-01

    An ontology is a highly structured form of controlled vocabulary. Each entry in the ontology is commonly called a term. These terms are used when talking about an annotation. However, each term has a definition that, like the definition of a word found within a dictionary, provides the complete usage and detailed explanation of the term. It is critical to consult a term's definition because the distinction between terms can be subtle. The use of ontologies in biology started as a way of unifying communication between scientific communities and to provide a standard dictionary for different topics, including molecular functions, biological processes, mutant phenotypes, chemical properties and structures. The creation of ontology terms and their definitions often requires debate to reach agreement but the result has been a unified descriptive language used to communicate knowledge. In addition to terms and definitions, ontologies require a relationship used to define the type of connection between terms. In an ontology, a term can have more than one parent term, the term above it in an ontology, as well as more than one child, the term below it in the ontology. Many ontologies are used to construct annotations in the Saccharomyces Genome Database (SGD), as in all modern biological databases; however, Gene Ontology (GO), a descriptive system used to categorize gene function, is the most extensively used ontology in SGD annotations. Examples included in this protocol illustrate the structure and features of this ontology.

  3. Biological Database of Images and Genomes: tools for community annotations linking image and genomic information

    PubMed Central

    Oberlin, Andrew T; Jurkovic, Dominika A; Balish, Mitchell F; Friedberg, Iddo

    2013-01-01

    Genomic data and biomedical imaging data are undergoing exponential growth. However, our understanding of the phenotype–genotype connection linking the two types of data is lagging behind. While there are many types of software that enable the manipulation and analysis of image data and genomic data as separate entities, there is no framework established for linking the two. We present a generic set of software tools, BioDIG, that allows linking of image data to genomic data. BioDIG tools can be applied to a wide range of research problems that require linking images to genomes. BioDIG features the following: rapid construction of web-based workbenches, community-based annotation, user management and web services. By using BioDIG to create websites, researchers and curators can rapidly annotate a large number of images with genomic information. Here we present the BioDIG software tools that include an image module, a genome module and a user management module. We also introduce a BioDIG-based website, MyDIG, which is being used to annotate images of mycoplasmas. Database URL: BioDIG website: http://biodig.org BioDIG source code repository: http://github.com/FriedbergLab/BioDIG The MyDIG database: http://mydig.biodig.org/ PMID:23550062

  4. BambooGDB: a bamboo genome database with functional annotation and an analysis platform

    PubMed Central

    Zhao, Hansheng; Peng, Zhenhua; Fei, Benhua; Li, Lubin; Hu, Tao; Gao, Zhimin; Jiang, Zehui

    2014-01-01

    Bamboo, as one of the most important non-timber forest products and fastest-growing plants in the world, represents the only major lineage of grasses that is native to forests. Recent success on the first high-quality draft genome sequence of moso bamboo (Phyllostachys edulis) provides new insights on bamboo genetics and evolution. To further extend our understanding on bamboo genome and facilitate future studies on the basis of previous achievements, here we have developed BambooGDB, a bamboo genome database with functional annotation and analysis platform. The de novo sequencing data, together with the full-length complementary DNA and RNA-seq data of moso bamboo composed the main contents of this database. Based on these sequence data, a comprehensively functional annotation for bamboo genome was made. Besides, an analytical platform composed of comparative genomic analysis, protein–protein interactions network, pathway analysis and visualization of genomic data was also constructed. As discovery tools to understand and identify biological mechanisms of bamboo, the platform can be used as a systematic framework for helping and designing experiments for further validation. Moreover, diverse and powerful search tools and a convenient browser were incorporated to facilitate the navigation of these data. As far as we know, this is the first genome database for bamboo. Through integrating high-throughput sequencing data, a full functional annotation and several analysis modules, BambooGDB aims to provide worldwide researchers with a central genomic resource and an extensible analysis platform for bamboo genome. BambooGDB is freely available at http://www.bamboogdb.org/. Database URL: http://www.bamboogdb.org PMID:24602877

  5. LNCipedia: a database for annotated human lncRNA transcript sequences and structures

    PubMed Central

    Volders, Pieter-Jan; Helsens, Kenny; Wang, Xiaowei; Menten, Björn; Martens, Lennart; Gevaert, Kris; Vandesompele, Jo; Mestdagh, Pieter

    2013-01-01

    Here, we present LNCipedia (http://www.lncipedia.org), a novel database for human long non-coding RNA (lncRNA) transcripts and genes. LncRNAs constitute a large and diverse class of non-coding RNA genes. Although several lncRNAs have been functionally annotated, the majority remains to be characterized. Different high-throughput methods to identify new lncRNAs (including RNA sequencing and annotation of chromatin-state maps) have been applied in various studies resulting in multiple unrelated lncRNA data sets. LNCipedia offers 21 488 annotated human lncRNA transcripts obtained from different sources. In addition to basic transcript information and gene structure, several statistics are determined for each entry in the database, such as secondary structure information, protein coding potential and microRNA binding sites. Our analyses suggest that, much like microRNAs, many lncRNAs have a significant secondary structure, in-line with their presumed association with proteins or protein complexes. Available literature on specific lncRNAs is linked, and users or authors can submit articles through a web interface. Protein coding potential is assessed by two different prediction algorithms: Coding Potential Calculator and HMMER. In addition, a novel strategy has been integrated for detecting potentially coding lncRNAs by automatically re-analysing the large body of publicly available mass spectrometry data in the PRIDE database. LNCipedia is publicly available and allows users to query and download lncRNA sequences and structures based on different search criteria. The database may serve as a resource to initiate small- and large-scale lncRNA studies. As an example, the LNCipedia content was used to develop a custom microarray for expression profiling of all available lncRNAs. PMID:23042674

  6. Design and implementation of a database for Brucella melitensis genome annotation.

    PubMed

    De Hertogh, Benoît; Lahlimi, Leïla; Lambert, Christophe; Letesson, Jean-Jacques; Depiereux, Eric

    2008-03-18

    The genome sequences of three Brucella biovars and of some species close to Brucella sp. have become available, leading to new relationship analysis. Moreover, the automatic genome annotation of the pathogenic bacteria Brucella melitensis has been manually corrected by a consortium of experts, leading to 899 modifications of start sites predictions among the 3198 open reading frames (ORFs) examined. This new annotation, coupled with the results of automatic annotation tools of the complete genome sequences of the B. melitensis genome (including BLASTs to 9 genomes close to Brucella), provides numerous data sets related to predicted functions, biochemical properties and phylogenic comparisons. To made these results available, alphaPAGe, a functional auto-updatable database of the corrected sequence genome of B. melitensis, has been built, using the entity-relationship (ER) approach and a multi-purpose database structure. A friendly graphical user interface has been designed, and users can carry out different kinds of information by three levels of queries: (1) the basic search use the classical keywords or sequence identifiers; (2) the original advanced search engine allows to combine (by using logical operators) numerous criteria: (a) keywords (textual comparison) related to the pCDS's function, family domains and cellular localization; (b) physico-chemical characteristics (numerical comparison) such as isoelectric point or molecular weight and structural criteria such as the nucleic length or the number of transmembrane helix (TMH); (c) similarity scores with Escherichia coli and 10 species phylogenetically close to B. melitensis; (3) complex queries can be performed by using a SQL field, which allows all queries respecting the database's structure. The database is publicly available through a Web server at the following url: http://www.fundp.ac.be/urbm/bioinfo/aPAGe.

  7. PDEStrIAn: A Phosphodiesterase Structure and Ligand Interaction Annotated Database As a Tool for Structure-Based Drug Design.

    PubMed

    Jansen, Chimed; Kooistra, Albert J; Kanev, Georgi K; Leurs, Rob; de Esch, Iwan J P; de Graaf, Chris

    2016-08-11

    A systematic analysis is presented of the 220 phosphodiesterase (PDE) catalytic domain crystal structures present in the Protein Data Bank (PDB) with a focus on PDE-ligand interactions. The consistent structural alignment of 57 PDE ligand binding site residues enables the systematic analysis of PDE-ligand interaction fingerprints (IFPs), the identification of subtype-specific PDE-ligand interaction features, and the classification of ligands according to their binding modes. We illustrate how systematic mining of this phosphodiesterase structure and ligand interaction annotated (PDEStrIAn) database provides new insights into how conserved and selective PDE interaction hot spots can accommodate the large diversity of chemical scaffolds in PDE ligands. A substructure analysis of the cocrystallized PDE ligands in combination with those in the ChEMBL database provides a toolbox for scaffold hopping and ligand design. These analyses lead to an improved understanding of the structural requirements of PDE binding that will be useful in future drug discovery studies.

  8. Construction of customized sub-databases from NCBI-nr database for rapid annotation of huge metagenomic datasets using a combined BLAST and MEGAN approach.

    PubMed

    Yu, Ke; Zhang, Tong

    2013-01-01

    We developed a fast method to construct local sub-databases from the NCBI-nr database for the quick similarity search and annotation of huge metagenomic datasets based on BLAST-MEGAN approach. A three-step sub-database annotation pipeline (SAP) was further proposed to conduct the annotation in a much more time-efficient way which required far less computational capacity than the direct NCBI-nr database BLAST-MEGAN approach. The 1(st) BLAST of SAP was conducted using the original metagenomic dataset against the constructed sub-database for a quick screening of candidate target sequences. Then, the candidate target sequences identified in the 1(st) BLAST were subjected to the 2(nd) BLAST against the whole NCBI-nr database. The BLAST results were finally annotated using MEGAN to filter out those mistakenly selected sequences in the 1(st) BLAST to guarantee the accuracy of the results. Based on the tests conducted in this study, SAP achieved a speedup of ~150-385 times at the BLAST e-value of 1e-5, compared to the direct BLAST against NCBI-nr database. The annotation results of SAP are exactly in agreement with those of the direct NCBI-nr database BLAST-MEGAN approach, which is very time-consuming and computationally intensive. Selecting rigorous thresholds (e.g. e-value of 1e-10) would further accelerate SAP process. The SAP pipeline may also be coupled with novel similarity search tools (e.g. RAPsearch) other than BLAST to achieve even faster annotation of huge metagenomic datasets. Above all, this sub-database construction method and SAP pipeline provides a new time-efficient and convenient annotation similarity search strategy for laboratories without access to high performance computing facilities. SAP also offers a solution to high performance computing facilities for the processing of more similarity search tasks. PMID:23573212

  9. Global profiling of Shewanella oneidensis MR-1: expression of hypothetical genes and improved functional annotations.

    PubMed

    Kolker, Eugene; Picone, Alex F; Galperin, Michael Y; Romine, Margaret F; Higdon, Roger; Makarova, Kira S; Kolker, Natali; Anderson, Gordon A; Qiu, Xiaoyun; Auberry, Kenneth J; Babnigg, Gyorgy; Beliaev, Alex S; Edlefsen, Paul; Elias, Dwayne A; Gorby, Yuri A; Holzman, Ted; Klappenbach, Joel A; Konstantinidis, Konstantinos T; Land, Miriam L; Lipton, Mary S; McCue, Lee-Ann; Monroe, Matthew; Pasa-Tolic, Ljiljana; Pinchuk, Grigoriy; Purvine, Samuel; Serres, Margrethe H; Tsapin, Sasha; Zakrajsek, Brian A; Zhu, Wenhong; Zhou, Jizhong; Larimer, Frank W; Lawrence, Charles E; Riley, Monica; Collart, Frank R; Yates, John R; Smith, Richard D; Giometti, Carol S; Nealson, Kenneth H; Fredrickson, James K; Tiedje, James M

    2005-02-01

    The gamma-proteobacterium Shewanella oneidensis strain MR-1 is a metabolically versatile organism that can reduce a wide range of organic compounds, metal ions, and radionuclides. Similar to most other sequenced organisms, approximately 40% of the predicted ORFs in the S. oneidensis genome were annotated as uncharacterized "hypothetical" genes. We implemented an integrative approach by using experimental and computational analyses to provide more detailed insight into gene function. Global expression profiles were determined for cells after UV irradiation and under aerobic and suboxic growth conditions. Transcriptomic and proteomic analyses confidently identified 538 hypothetical genes as expressed in S. oneidensis cells both as mRNAs and proteins (33% of all predicted hypothetical proteins). Publicly available analysis tools and databases and the expression data were applied to improve the annotation of these genes. The annotation results were scored by using a seven-category schema that ranked both confidence and precision of the functional assignment. We were able to identify homologs for nearly all of these hypothetical proteins (97%), but could confidently assign exact biochemical functions for only 16 proteins (category 1; 3%). Altogether, computational and experimental evidence provided functional assignments or insights for 240 more genes (categories 2-5; 45%). These functional annotations advance our understanding of genes involved in vital cellular processes, including energy conversion, ion transport, secondary metabolism, and signal transduction. We propose that this integrative approach offers a valuable means to undertake the enormous challenge of characterizing the rapidly growing number of hypothetical proteins with each newly sequenced genome. PMID:15684069

  10. Global profiling of Shewanella oneidensis MR-1: Expression of hypothetical genes and improved functional annotations

    SciTech Connect

    Picone, Alex F.; Galperin, Michael Y.; Romine, Margaret; Higdon, Roger; Makarova, Kira S.; Kolker, Natali; Anderson, Gordon A; Qiu, Xiaoyun; Babnigg, Gyorgy; Beliaev, Alexander S; Edlefsen, Paul; Elias, Dwayne A.; Gorby, Dr. Yuri A.; Holzman, Ted; Klappenbach, Joel; Konstantinidis, Konstantinos T; Land, Miriam L; Lipton, Mary S.; McCue, Lee Ann; Monroe, Matthew; Pasa-Tolic, Ljiljana; Pinchuk, Grigoriy; Purvine, Samuel; Serres, Margrethe H.; Tsapin, Sasha; Zakrajsek, Brian A.; Zhu, Wenguang; Zhou, Jizhong; Larimer, Frank W; Lawrence, Charles E.; Riley, Monica; Collart, Frank; YatesIII, John R.; Smith, Richard D.; Nealson, Kenneth H.; Fredrickson, James K; Tiedje, James M.

    2005-01-01

    The gamma-proteobacterium Shewanella oneidensis strain MR-1 is a metabolically versatile organism that can reduce a wide range of organic compounds, metal ions, and radionuclides. Similar to most other sequenced organisms, approximate to40% of the predicted ORFs in the S. oneidensis genome were annotated as uncharacterized "hypothetical" genes. We implemented an integrative approach by using experimental and computational analyses to provide more detailed insight into gene function. Global expression profiles were determined for cells after UV irradiation and under aerobic and suboxic growth conditions. Transcriptomic and proteomic analyses confidently identified 538 hypothetical genes as expressed in S. oneidensis cells both as mRNAs and proteins (33% of all predicted hypothetical proteins). Publicly available analysis tools and databases and the expression data were applied to improve the annotation of these genes. The annotation results were scored by using a seven-category schema that ranked both confidence and precision of the functional assignment. We were able to identify homologs for nearly all of these hypothetical proteins (97%), but could confidently assign exact biochemical functions for only 16 proteins (category 1; 3%). Altogether, computational and experimental evidence provided functional assignments or insights for 240 more genes (categories 2-5; 45%). These functional annotations advance our understanding of genes involved in vital cellular processes, including energy conversion, ion transport, secondary metabolism, and signal transduction. We propose that this integrative approach offers a valuable means to undertake the enormous challenge of characterizing the rapidly growing number of hypothetical proteins with each newly sequenced genome.

  11. MAKER2: an annotation pipeline and genome-database management tool for second-generation genome projects

    PubMed Central

    2011-01-01

    Background Second-generation sequencing technologies are precipitating major shifts with regards to what kinds of genomes are being sequenced and how they are annotated. While the first generation of genome projects focused on well-studied model organisms, many of today's projects involve exotic organisms whose genomes are largely terra incognita. This complicates their annotation, because unlike first-generation projects, there are no pre-existing 'gold-standard' gene-models with which to train gene-finders. Improvements in genome assembly and the wide availability of mRNA-seq data are also creating opportunities to update and re-annotate previously published genome annotations. Today's genome projects are thus in need of new genome annotation tools that can meet the challenges and opportunities presented by second-generation sequencing technologies. Results We present MAKER2, a genome annotation and data management tool designed for second-generation genome projects. MAKER2 is a multi-threaded, parallelized application that can process second-generation datasets of virtually any size. We show that MAKER2 can produce accurate annotations for novel genomes where training-data are limited, of low quality or even non-existent. MAKER2 also provides an easy means to use mRNA-seq data to improve annotation quality; and it can use these data to update legacy annotations, significantly improving their quality. We also show that MAKER2 can evaluate the quality of genome annotations, and identify and prioritize problematic annotations for manual review. Conclusions MAKER2 is the first annotation engine specifically designed for second-generation genome projects. MAKER2 scales to datasets of any size, requires little in the way of training data, and can use mRNA-seq data to improve annotation quality. It can also update and manage legacy genome annotation datasets. PMID:22192575

  12. Improved gene ontology annotation for biofilm formation, filamentous growth, and phenotypic switching in Candida albicans.

    PubMed

    Inglis, Diane O; Skrzypek, Marek S; Arnaud, Martha B; Binkley, Jonathan; Shah, Prachi; Wymore, Farrell; Sherlock, Gavin

    2013-01-01

    The opportunistic fungal pathogen Candida albicans is a significant medical threat, especially for immunocompromised patients. Experimental research has focused on specific areas of C. albicans biology, with the goal of understanding the multiple factors that contribute to its pathogenic potential. Some of these factors include cell adhesion, invasive or filamentous growth, and the formation of drug-resistant biofilms. The Gene Ontology (GO) (www.geneontology.org) is a standardized vocabulary that the Candida Genome Database (CGD) (www.candidagenome.org) and other groups use to describe the functions of gene products. To improve the breadth and accuracy of pathogenicity-related gene product descriptions and to facilitate the description of as yet uncharacterized but potentially pathogenicity-related genes in Candida species, CGD undertook a three-part project: first, the addition of terms to the biological process branch of the GO to improve the description of fungus-related processes; second, manual recuration of gene product annotations in CGD to use the improved GO vocabulary; and third, computational ortholog-based transfer of GO annotations from experimentally characterized gene products, using these new terms, to uncharacterized orthologs in other Candida species. Through genome annotation and analysis, we identified candidate pathogenicity genes in seven non-C. albicans Candida species and in one additional C. albicans strain, WO-1. We also defined a set of C. albicans genes at the intersection of biofilm formation, filamentous growth, pathogenesis, and phenotypic switching of this opportunistic fungal pathogen, which provides a compelling list of candidates for further experimentation.

  13. Improving tRNAscan-SE Annotation Results via Ensemble Classifiers.

    PubMed

    Zou, Quan; Guo, Jiasheng; Ju, Ying; Wu, Meihong; Zeng, Xiangxiang; Hong, Zhiling

    2015-11-01

    tRNAScan-SE is a tRNA detection program that is widely used for tRNA annotation; however, the false positive rate of tRNAScan-SE is unacceptable for large sequences. Here, we used a machine learning method to try to improve the tRNAScan-SE results. A new predictor, tRNA-Predict, was designed. We obtained real and pseudo-tRNA sequences as training data sets using tRNAScan-SE and constructed three different tRNA feature sets. We then set up an ensemble classifier, LibMutil, to predict tRNAs from the training data. The positive data set of 623 tRNA sequences was obtained from tRNAdb 2009 and the negative data set was the false positive tRNAs predicted by tRNAscan-SE. Our in silico experiments revealed a prediction accuracy rate of 95.1 % for tRNA-Predict using 10-fold cross-validation. tRNA-Predict was developed to distinguish functional tRNAs from pseudo-tRNAs rather than to predict tRNAs from a genome-wide scan. However, tRNA-Predict can work with the output of tRNAscan-SE, which is a genome-wide scanning method, to improve the tRNAscan-SE annotation results. The tRNA-Predict web server is accessible at http://datamining.xmu.edu.cn/∼gjs/tRNA-Predict. PMID:27491037

  14. Semi-Automated Annotation of Biobank Data Using Standard Medical Terminologies in a Graph Database.

    PubMed

    Hofer, Philipp; Neururer, Sabrina; Goebel, Georg

    2016-01-01

    Data describing biobank resources frequently contains unstructured free-text information or insufficient coding standards. (Bio-) medical ontologies like Orphanet Rare Diseases Ontology (ORDO) or the Human Disease Ontology (DOID) provide a high number of concepts, synonyms and entity relationship properties. Such standard terminologies increase quality and granularity of input data by adding comprehensive semantic background knowledge from validated entity relationships. Moreover, cross-references between terminology concepts facilitate data integration across databases using different coding standards. In order to encourage the use of standard terminologies, our aim is to identify and link relevant concepts with free-text diagnosis inputs within a biobank registry. Relevant concepts are selected automatically by lexical matching and SPARQL queries against a RDF triplestore. To ensure correctness of annotations, proposed concepts have to be confirmed by medical data administration experts before they are entered into the registry database. Relevant (bio-) medical terminologies describing diseases and phenotypes were identified and stored in a graph database which was tied to a local biobank registry. Concept recommendations during data input trigger a structured description of medical data and facilitate data linkage between heterogeneous systems. PMID:27577487

  15. SureChEMBL: a large-scale, chemically annotated patent document database

    PubMed Central

    Papadatos, George; Davies, Mark; Dedman, Nathan; Chambers, Jon; Gaulton, Anna; Siddle, James; Koks, Richard; Irvine, Sean A.; Pettersson, Joe; Goncharoff, Nicko; Hersey, Anne; Overington, John P.

    2016-01-01

    SureChEMBL is a publicly available large-scale resource containing compounds extracted from the full text, images and attachments of patent documents. The data are extracted from the patent literature according to an automated text and image-mining pipeline on a daily basis. SureChEMBL provides access to a previously unavailable, open and timely set of annotated compound-patent associations, complemented with sophisticated combined structure and keyword-based search capabilities against the compound repository and patent document corpus; given the wealth of knowledge hidden in patent documents, analysis of SureChEMBL data has immediate applications in drug discovery, medicinal chemistry and other commercial areas of chemical science. Currently, the database contains 17 million compounds extracted from 14 million patent documents. Access is available through a dedicated web-based interface and data downloads at: https://www.surechembl.org/. PMID:26582922

  16. SureChEMBL: a large-scale, chemically annotated patent document database.

    PubMed

    Papadatos, George; Davies, Mark; Dedman, Nathan; Chambers, Jon; Gaulton, Anna; Siddle, James; Koks, Richard; Irvine, Sean A; Pettersson, Joe; Goncharoff, Nicko; Hersey, Anne; Overington, John P

    2016-01-01

    SureChEMBL is a publicly available large-scale resource containing compounds extracted from the full text, images and attachments of patent documents. The data are extracted from the patent literature according to an automated text and image-mining pipeline on a daily basis. SureChEMBL provides access to a previously unavailable, open and timely set of annotated compound-patent associations, complemented with sophisticated combined structure and keyword-based search capabilities against the compound repository and patent document corpus; given the wealth of knowledge hidden in patent documents, analysis of SureChEMBL data has immediate applications in drug discovery, medicinal chemistry and other commercial areas of chemical science. Currently, the database contains 17 million compounds extracted from 14 million patent documents. Access is available through a dedicated web-based interface and data downloads at: https://www.surechembl.org/.

  17. SureChEMBL: a large-scale, chemically annotated patent document database.

    PubMed

    Papadatos, George; Davies, Mark; Dedman, Nathan; Chambers, Jon; Gaulton, Anna; Siddle, James; Koks, Richard; Irvine, Sean A; Pettersson, Joe; Goncharoff, Nicko; Hersey, Anne; Overington, John P

    2016-01-01

    SureChEMBL is a publicly available large-scale resource containing compounds extracted from the full text, images and attachments of patent documents. The data are extracted from the patent literature according to an automated text and image-mining pipeline on a daily basis. SureChEMBL provides access to a previously unavailable, open and timely set of annotated compound-patent associations, complemented with sophisticated combined structure and keyword-based search capabilities against the compound repository and patent document corpus; given the wealth of knowledge hidden in patent documents, analysis of SureChEMBL data has immediate applications in drug discovery, medicinal chemistry and other commercial areas of chemical science. Currently, the database contains 17 million compounds extracted from 14 million patent documents. Access is available through a dedicated web-based interface and data downloads at: https://www.surechembl.org/. PMID:26582922

  18. Re-Annotator: Annotation Pipeline for Microarray Probe Sequences.

    PubMed

    Arloth, Janine; Bader, Daniel M; Röh, Simone; Altmann, Andre

    2015-01-01

    Microarray technologies are established approaches for high throughput gene expression, methylation and genotyping analysis. An accurate mapping of the array probes is essential to generate reliable biological findings. However, manufacturers of the microarray platforms typically provide incomplete and outdated annotation tables, which often rely on older genome and transcriptome versions that differ substantially from up-to-date sequence databases. Here, we present the Re-Annotator, a re-annotation pipeline for microarray probe sequences. It is primarily designed for gene expression microarrays but can also be adapted to other types of microarrays. The Re-Annotator uses a custom-built mRNA reference database to identify the positions of gene expression array probe sequences. We applied Re-Annotator to the Illumina Human-HT12 v4 microarray platform and found that about one quarter (25%) of the probes differed from the manufacturer's annotation. In further computational experiments on experimental gene expression data, we compared Re-Annotator to another probe re-annotation tool, ReMOAT, and found that Re-Annotator provided an improved re-annotation of microarray probes. A thorough re-annotation of probe information is crucial to any microarray analysis. The Re-Annotator pipeline is freely available at http://sourceforge.net/projects/reannotator along with re-annotated files for Illumina microarrays HumanHT-12 v3/v4 and MouseRef-8 v2.

  19. Novel transcriptome assembly and improved annotation of the whiteleg shrimp (Litopenaeus vannamei), a dominant crustacean in global seafood mariculture.

    PubMed

    Ghaffari, Noushin; Sanchez-Flores, Alejandro; Doan, Ryan; Garcia-Orozco, Karina D; Chen, Patricia L; Ochoa-Leyva, Adrian; Lopez-Zavala, Alonso A; Carrasco, J Salvador; Hong, Chris; Brieba, Luis G; Rudiño-Piñera, Enrique; Blood, Philip D; Sawyer, Jason E; Johnson, Charles D; Dindot, Scott V; Sotelo-Mundo, Rogerio R; Criscitiello, Michael F

    2014-11-25

    We present a new transcriptome assembly of the Pacific whiteleg shrimp (Litopenaeus vannamei), the species most farmed for human consumption. Its functional annotation, a substantial improvement over previous ones, is provided freely. RNA-Seq with Illumina HiSeq technology was used to analyze samples extracted from shrimp abdominal muscle, hepatopancreas, gills and pleopods. We used the Trinity and Trinotate software suites for transcriptome assembly and annotation, respectively. The quality of this assembly and the affiliated targeted homology searches greatly enrich the curated transcripts currently available in public databases for this species. Comparison with the model arthropod Daphnia allows some insights into defining characteristics of decapod crustaceans. This large-scale gene discovery gives the broadest depth yet to the annotated transcriptome of this important species and should be of value to ongoing genomics and immunogenetic resistance studies in this shrimp of paramount global economic importance.

  20. Novel transcriptome assembly and improved annotation of the whiteleg shrimp (Litopenaeus vannamei), a dominant crustacean in global seafood mariculture.

    PubMed

    Ghaffari, Noushin; Sanchez-Flores, Alejandro; Doan, Ryan; Garcia-Orozco, Karina D; Chen, Patricia L; Ochoa-Leyva, Adrian; Lopez-Zavala, Alonso A; Carrasco, J Salvador; Hong, Chris; Brieba, Luis G; Rudiño-Piñera, Enrique; Blood, Philip D; Sawyer, Jason E; Johnson, Charles D; Dindot, Scott V; Sotelo-Mundo, Rogerio R; Criscitiello, Michael F

    2014-01-01

    We present a new transcriptome assembly of the Pacific whiteleg shrimp (Litopenaeus vannamei), the species most farmed for human consumption. Its functional annotation, a substantial improvement over previous ones, is provided freely. RNA-Seq with Illumina HiSeq technology was used to analyze samples extracted from shrimp abdominal muscle, hepatopancreas, gills and pleopods. We used the Trinity and Trinotate software suites for transcriptome assembly and annotation, respectively. The quality of this assembly and the affiliated targeted homology searches greatly enrich the curated transcripts currently available in public databases for this species. Comparison with the model arthropod Daphnia allows some insights into defining characteristics of decapod crustaceans. This large-scale gene discovery gives the broadest depth yet to the annotated transcriptome of this important species and should be of value to ongoing genomics and immunogenetic resistance studies in this shrimp of paramount global economic importance. PMID:25420880

  1. Novel transcriptome assembly and improved annotation of the whiteleg shrimp (Litopenaeus vannamei), a dominant crustacean in global seafood mariculture

    PubMed Central

    Ghaffari, Noushin; Sanchez-Flores, Alejandro; Doan, Ryan; Garcia-Orozco, Karina D.; Chen, Patricia L.; Ochoa-Leyva, Adrian; Lopez-Zavala, Alonso A.; Carrasco, J. Salvador; Hong, Chris; Brieba, Luis G.; Rudiño-Piñera, Enrique; Blood, Philip D.; Sawyer, Jason E.; Johnson, Charles D.; Dindot, Scott V.; Sotelo-Mundo, Rogerio R.; Criscitiello, Michael F.

    2014-01-01

    We present a new transcriptome assembly of the Pacific whiteleg shrimp (Litopenaeus vannamei), the species most farmed for human consumption. Its functional annotation, a substantial improvement over previous ones, is provided freely. RNA-Seq with Illumina HiSeq technology was used to analyze samples extracted from shrimp abdominal muscle, hepatopancreas, gills and pleopods. We used the Trinity and Trinotate software suites for transcriptome assembly and annotation, respectively. The quality of this assembly and the affiliated targeted homology searches greatly enrich the curated transcripts currently available in public databases for this species. Comparison with the model arthropod Daphnia allows some insights into defining characteristics of decapod crustaceans. This large-scale gene discovery gives the broadest depth yet to the annotated transcriptome of this important species and should be of value to ongoing genomics and immunogenetic resistance studies in this shrimp of paramount global economic importance. PMID:25420880

  2. The MitoDrome database annotates and compares the OXPHOS nuclear genes of Drosophila melanogaster, Drosophila pseudoobscura and Anopheles gambiae.

    PubMed

    D'Elia, Domenica; Catalano, Domenico; Licciulli, Flavio; Turi, Antonio; Tripoli, Gaetano; Porcelli, Damiano; Saccone, Cecilia; Caggese, Corrado

    2006-10-01

    The oxidative phosphorylation (OXPHOS) is the primary energy-producing process of all aerobic organisms and the only cellular function under the dual control of both the mitochondrial and the nuclear genomes. Functional characterization and evolutionary study of the OXPHOS system is of great importance for the understanding of many as yet unclear aspects of nucleus-mitochondrion genomic co-evolution and co-regulation gene networks. The MitoDrome database is a web-based database which provides genomic annotations about nuclear genes of Drosophila melanogaster encoding for mitochondrial proteins. Recently, MitoDrome has included a new section annotating genomic information about OXPHOS genes in Drosophila pseudoobscura and Anopheles gambiae and their comparative analysis with their Drosophila melanogaster and human counterparts. The introduction of this new comparative annotation section into MitoDrome is expected to be a useful resource for both functional and structural genomics related to the OXPHOS system.

  3. A database for coconut crop improvement

    PubMed Central

    Rajagopal, Velamoor; Manimekalai, Ramaswamy; Devakumar, Krishnamurthy; Rajesh; Karun, Anitha; Niral, Vittal; Gopal, Murali; Aziz, Shamina; Gunasekaran, Marimuthu; Kumar, Mundappurathe Ramesh; Chandrasekar, Arumugam

    2005-01-01

    Coconut crop improvement requires a number of biotechnology and bioinformatics tools. A database containing information on CG (coconut germplasm), CCI (coconut cultivar identification), CD (coconut disease), MIFSPC (microbial information systems in plantation crops) and VO (vegetable oils) is described. The database was developed using MySQL and PostgreSQL running in Linux operating system. The database interface is developed in PHP, HTML and JAVA. Availability http://www.bioinfcpcri.org PMID:17597858

  4. Ontology modularization to improve semantic medical image annotation.

    PubMed

    Wennerberg, Pinar; Schulz, Klaus; Buitelaar, Paul

    2011-02-01

    Searching for medical images and patient reports is a significant challenge in a clinical setting. The contents of such documents are often not described in sufficient detail thus making it difficult to utilize the inherent wealth of information contained within them. Semantic image annotation addresses this problem by describing the contents of images and reports using medical ontologies. Medical images and patient reports are then linked to each other through common annotations. Subsequently, search algorithms can more effectively find related sets of documents on the basis of these semantic descriptions. A prerequisite to realizing such a semantic search engine is that the data contained within should have been previously annotated with concepts from medical ontologies. One major challenge in this regard is the size and complexity of medical ontologies as annotation sources. Manual annotation is particularly time consuming labor intensive in a clinical environment. In this article we propose an approach to reducing the size of clinical ontologies for more efficient manual image and text annotation. More precisely, our goal is to identify smaller fragments of a large anatomy ontology that are relevant for annotating medical images from patients suffering from lymphoma. Our work is in the area of ontology modularization, which is a recent and active field of research. We describe our approach, methods and data set in detail and we discuss our results.

  5. MITOS: improved de novo metazoan mitochondrial genome annotation.

    PubMed

    Bernt, Matthias; Donath, Alexander; Jühling, Frank; Externbrink, Fabian; Florentz, Catherine; Fritzsch, Guido; Pütz, Joern; Middendorf, Martin; Stadler, Peter F

    2013-11-01

    About 2000 completely sequenced mitochondrial genomes are available from the NCBI RefSeq data base together with manually curated annotations of their protein-coding genes, rRNAs, and tRNAs. This annotation information, which has accumulated over two decades, has been obtained with a diverse set of computational tools and annotation strategies. Despite all efforts of manual curation it is still plagued by misassignments of reading directions, erroneous gene names, and missing as well as false positive annotations in particular for the RNA genes. Taken together, this causes substantial problems for fully automatic pipelines that aim to use these data comprehensively for studies of animal phylogenetics and the molecular evolution of mitogenomes. The MITOS pipeline is designed to compute a consistent de novo annotation of the mitogenomic sequences. We show that the results of MITOS match RefSeq and MitoZoa in terms of annotation coverage and quality. At the same time we avoid biases, inconsistencies of nomenclature, and typos originating from manual curation strategies. The MITOS pipeline is accessible online at http://mitos.bioinf.uni-leipzig.de.

  6. Improving the Annotation of Arabidopsis lyrata Using RNA-Seq Data

    PubMed Central

    Rawat, Vimal; Abdelsamad, Ahmed; Pietzenuk, Björn; Seymour, Danelle K.; Koenig, Daniel; Weigel, Detlef; Pecinka, Ales; Schneeberger, Korbinian

    2015-01-01

    Gene model annotations are important community resources that ensure comparability and reproducibility of analyses and are typically the first step for functional annotation of genomic regions. Without up-to-date genome annotations, genome sequences cannot be used to maximum advantage. It is therefore essential to regularly update gene annotations by integrating the latest information to guarantee that reference annotations can remain a common basis for various types of analyses. Here, we report an improvement of the Arabidopsis lyrata gene annotation using extensive RNA-seq data. This new annotation consists of 31,132 protein coding gene models in addition to 2,089 genes with high similarity to transposable elements. Overall, ~87% of the gene models are corroborated by evidence of expression and 2,235 of these models feature multiple transcripts. Our updated gene annotation corrects hundreds of incorrectly split or merged gene models in the original annotation, and as a result the identification of alternative splicing events and differential isoform usage are vastly improved. PMID:26382944

  7. ModBase, a database of annotated comparative protein structure models, and associated resources.

    PubMed

    Pieper, Ursula; Webb, Benjamin M; Barkan, David T; Schneidman-Duhovny, Dina; Schlessinger, Avner; Braberg, Hannes; Yang, Zheng; Meng, Elaine C; Pettersen, Eric F; Huang, Conrad C; Datta, Ruchira S; Sampathkumar, Parthasarathy; Madhusudhan, Mallur S; Sjölander, Kimmen; Ferrin, Thomas E; Burley, Stephen K; Sali, Andrej

    2011-01-01

    ModBase (http://salilab.org/modbase) is a database of annotated comparative protein structure models. The models are calculated by ModPipe, an automated modeling pipeline that relies primarily on Modeller for fold assignment, sequence-structure alignment, model building and model assessment (http://salilab.org/modeller/). ModBase currently contains 10,355,444 reliable models for domains in 2,421,920 unique protein sequences. ModBase allows users to update comparative models on demand, and request modeling of additional sequences through an interface to the ModWeb modeling server (http://salilab.org/modweb). ModBase models are available through the ModBase interface as well as the Protein Model Portal (http://www.proteinmodelportal.org/). Recently developed associated resources include the SALIGN server for multiple sequence and structure alignment (http://salilab.org/salign), the ModEval server for predicting the accuracy of protein structure models (http://salilab.org/modeval), the PCSS server for predicting which peptides bind to a given protein (http://salilab.org/pcss) and the FoXS server for calculating and fitting Small Angle X-ray Scattering profiles (http://salilab.org/foxs). PMID:21097780

  8. Clever generation of rich SPARQL queries from annotated relational schema: application to Semantic Web Service creation for biological databases

    PubMed Central

    2013-01-01

    Background In recent years, a large amount of “-omics” data have been produced. However, these data are stored in many different species-specific databases that are managed by different institutes and laboratories. Biologists often need to find and assemble data from disparate sources to perform certain analyses. Searching for these data and assembling them is a time-consuming task. The Semantic Web helps to facilitate interoperability across databases. A common approach involves the development of wrapper systems that map a relational database schema onto existing domain ontologies. However, few attempts have been made to automate the creation of such wrappers. Results We developed a framework, named BioSemantic, for the creation of Semantic Web Services that are applicable to relational biological databases. This framework makes use of both Semantic Web and Web Services technologies and can be divided into two main parts: (i) the generation and semi-automatic annotation of an RDF view; and (ii) the automatic generation of SPARQL queries and their integration into Semantic Web Services backbones. We have used our framework to integrate genomic data from different plant databases. Conclusions BioSemantic is a framework that was designed to speed integration of relational databases. We present how it can be used to speed the development of Semantic Web Services for existing relational biological databases. Currently, it creates and annotates RDF views that enable the automatic generation of SPARQL queries. Web Services are also created and deployed automatically, and the semantic annotations of our Web Services are added automatically using SAWSDL attributes. BioSemantic is downloadable at http://southgreen.cirad.fr/?q=content/Biosemantic. PMID:23586394

  9. Designing and Using Databases for School Improvement.

    ERIC Educational Resources Information Center

    Bernhardt, Victoria L.

    This guide is designed for school and district administrators and teachers who want to use data to improve their schools, for college and university instructors who teach school administrators, and for support personnel who teach graduate-level education courses. The guide explains how to define the scope of a needed database, how to ready the…

  10. Improving HIV proteome annotation: new features of BioAfrica HIV Proteomics Resource

    PubMed Central

    Druce, Megan; Hulo, Chantal; Masson, Patrick; Sommer, Paula; Xenarios, Ioannis; Le Mercier, Philippe; De Oliveira, Tulio

    2016-01-01

    The Human Immunodeficiency Virus (HIV) is one of the pathogens that cause the greatest global concern, with approximately 35 million people currently infected with HIV. Extensive HIV research has been performed, generating a large amount of HIV and host genomic data. However, no effective vaccine that protects the host from HIV infection is available and HIV is still spreading at an alarming rate, despite effective antiretroviral (ARV) treatment. In order to develop effective therapies, we need to expand our knowledge of the interaction between HIV and host proteins. In contrast to virus proteins, which often rapidly evolve drug resistance mutations, the host proteins are essentially invariant within all humans. Thus, if we can identify the host proteins needed for virus replication, such as those involved in transporting viral proteins to the cell surface, we have a chance of interrupting viral replication. There is no proteome resource that summarizes this interaction, making research on this subject a difficult enterprise. In order to fill this gap in knowledge, we curated a resource presents detailed annotation on the interaction between the HIV proteome and host proteins. Our resource was produced in collaboration with ViralZone and used manual curation techniques developed by UniProtKB/Swiss-Prot. Our new website also used previous annotations of the BioAfrica HIV-1 Proteome Resource, which has been accessed by approximately 10 000 unique users a year since its inception in 2005. The novel features include a dedicated new page for each HIV protein, a graphic display of its function and a section on its interaction with host proteins. Our new webpages also add information on the genomic location of each HIV protein and the position of ARV drug resistance mutations. Our improved BioAfrica HIV-1 Proteome Resource fills a gap in the current knowledge of biocuration. Database URL: http://www.bioafrica.net/proteomics/HIVproteome.html PMID:27087306

  11. Improving HIV proteome annotation: new features of BioAfrica HIV Proteomics Resource.

    PubMed

    Druce, Megan; Hulo, Chantal; Masson, Patrick; Sommer, Paula; Xenarios, Ioannis; Le Mercier, Philippe; De Oliveira, Tulio

    2016-01-01

    The Human Immunodeficiency Virus (HIV) is one of the pathogens that cause the greatest global concern, with approximately 35 million people currently infected with HIV. Extensive HIV research has been performed, generating a large amount of HIV and host genomic data. However, no effective vaccine that protects the host from HIV infection is available and HIV is still spreading at an alarming rate, despite effective antiretroviral (ARV) treatment. In order to develop effective therapies, we need to expand our knowledge of the interaction between HIV and host proteins. In contrast to virus proteins, which often rapidly evolve drug resistance mutations, the host proteins are essentially invariant within all humans. Thus, if we can identify the host proteins needed for virus replication, such as those involved in transporting viral proteins to the cell surface, we have a chance of interrupting viral replication. There is no proteome resource that summarizes this interaction, making research on this subject a difficult enterprise. In order to fill this gap in knowledge, we curated a resource presents detailed annotation on the interaction between the HIV proteome and host proteins. Our resource was produced in collaboration with ViralZone and used manual curation techniques developed by UniProtKB/Swiss-Prot. Our new website also used previous annotations of the BioAfrica HIV-1 Proteome Resource, which has been accessed by approximately 10 000 unique users a year since its inception in 2005. The novel features include a dedicated new page for each HIV protein, a graphic display of its function and a section on its interaction with host proteins. Our new webpages also add information on the genomic location of each HIV protein and the position of ARV drug resistance mutations. Our improved BioAfrica HIV-1 Proteome Resource fills a gap in the current knowledge of biocuration.Database URL:http://www.bioafrica.net/proteomics/HIVproteome.html. PMID:27087306

  12. The Disease Portals, disease-gene annotation and the RGD disease ontology at the Rat Genome Database.

    PubMed

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

    2016-01-01

    The Rat Genome Database (RGD;http://rgd.mcw.edu/) provides critical datasets and software tools to a diverse community of rat and non-rat researchers worldwide. To meet the needs of the many users whose research is disease oriented, RGD has created a series of Disease Portals and has prioritized its curation efforts on the datasets important to understanding the mechanisms of various diseases. Gene-disease relationships for three species, rat, human and mouse, are annotated to capture biomarkers, genetic associations, molecular mechanisms and therapeutic targets. To generate gene-disease annotations more effectively and in greater detail, RGD initially adopted the MEDIC disease vocabulary from the Comparative Toxicogenomics Database and adapted it for use by expanding this framework with the addition of over 1000 terms to create the RGD Disease Ontology (RDO). The RDO provides the foundation for, at present, 10 comprehensive disease area-related dataset and analysis platforms at RGD, the Disease Portals. Two major disease areas are the focus of data acquisition and curation efforts each year, leading to the release of the related Disease Portals. Collaborative efforts to realize a more robust disease ontology are underway. Database URL:http://rgd.mcw.edu.

  13. The Disease Portals, disease–gene annotation and the RGD disease ontology at the Rat Genome Database

    PubMed Central

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

    2016-01-01

    The Rat Genome Database (RGD; http://rgd.mcw.edu/) provides critical datasets and software tools to a diverse community of rat and non-rat researchers worldwide. To meet the needs of the many users whose research is disease oriented, RGD has created a series of Disease Portals and has prioritized its curation efforts on the datasets important to understanding the mechanisms of various diseases. Gene-disease relationships for three species, rat, human and mouse, are annotated to capture biomarkers, genetic associations, molecular mechanisms and therapeutic targets. To generate gene–disease annotations more effectively and in greater detail, RGD initially adopted the MEDIC disease vocabulary from the Comparative Toxicogenomics Database and adapted it for use by expanding this framework with the addition of over 1000 terms to create the RGD Disease Ontology (RDO). The RDO provides the foundation for, at present, 10 comprehensive disease area-related dataset and analysis platforms at RGD, the Disease Portals. Two major disease areas are the focus of data acquisition and curation efforts each year, leading to the release of the related Disease Portals. Collaborative efforts to realize a more robust disease ontology are underway. Database URL: http://rgd.mcw.edu PMID:27009807

  14. ASPicDB: a database of annotated transcript and protein variants generated by alternative splicing

    PubMed Central

    Martelli, Pier L.; D’Antonio, Mattia; Bonizzoni, Paola; Castrignanò, Tiziana; D’Erchia, Anna M.; D’Onorio De Meo, Paolo; Fariselli, Piero; Finelli, Michele; Licciulli, Flavio; Mangiulli, Marina; Mignone, Flavio; Pavesi, Giulio; Picardi, Ernesto; Rizzi, Raffaella; Rossi, Ivan; Valletti, Alessio; Zauli, Andrea; Zambelli, Federico; Casadio, Rita; Pesole, Graziano

    2011-01-01

    Alternative splicing is emerging as a major mechanism for the expansion of the transcriptome and proteome diversity, particularly in human and other vertebrates. However, the proportion of alternative transcripts and proteins actually endowed with functional activity is currently highly debated. We present here a new release of ASPicDB which now provides a unique annotation resource of human protein variants generated by alternative splicing. A total of 256 939 protein variants from 17 191 multi-exon genes have been extensively annotated through state of the art machine learning tools providing information of the protein type (globular and transmembrane), localization, presence of PFAM domains, signal peptides, GPI-anchor propeptides, transmembrane and coiled-coil segments. Furthermore, full-length variants can be now specifically selected based on the annotation of CAGE-tags and polyA signal and/or polyA sites, marking transcription initiation and termination sites, respectively. The retrieval can be carried out at gene, transcript, exon, protein or splice site level allowing the selection of data sets fulfilling one or more features settled by the user. The retrieval interface also enables the selection of protein variants showing specific differences in the annotated features. ASPicDB is available at http://www.caspur.it/ASPicDB/. PMID:21051348

  15. A computational platform to maintain and migrate manual functional annotations for BioCyc databases

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Model organism databases are an important resource for information on biological pathways and genomic data. Such databases represent the accumulation of biological data, some of which has been manually curated from literature. An essential feature of these databases is the continuing data integratio...

  16. Recent improvements to the SMART domain-based sequence annotation resource.

    PubMed

    Letunic, Ivica; Goodstadt, Leo; Dickens, Nicholas J; Doerks, Tobias; Schultz, Joerg; Mott, Richard; Ciccarelli, Francesca; Copley, Richard R; Ponting, Chris P; Bork, Peer

    2002-01-01

    SMART (Simple Modular Architecture Research Tool, http://smart.embl-heidelberg.de) is a web-based resource used for the annotation of protein domains and the analysis of domain architectures, with particular emphasis on mobile eukaryotic domains. Extensive annotation for each domain family is available, providing information relating to function, subcellular localization, phyletic distribution and tertiary structure. The January 2002 release has added more than 200 hand-curated domain models. This brings the total to over 600 domain families that are widely represented among nuclear, signalling and extracellular proteins. Annotation now includes links to the Online Mendelian Inheritance in Man (OMIM) database in cases where a human disease is associated with one or more mutations in a particular domain. We have implemented new analysis methods and updated others. New advanced queries provide direct access to the SMART relational database using SQL. This database now contains information on intrinsic sequence features such as transmembrane regions, coiled-coils, signal peptides and internal repeats. SMART output can now be easily included in users' documents. A SMART mirror has been created at http://smart.ox.ac.uk. PMID:11752305

  17. Citrus sinensis annotation project (CAP): a comprehensive database for sweet orange genome.

    PubMed

    Wang, Jia; Chen, Dijun; Lei, Yang; Chang, Ji-Wei; Hao, Bao-Hai; Xing, Feng; Li, Sen; Xu, Qiang; Deng, Xiu-Xin; Chen, Ling-Ling

    2014-01-01

    Citrus is one of the most important and widely grown fruit crop with global production ranking firstly among all the fruit crops in the world. Sweet orange accounts for more than half of the Citrus production both in fresh fruit and processed juice. We have sequenced the draft genome of a double-haploid sweet orange (C. sinensis cv. Valencia), and constructed the Citrus sinensis annotation project (CAP) to store and visualize the sequenced genomic and transcriptome data. CAP provides GBrowse-based organization of sweet orange genomic data, which integrates ab initio gene prediction, EST, RNA-seq and RNA-paired end tag (RNA-PET) evidence-based gene annotation. Furthermore, we provide a user-friendly web interface to show the predicted protein-protein interactions (PPIs) and metabolic pathways in sweet orange. CAP provides comprehensive information beneficial to the researchers of sweet orange and other woody plants, which is freely available at http://citrus.hzau.edu.cn/.

  18. Biological database of images and genomes: tools for community annotations linking image and genomic information.

    PubMed

    Oberlin, Andrew T; Jurkovic, Dominika A; Balish, Mitchell F; Friedberg, Iddo

    2013-01-01

    Genomic data and biomedical imaging data are undergoing exponential growth. However, our understanding of the phenotype-genotype connection linking the two types of data is lagging behind. While there are many types of software that enable the manipulation and analysis of image data and genomic data as separate entities, there is no framework established for linking the two. We present a generic set of software tools, BioDIG, that allows linking of image data to genomic data. BioDIG tools can be applied to a wide range of research problems that require linking images to genomes. BioDIG features the following: rapid construction of web-based workbenches, community-based annotation, user management and web services. By using BioDIG to create websites, researchers and curators can rapidly annotate a large number of images with genomic information. Here we present the BioDIG software tools that include an image module, a genome module and a user management module. We also introduce a BioDIG-based website, MyDIG, which is being used to annotate images of mycoplasmas. PMID:23550062

  19. Strategies for annotation and curation of translational databases: the eTUMOUR project

    PubMed Central

    Julià-Sapé, Margarida; Lurgi, Miguel; Mier, Mariola; Estanyol, Francesc; Rafael, Xavier; Candiota, Ana Paula; Barceló, Anna; García, Alina; Martínez-Bisbal, M. Carmen; Ferrer-Luna, Rubén; Moreno-Torres, Àngel; Celda, Bernardo; Arús, Carles

    2012-01-01

    The eTUMOUR (eT) multi-centre project gathered in vivo and ex vivo magnetic resonance (MR) data, as well as transcriptomic and clinical information from brain tumour patients, with the purpose of improving the diagnostic and prognostic evaluation of future patients. In order to carry this out, among other work, a database—the eTDB—was developed. In addition to complex permission rules and software and management quality control (QC), it was necessary to develop anonymization, processing and data visualization tools for the data uploaded. It was also necessary to develop sophisticated curation strategies that involved on one hand, dedicated fields for QC-generated meta-data and specialized queries and global permissions for senior curators and on the other, to establish a set of metrics to quantify its contents. The indispensable dataset (ID), completeness and pairedness indices were set. The database contains 1317 cases created as a result of the eT project and 304 from a previous project, INTERPRET. The number of cases fulfilling the ID was 656. Completeness and pairedness were heterogeneous, depending on the data type involved. PMID:23180768

  20. Comparative high-throughput transcriptome sequencing and development of SiESTa, the Silene EST annotation database

    PubMed Central

    2011-01-01

    Background The genus Silene is widely used as a model system for addressing ecological and evolutionary questions in plants, but advances in using the genus as a model system are impeded by the lack of available resources for studying its genome. Massively parallel sequencing cDNA has recently developed into an efficient method for characterizing the transcriptomes of non-model organisms, generating massive amounts of data that enable the study of multiple species in a comparative framework. The sequences generated provide an excellent resource for identifying expressed genes, characterizing functional variation and developing molecular markers, thereby laying the foundations for future studies on gene sequence and gene expression divergence. Here, we report the results of a comparative transcriptome sequencing study of eight individuals representing four Silene and one Dianthus species as outgroup. All sequences and annotations have been deposited in a newly developed and publicly available database called SiESTa, the Silene EST annotation database. Results A total of 1,041,122 EST reads were generated in two runs on a Roche GS-FLX 454 pyrosequencing platform. EST reads were analyzed separately for all eight individuals sequenced and were assembled into contigs using TGICL. These were annotated with results from BLASTX searches and Gene Ontology (GO) terms, and thousands of single-nucleotide polymorphisms (SNPs) were characterized. Unassembled reads were kept as singletons and together with the contigs contributed to the unigenes characterized in each individual. The high quality of unigenes is evidenced by the proportion (49%) that have significant hits in similarity searches with the A. thaliana proteome. The SiESTa database is accessible at http://www.siesta.ethz.ch. Conclusion The sequence collections established in the present study provide an important genomic resource for four Silene and one Dianthus species and will help to further develop Silene as a

  1. Improvement of whole-genome annotation of cereals through comparative analyses

    PubMed Central

    Zhu, Wei; Buell, C. Robin

    2007-01-01

    Rice is an important model species for the Poaceae and other monocotyledonous plants. With the availability of a near-complete, finished, and annotated rice genome, we performed genome level comparisons between rice and all plant species in which large genomic or transcriptomic data sets are available to determine the utility of cross-species sequence for structural and functional annotation of the rice genome. Through comparative analyses with four plant genome sequence data sets and transcript assemblies from 185 plant species, we were able to confirm and improve the structural annotation of the rice genome. Support for 38,109 (89.3%) of the total 42,653 nontransposable element-related genes in the rice genome in the form of a rice expressed sequence tag, full-length cDNA, or plant homolog from our comparative analyses could be found. Although the majority of the putative homologs were obtained from Poaceae species, putative homologs were identified in dicotyledonous angiosperms, gymnosperms, and other plants such as algae, moss, and fern. A set of rice genes (7669) lacking a putative homolog was identified which may be lineage-specific genes that evolved after speciation and have a role in species diversity. Improvements to the current rice gene structural annotation could be identified from our comparative alignments and we were able to identify 487 genes which were mostly likely missed in the current rice genome annotation and another 500 genes for structural annotation review. We were able to demonstrate the utility of cross-species comparative alignments in the identification of noncoding sequences and in confirmation of gene nesting in rice. PMID:17284677

  2. Improving Automated Annotation of Benthic Survey Images Using Wide-band Fluorescence

    PubMed Central

    Beijbom, Oscar; Treibitz, Tali; Kline, David I.; Eyal, Gal; Khen, Adi; Neal, Benjamin; Loya, Yossi; Mitchell, B. Greg; Kriegman, David

    2016-01-01

    Large-scale imaging techniques are used increasingly for ecological surveys. However, manual analysis can be prohibitively expensive, creating a bottleneck between collected images and desired data-products. This bottleneck is particularly severe for benthic surveys, where millions of images are obtained each year. Recent automated annotation methods may provide a solution, but reflectance images do not always contain sufficient information for adequate classification accuracy. In this work, the FluorIS, a low-cost modified consumer camera, was used to capture wide-band wide-field-of-view fluorescence images during a field deployment in Eilat, Israel. The fluorescence images were registered with standard reflectance images, and an automated annotation method based on convolutional neural networks was developed. Our results demonstrate a 22% reduction of classification error-rate when using both images types compared to only using reflectance images. The improvements were large, in particular, for coral reef genera Platygyra, Acropora and Millepora, where classification recall improved by 38%, 33%, and 41%, respectively. We conclude that convolutional neural networks can be used to combine reflectance and fluorescence imagery in order to significantly improve automated annotation accuracy and reduce the manual annotation bottleneck. PMID:27021133

  3. Improving Automated Annotation of Benthic Survey Images Using Wide-band Fluorescence

    NASA Astrophysics Data System (ADS)

    Beijbom, Oscar; Treibitz, Tali; Kline, David I.; Eyal, Gal; Khen, Adi; Neal, Benjamin; Loya, Yossi; Mitchell, B. Greg; Kriegman, David

    2016-03-01

    Large-scale imaging techniques are used increasingly for ecological surveys. However, manual analysis can be prohibitively expensive, creating a bottleneck between collected images and desired data-products. This bottleneck is particularly severe for benthic surveys, where millions of images are obtained each year. Recent automated annotation methods may provide a solution, but reflectance images do not always contain sufficient information for adequate classification accuracy. In this work, the FluorIS, a low-cost modified consumer camera, was used to capture wide-band wide-field-of-view fluorescence images during a field deployment in Eilat, Israel. The fluorescence images were registered with standard reflectance images, and an automated annotation method based on convolutional neural networks was developed. Our results demonstrate a 22% reduction of classification error-rate when using both images types compared to only using reflectance images. The improvements were large, in particular, for coral reef genera Platygyra, Acropora and Millepora, where classification recall improved by 38%, 33%, and 41%, respectively. We conclude that convolutional neural networks can be used to combine reflectance and fluorescence imagery in order to significantly improve automated annotation accuracy and reduce the manual annotation bottleneck.

  4. Improving Automated Annotation of Benthic Survey Images Using Wide-band Fluorescence.

    PubMed

    Beijbom, Oscar; Treibitz, Tali; Kline, David I; Eyal, Gal; Khen, Adi; Neal, Benjamin; Loya, Yossi; Mitchell, B Greg; Kriegman, David

    2016-01-01

    Large-scale imaging techniques are used increasingly for ecological surveys. However, manual analysis can be prohibitively expensive, creating a bottleneck between collected images and desired data-products. This bottleneck is particularly severe for benthic surveys, where millions of images are obtained each year. Recent automated annotation methods may provide a solution, but reflectance images do not always contain sufficient information for adequate classification accuracy. In this work, the FluorIS, a low-cost modified consumer camera, was used to capture wide-band wide-field-of-view fluorescence images during a field deployment in Eilat, Israel. The fluorescence images were registered with standard reflectance images, and an automated annotation method based on convolutional neural networks was developed. Our results demonstrate a 22% reduction of classification error-rate when using both images types compared to only using reflectance images. The improvements were large, in particular, for coral reef genera Platygyra, Acropora and Millepora, where classification recall improved by 38%, 33%, and 41%, respectively. We conclude that convolutional neural networks can be used to combine reflectance and fluorescence imagery in order to significantly improve automated annotation accuracy and reduce the manual annotation bottleneck.

  5. Polymorphism Identification and Improved Genome Annotation of Brassica rapa Through Deep RNA Sequencing

    PubMed Central

    Devisetty, Upendra Kumar; Covington, Michael F.; Tat, An V.; Lekkala, Saradadevi; Maloof, Julin N.

    2014-01-01

    The mapping and functional analysis of quantitative traits in Brassica rapa can be greatly improved with the availability of physically positioned, gene-based genetic markers and accurate genome annotation. In this study, deep transcriptome RNA sequencing (RNA-Seq) of Brassica rapa was undertaken with two objectives: SNP detection and improved transcriptome annotation. We performed SNP detection on two varieties that are parents of a mapping population to aid in development of a marker system for this population and subsequent development of high-resolution genetic map. An improved Brassica rapa transcriptome was constructed to detect novel transcripts and to improve the current genome annotation. This is useful for accurate mRNA abundance and detection of expression QTL (eQTLs) in mapping populations. Deep RNA-Seq of two Brassica rapa genotypes—R500 (var. trilocularis, Yellow Sarson) and IMB211 (a rapid cycling variety)—using eight different tissues (root, internode, leaf, petiole, apical meristem, floral meristem, silique, and seedling) grown across three different environments (growth chamber, greenhouse and field) and under two different treatments (simulated sun and simulated shade) generated 2.3 billion high-quality Illumina reads. A total of 330,995 SNPs were identified in transcribed regions between the two genotypes with an average frequency of one SNP in every 200 bases. The deep RNA-Seq reassembled Brassica rapa transcriptome identified 44,239 protein-coding genes. Compared with current gene models of B. rapa, we detected 3537 novel transcripts, 23,754 gene models had structural modifications, and 3655 annotated proteins changed. Gaps in the current genome assembly of B. rapa are highlighted by our identification of 780 unmapped transcripts. All the SNPs, annotations, and predicted transcripts can be viewed at http://phytonetworks.ucdavis.edu/. PMID:25122667

  6. Polymorphism identification and improved genome annotation of Brassica rapa through Deep RNA sequencing.

    PubMed

    Devisetty, Upendra Kumar; Covington, Michael F; Tat, An V; Lekkala, Saradadevi; Maloof, Julin N

    2014-08-12

    The mapping and functional analysis of quantitative traits in Brassica rapa can be greatly improved with the availability of physically positioned, gene-based genetic markers and accurate genome annotation. In this study, deep transcriptome RNA sequencing (RNA-Seq) of Brassica rapa was undertaken with two objectives: SNP detection and improved transcriptome annotation. We performed SNP detection on two varieties that are parents of a mapping population to aid in development of a marker system for this population and subsequent development of high-resolution genetic map. An improved Brassica rapa transcriptome was constructed to detect novel transcripts and to improve the current genome annotation. This is useful for accurate mRNA abundance and detection of expression QTL (eQTLs) in mapping populations. Deep RNA-Seq of two Brassica rapa genotypes-R500 (var. trilocularis, Yellow Sarson) and IMB211 (a rapid cycling variety)-using eight different tissues (root, internode, leaf, petiole, apical meristem, floral meristem, silique, and seedling) grown across three different environments (growth chamber, greenhouse and field) and under two different treatments (simulated sun and simulated shade) generated 2.3 billion high-quality Illumina reads. A total of 330,995 SNPs were identified in transcribed regions between the two genotypes with an average frequency of one SNP in every 200 bases. The deep RNA-Seq reassembled Brassica rapa transcriptome identified 44,239 protein-coding genes. Compared with current gene models of B. rapa, we detected 3537 novel transcripts, 23,754 gene models had structural modifications, and 3655 annotated proteins changed. Gaps in the current genome assembly of B. rapa are highlighted by our identification of 780 unmapped transcripts. All the SNPs, annotations, and predicted transcripts can be viewed at http://phytonetworks.ucdavis.edu/.

  7. T3DB: a comprehensively annotated database of common toxins and their targets.

    PubMed

    Lim, Emilia; Pon, Allison; Djoumbou, Yannick; Knox, Craig; Shrivastava, Savita; Guo, An Chi; Neveu, Vanessa; Wishart, David S

    2010-01-01

    In an effort to capture meaningful biological, chemical and mechanistic information about clinically relevant, commonly encountered or important toxins, we have developed the Toxin and Toxin-Target Database (T3DB). The T3DB is a unique bioinformatics resource that compiles comprehensive information about common or ubiquitous toxins and their toxin-targets into a single electronic repository. The database currently contains over 2900 small molecule and peptide toxins, 1300 toxin-targets and more than 33,000 toxin-target associations. Each T3DB record (ToxCard) contains over 80 data fields providing detailed information on chemical properties and descriptors, toxicity values, protein and gene sequences (for both targets and toxins), molecular and cellular interaction data, toxicological data, mechanistic information and references. This information has been manually extracted and manually verified from numerous sources, including other electronic databases, government documents, textbooks and scientific journals. A key focus of the T3DB is on providing 'depth' over 'breadth' with detailed descriptions, mechanisms of action, and information on toxins and toxin-targets. T3DB is fully searchable and supports extensive text, sequence, chemical structure and relational query searches, similar to those found in the Human Metabolome Database (HMDB) and DrugBank. Potential applications of the T3DB include clinical metabolomics, toxin target prediction, toxicity prediction and toxicology education. The T3DB is available online at http://www.t3db.org. PMID:19897546

  8. An annotated bibliography of selected guides for stream habitat improvement in the Pacific Northwest

    USGS Publications Warehouse

    Keim, R.F.; Price, A.B.; Hardin, T. S.; Skaugset, Arne E.; Bateman, D.S.; Gresswell, R.E.; Tesch, S. D.

    2004-01-01

    This annotated bibliography is a response to widespread interest in stream habitat improvement in the Pacific Northwest by land managers, governmental and nongovernmental organizations, and the lay public. Several guides to stream habitat improvement have been written in the past, but may not be easily accessible to people from diverse backgrounds. This annotated bibliography reviews 11 guides to stream habitat improvement so that readers can find literature appropriate to their needs. All reviews begin with summaries of the contents, stated audiences, and goals of each guide. Reviews also include subjective comments on the strengths and weaknesses of each guide. Finally, this bibliography includes recommendations of guides and combinations of guides judged most useful for a range of purposes. 

  9. The National Microbial Pathogen Database Resource (NMPDR): a genomics platform based on subsystem annotation.

    PubMed

    McNeil, Leslie Klis; Reich, Claudia; Aziz, Ramy K; Bartels, Daniela; Cohoon, Matthew; Disz, Terry; Edwards, Robert A; Gerdes, Svetlana; Hwang, Kaitlyn; Kubal, Michael; Margaryan, Gohar Rem; Meyer, Folker; Mihalo, William; Olsen, Gary J; Olson, Robert; Osterman, Andrei; Paarmann, Daniel; Paczian, Tobias; Parrello, Bruce; Pusch, Gordon D; Rodionov, Dmitry A; Shi, Xinghua; Vassieva, Olga; Vonstein, Veronika; Zagnitko, Olga; Xia, Fangfang; Zinner, Jenifer; Overbeek, Ross; Stevens, Rick

    2007-01-01

    The National Microbial Pathogen Data Resource (NMPDR) (http://www.nmpdr.org) is a National Institute of Allergy and Infections Disease (NIAID)-funded Bioinformatics Resource Center that supports research in selected Category B pathogens. NMPDR contains the complete genomes of approximately 50 strains of pathogenic bacteria that are the focus of our curators, as well as >400 other genomes that provide a broad context for comparative analysis across the three phylogenetic Domains. NMPDR integrates complete, public genomes with expertly curated biological subsystems to provide the most consistent genome annotations. Subsystems are sets of functional roles related by a biologically meaningful organizing principle, which are built over large collections of genomes; they provide researchers with consistent functional assignments in a biologically structured context. Investigators can browse subsystems and reactions to develop accurate reconstructions of the metabolic networks of any sequenced organism. NMPDR provides a comprehensive bioinformatics platform, with tools and viewers for genome analysis. Results of precomputed gene clustering analyses can be retrieved in tabular or graphic format with one-click tools. NMPDR tools include Signature Genes, which finds the set of genes in common or that differentiates two groups of organisms. Essentiality data collated from genome-wide studies have been curated. Drug target identification and high-throughput, in silico, compound screening are in development. PMID:17145713

  10. The National Microbial Pathogen Database Resource (NMPDR): a genomics platform based on subsystem annotation

    PubMed Central

    McNeil, Leslie Klis; Reich, Claudia; Aziz, Ramy K.; Bartels, Daniela; Cohoon, Matthew; Disz, Terry; Edwards, Robert A.; Gerdes, Svetlana; Hwang, Kaitlyn; Kubal, Michael; Margaryan, Gohar Rem; Meyer, Folker; Mihalo, William; Olsen, Gary J.; Olson, Robert; Osterman, Andrei; Paarmann, Daniel; Paczian, Tobias; Parrello, Bruce; Pusch, Gordon D.; Rodionov, Dmitry A.; Shi, Xinghua; Vassieva, Olga; Vonstein, Veronika; Zagnitko, Olga; Xia, Fangfang; Zinner, Jenifer; Overbeek, Ross; Stevens, Rick

    2007-01-01

    The National Microbial Pathogen Data Resource (NMPDR) () is a National Institute of Allergy and Infections Disease (NIAID)-funded Bioinformatics Resource Center that supports research in selected Category B pathogens. NMPDR contains the complete genomes of ∼50 strains of pathogenic bacteria that are the focus of our curators, as well as >400 other genomes that provide a broad context for comparative analysis across the three phylogenetic Domains. NMPDR integrates complete, public genomes with expertly curated biological subsystems to provide the most consistent genome annotations. Subsystems are sets of functional roles related by a biologically meaningful organizing principle, which are built over large collections of genomes; they provide researchers with consistent functional assignments in a biologically structured context. Investigators can browse subsystems and reactions to develop accurate reconstructions of the metabolic networks of any sequenced organism. NMPDR provides a comprehensive bioinformatics platform, with tools and viewers for genome analysis. Results of precomputed gene clustering analyses can be retrieved in tabular or graphic format with one-click tools. NMPDR tools include Signature Genes, which finds the set of genes in common or that differentiates two groups of organisms. Essentiality data collated from genome-wide studies have been curated. Drug target identification and high-throughput, in silico, compound screening are in development. PMID:17145713

  11. The CATH extended protein-family database: providing structural annotations for genome sequences.

    PubMed

    Pearl, Frances M G; Lee, David; Bray, James E; Buchan, Daniel W A; Shepherd, Adrian J; Orengo, Christine A

    2002-02-01

    An automatic sequence search and analysis protocol (DomainFinder) based on PSI-BLAST and IMPALA, and using conservative thresholds, has been developed for reliably integrating gene sequences from GenBank into their respective structural families within the CATH domain database (http://www.biochem.ucl.ac.uk/bsm/cath_new). DomainFinder assigns a new gene sequence to a CATH homologous superfamily provided that PSI-BLAST identifies a clear relationship to at least one other Protein Data Bank sequence within that superfamily. This has resulted in an expansion of the CATH protein family database (CATH-PFDB v1.6) from 19,563 domain structures to 176,597 domain sequences. A further 50,000 putative homologous relationships can be identified using less stringent cut-offs and these relationships are maintained within neighbour tables in the CATH Oracle database, pending further evidence of their suggested evolutionary relationship. Analysis of the CATH-PFDB has shown that only 15% of the sequence families are close enough to a known structure for reliable homology modeling. IMPALA/PSI-BLAST profiles have been generated for each of the sequence families in the expanded CATH-PFDB and a web server has been provided so that new sequences may be scanned against the profile library and be assigned to a structure and homologous superfamily.

  12. GELBANK : A database of annotated two-dimensional gel electrophoresis patterns of biological systems with completed genomes.

    SciTech Connect

    Babnigg, G.; Giometti, C. S.; Biosciences Division

    2004-01-01

    GELBANK is a publicly available database of two-dimensional gel electrophoresis (2DE) gel patterns of proteomes from organisms with known genome information (available at and ftp://bioinformatics.anl.gov/gelbank/). Currently it includes 131 completed, mostly microbial proteomes available from the National Center for Biotechnology Information. A web interface allows the upload of 2D gel patterns and their annotation for registered users. The images are organized by species, tissue type, separation method, sample type and staining method. The database can be queried based on protein or 2DE-pattern attributes. A web interface allows registered users to assign molecular weight and pH gradient profiles to their own 2D gel patterns as well as to link protein identifications to a given spot on the pattern. The website presents all of the submitted 2D gel patterns where the end-user can dynamically display the images or parts of images along with molecular weight, pH profile information and linked protein identification. A collection of images can be selected for the creation of animations from which the user can select sub-regions of interest and unlimited 2D gel patterns for visualization. The website currently presents 233 identifications for 81 gel patterns for Homo sapiens, Methanococcus jannaschii, Pyro coccus furiosus, Shewanella oneidensis, Escherichia coli and Deinococcus radiodurans.

  13. Enchytraeus albidus Microarray: Enrichment, Design, Annotation and Database (EnchyBASE)

    PubMed Central

    Novais, Sara C.; Arrais, Joel; Lopes, Pedro; Vandenbrouck, Tine; De Coen, Wim; Roelofs, Dick; Soares, Amadeu M. V. M.; Amorim, Mónica J. B.

    2012-01-01

    Enchytraeus albidus (Oligochaeta) is an ecologically relevant species used as standard test organisms for risk assessment. Effects of stressors in this species are commonly determined at the population level using reproduction and survival as endpoints. The assessment of transcriptomic responses can be very useful e.g. to understand underlying mechanisms of toxicity with gene expression fingerprinting. In the present paper the following is being addressed: 1) development of suppressive subtractive hybridization (SSH) libraries enriched for differentially expressed genes after metal and pesticide exposures; 2) sequencing and characterization of all generated cDNA inserts; 3) development of a publicly available genomic database on E. albidus. A total of 2100 Expressed Sequence Tags (ESTs) were isolated, sequenced and assembled into 1124 clusters (947 singletons and 177 contigs). From these sequences, 41% matched known proteins in GenBank (BLASTX, e-value≤10-5) and 37% had at least one Gene Ontology (GO) term assigned. In total, 5.5% of the sequences were assigned to a metabolic pathway, based on KEGG. With this new sequencing information, an Agilent custom oligonucleotide microarray was designed, representing a potential tool for transcriptomic studies. EnchyBASE (http://bioinformatics.ua.pt/enchybase/) was developed as a web freely available database containing genomic information on E. albidus and will be further extended in the near future for other enchytraeid species. The database so far includes all ESTs generated for E. albidus from three cDNA libraries. This information can be downloaded and applied in functional genomics and transcription studies. PMID:22558086

  14. VibrioBase: a model for next-generation genome and annotation database development.

    PubMed

    Choo, Siew Woh; Heydari, Hamed; Tan, Tze King; Siow, Cheuk Chuen; Beh, Ching Yew; Wee, Wei Yee; Mutha, Naresh V R; Wong, Guat Jah; Ang, Mia Yang; Yazdi, Amir Hessam

    2014-01-01

    To facilitate the ongoing research of Vibrio spp., a dedicated platform for the Vibrio research community is needed to host the fast-growing amount of genomic data and facilitate the analysis of these data. We present VibrioBase, a useful resource platform, providing all basic features of a sequence database with the addition of unique analysis tools which could be valuable for the Vibrio research community. VibrioBase currently houses a total of 252 Vibrio genomes developed in a user-friendly manner and useful to enable the analysis of these genomic data, particularly in the field of comparative genomics. Besides general data browsing features, VibrioBase offers analysis tools such as BLAST interfaces and JBrowse genome browser. Other important features of this platform include our newly developed in-house tools, the pairwise genome comparison (PGC) tool, and pathogenomics profiling tool (PathoProT). The PGC tool is useful in the identification and comparative analysis of two genomes, whereas PathoProT is designed for comparative pathogenomics analysis of Vibrio strains. Both of these tools will enable researchers with little experience in bioinformatics to get meaningful information from Vibrio genomes with ease. We have tested the validity and suitability of these tools and features for use in the next-generation database development.

  15. CrAgDb--a database of annotated chaperone repertoire in archaeal genomes.

    PubMed

    Rani, Shikha; Srivastava, Abhishikha; Kumar, Manish; Goel, Manisha

    2016-03-01

    Chaperones are a diverse class of ubiquitous proteins that assist other cellular proteins in folding correctly and maintaining their native structure. Many different chaperones cooperate to constitute the 'proteostasis' machinery in the cells. It has been proposed earlier that archaeal organisms could be ideal model systems for deciphering the basic functioning of the 'protein folding machinery' in higher eukaryotes. Several chaperone families have been characterized in archaea over the years but mostly one protein at a time, making it difficult to decipher the composition and mechanistics of the protein folding system as a whole. In order to deal with these lacunae, we have developed a database of all archaeal chaperone proteins, CrAgDb (Chaperone repertoire in Archaeal genomes). The data have been presented in a systematic way with intuitive browse and search facilities for easy retrieval of information. Access to these curated datasets should expedite large-scale analysis of archaeal chaperone networks and significantly advance our understanding of operation and regulation of the protein folding machinery in archaea. Researchers could then translate this knowledge to comprehend the more complex protein folding pathways in eukaryotic systems. The database is freely available at http://14.139.227.92/mkumar/cragdb/. PMID:26862144

  16. Method for the Compound Annotation of Conjugates in Nontargeted Metabolomics Using Accurate Mass Spectrometry, Multistage Product Ion Spectra and Compound Database Searching.

    PubMed

    Ogura, Tairo; Bamba, Takeshi; Tai, Akihiro; Fukusaki, Eiichiro

    2015-01-01

    Owing to biotransformation, xenobiotics are often found in conjugated form in biological samples such as urine and plasma. Liquid chromatography coupled with accurate mass spectrometry with multistage collision-induced dissociation provides spectral information concerning these metabolites in complex materials. Unfortunately, compound databases typically do not contain a sufficient number of records for such conjugates. We report here on the development of a novel protocol, referred to as ChemProphet, to annotate compounds, including conjugates, using compound databases such as PubChem and ChemSpider. The annotation of conjugates involves three steps: 1. Recognition of the type and number of conjugates in the sample; 2. Compound search and annotation of the deconjugated form; and 3. In silico evaluation of the candidate conjugate. ChemProphet assigns a spectrum to each candidate by automatically exploring the substructures corresponding to the observed product ion spectrum. When finished, it annotates the candidates assigning a rank for each candidate based on the calculated score that ranks its relative likelihood. We assessed our protocol by annotating a benchmark dataset by including the product ion spectra for 102 compounds, annotating the commercially available standard for quercetin 3-glucuronide, and by conducting a model experiment using urine from mice that had been administered a green tea extract. The results show that by using the ChemProphet approach, it is possible to annotate not only the deconjugated molecules but also the conjugated molecules using an automatic interpretation method based on deconjugation that involves multistage collision-induced dissociation and in silico calculated conjugation.

  17. Involving Undergraduates in the Annotation and Analysis of Global Gene Expression Studies: Creation of a Maize Shoot Apical Meristem Expression Database

    PubMed Central

    Buckner, Brent; Beck, Jon; Browning, Kate; Fritz, Ashleigh; Grantham, Lisa; Hoxha, Eneda; Kamvar, Zhian; Lough, Ashley; Nikolova, Olga; Schnable, Patrick S.; Scanlon, Michael J.; Janick-Buckner, Diane

    2007-01-01

    Through a multi-university and interdisciplinary project we have involved undergraduate biology and computer science research students in the functional annotation of maize genes and the analysis of their microarray expression patterns. We have created a database to house the results of our functional annotation of >4400 genes identified as being differentially regulated in the maize shoot apical meristem (SAM). This database is located at http://sam.truman.edu and is now available for public use. The undergraduate students involved in constructing this unique SAM database received hands-on training in an intellectually challenging environment, which has prepared them for graduate and professional careers in biological sciences. We describe our experiences with this project as a model for effective research-based teaching of undergraduate biology and computer science students, as well as for a rich professional development experience for faculty at predominantly undergraduate institutions. PMID:17409087

  18. The Genome Sequence DataBase (GSDB): improving data quality and data access.

    PubMed Central

    Harger, C; Skupski, M; Bingham, J; Farmer, A; Hoisie, S; Hraber, P; Kiphart, D; Krakowski, L; McLeod, M; Schwertfeger, J; Seluja, G; Siepel, A; Singh, G; Stamper, D; Steadman, P; Thayer, N; Thompson, R; Wargo, P; Waugh, M; Zhuang, J J; Schad, P A

    1998-01-01

    In 1997 the primary focus of the Genome Sequence DataBase (GSDB; www. ncgr.org/gsdb ) located at the National Center for Genome Resources was to improve data quality and accessibility. Efforts to increase the quality of data within the database included two major projects; one to identify and remove all vector contamination from sequences in the database and one to create premier sequence sets (including both alignments and discontiguous sequences). Data accessibility was improved during the course of the last year in several ways. First, a graphical database sequence viewer was made available to researchers. Second, an update process was implemented for the web-based query tool, Maestro. Third, a web-based tool, Excerpt, was developed to retrieve selected regions of any sequence in the database. And lastly, a GSDB flatfile that contains annotation unique to GSDB (e.g., sequence analysis and alignment data) was developed. Additionally, the GSDB web site provides a tool for the detection of matrix attachment regions (MARs), which can be used to identify regions of high coding potential. The ultimate goal of this work is to make GSDB a more useful resource for genomic comparison studies and gene level studies by improving data quality and by providing data access capabilities that are consistent with the needs of both types of studies. PMID:9399793

  19. Integration of RNA-seq and proteomics data with genomics for improved genome annotation in Apicomplexan parasites.

    PubMed

    Silmon de Monerri, Natalie C; Weiss, Louis M

    2015-08-01

    While high quality genomic sequence data is available for many pathogenic organisms, the corresponding gene annotations are often plagued with inaccuracies that can hinder research that utilizes such genomic data. Experimental validation of gene models is clearly crucial in improving such gene annotations; the field of proteogenomics is an emerging area of research wherein proteomic data is applied to testing and improving genetic models. Krishna et al. [Proteomics 2015, 15, 2618-2628] investigated whether incorporation of RNA-seq data into proteogenomics analyses can contribute significantly to validation studies of genome annotation, in two important parasitic organisms Toxoplasma gondii and Neospora caninum. They applied a systematic approach to combine new and previously published proteomics data from T. gondii and N. caninum with transcriptomics data, leading to substantially improved gene models for these organisms. This study illustrates the importance of incorporating experimental data from both proteomics and RNA-seq studies into routine genome annotation protocols.

  20. EnzDP: improved enzyme annotation for metabolic network reconstruction based on domain composition profiles.

    PubMed

    Nguyen, Nam-Ninh; Srihari, Sriganesh; Leong, Hon Wai; Chong, Ket-Fah

    2015-10-01

    Determining the entire complement of enzymes and their enzymatic functions is a fundamental step for reconstructing the metabolic network of cells. High quality enzyme annotation helps in enhancing metabolic networks reconstructed from the genome, especially by reducing gaps and increasing the enzyme coverage. Currently, structure-based and network-based approaches can only cover a limited number of enzyme families, and the accuracy of homology-based approaches can be further improved. Bottom-up homology-based approach improves the coverage by rebuilding Hidden Markov Model (HMM) profiles for all known enzymes. However, its clustering procedure relies firmly on BLAST similarity score, ignoring protein domains/patterns, and is sensitive to changes in cut-off thresholds. Here, we use functional domain architecture to score the association between domain families and enzyme families (Domain-Enzyme Association Scoring, DEAS). The DEAS score is used to calculate the similarity between proteins, which is then used in clustering procedure, instead of using sequence similarity score. We improve the enzyme annotation protocol using a stringent classification procedure, and by choosing optimal threshold settings and checking for active sites. Our analysis shows that our stringent protocol EnzDP can cover up to 90% of enzyme families available in Swiss-Prot. It achieves a high accuracy of 94.5% based on five-fold cross-validation. EnzDP outperforms existing methods across several testing scenarios. Thus, EnzDP serves as a reliable automated tool for enzyme annotation and metabolic network reconstruction. Available at: www.comp.nus.edu.sg/~nguyennn/EnzDP . PMID:26542446

  1. EnzDP: improved enzyme annotation for metabolic network reconstruction based on domain composition profiles.

    PubMed

    Nguyen, Nam-Ninh; Srihari, Sriganesh; Leong, Hon Wai; Chong, Ket-Fah

    2015-10-01

    Determining the entire complement of enzymes and their enzymatic functions is a fundamental step for reconstructing the metabolic network of cells. High quality enzyme annotation helps in enhancing metabolic networks reconstructed from the genome, especially by reducing gaps and increasing the enzyme coverage. Currently, structure-based and network-based approaches can only cover a limited number of enzyme families, and the accuracy of homology-based approaches can be further improved. Bottom-up homology-based approach improves the coverage by rebuilding Hidden Markov Model (HMM) profiles for all known enzymes. However, its clustering procedure relies firmly on BLAST similarity score, ignoring protein domains/patterns, and is sensitive to changes in cut-off thresholds. Here, we use functional domain architecture to score the association between domain families and enzyme families (Domain-Enzyme Association Scoring, DEAS). The DEAS score is used to calculate the similarity between proteins, which is then used in clustering procedure, instead of using sequence similarity score. We improve the enzyme annotation protocol using a stringent classification procedure, and by choosing optimal threshold settings and checking for active sites. Our analysis shows that our stringent protocol EnzDP can cover up to 90% of enzyme families available in Swiss-Prot. It achieves a high accuracy of 94.5% based on five-fold cross-validation. EnzDP outperforms existing methods across several testing scenarios. Thus, EnzDP serves as a reliable automated tool for enzyme annotation and metabolic network reconstruction. Available at: www.comp.nus.edu.sg/~nguyennn/EnzDP .

  2. PlantTFDB 2.0: update and improvement of the comprehensive plant transcription factor database.

    PubMed

    Zhang, He; Jin, Jinpu; Tang, Liang; Zhao, Yi; Gu, Xiaocheng; Gao, Ge; Luo, Jingchu

    2011-01-01

    We updated the plant transcription factor (TF) database to version 2.0 (PlantTFDB 2.0, http://planttfdb.cbi.pku.edu.cn) which contains 53,319 putative TFs predicted from 49 species. We made detailed annotation including general information, domain feature, gene ontology, expression pattern and ortholog groups, as well as cross references to various databases and literature citations for these TFs classified into 58 newly defined families with computational approach and manual inspection. Multiple sequence alignments and phylogenetic trees for each family can be shown as Weblogo pictures or downloaded as text files. We have redesigned the user interface in the new version. Users can search TFs with much more flexibility through the improved advanced search page, and the search results can be exported into various formats for further analysis. In addition, we now provide web service for advanced users to access PlantTFDB 2.0 more efficiently.

  3. Strategies to improve usability and preserve accuracy in biological sequence databases.

    PubMed

    Bengtsson-Palme, Johan; Boulund, Fredrik; Edström, Robert; Feizi, Amir; Johnning, Anna; Jonsson, Viktor A; Karlsson, Fredrik H; Pal, Chandan; Pereira, Mariana Buongermino; Rehammar, Anna; Sanchez, José; Sanli, Kemal; Thorell, Kaisa

    2016-09-01

    Biology is increasingly dependent on large-scale analysis, such as proteomics, creating a requirement for efficient bioinformatics. Bioinformatic predictions of biological functions rely upon correctly annotated database sequences, and the presence of inaccurately annotated or otherwise poorly described sequences introduces noise and bias to biological analyses. Accurate annotations are, for example, pivotal for correct identification of polypeptide fragments. However, standards for how sequence databases are organized and presented are currently insufficient. Here, we propose five strategies to address fundamental issues in the annotation of sequence databases: (i) to clearly separate experimentally verified and unverified sequence entries; (ii) to enable a system for tracing the origins of annotations; (iii) to separate entries with high-quality, informative annotation from less useful ones; (iv) to integrate automated quality-control software whenever such tools exist; and (v) to facilitate postsubmission editing of annotations and metadata associated with sequences. We believe that implementation of these strategies, for example as requirements for publication of database papers, would enable biology to better take advantage of large-scale data. PMID:27528420

  4. MobiDB 2.0: an improved database of intrinsically disordered and mobile proteins

    PubMed Central

    Potenza, Emilio; Domenico, Tomás Di; Walsh, Ian; Tosatto, Silvio C.E.

    2015-01-01

    MobiDB (http://mobidb.bio.unipd.it/) is a database of intrinsically disordered and mobile proteins. Intrinsically disordered regions are key for the function of numerous proteins. Here we provide a new version of MobiDB, a centralized source aimed at providing the most complete picture on different flavors of disorder in protein structures covering all UniProt sequences (currently over 80 million). The database features three levels of annotation: manually curated, indirect and predicted. Manually curated data is extracted from the DisProt database. Indirect data is inferred from PDB structures that are considered an indication of intrinsic disorder. The 10 predictors currently included (three ESpritz flavors, two IUPred flavors, two DisEMBL flavors, GlobPlot, VSL2b and JRONN) enable MobiDB to provide disorder annotations for every protein in absence of more reliable data. The new version also features a consensus annotation and classification for long disordered regions. In order to complement the disorder annotations, MobiDB features additional annotations from external sources. Annotations from the UniProt database include post-translational modifications and linear motifs. Pfam annotations are displayed in graphical form and are link-enabled, allowing the user to visit the corresponding Pfam page for further information. Experimental protein–protein interactions from STRING are also classified for disorder content. PMID:25361972

  5. KEGG orthology-based annotation of the predicted proteome of Acropora digitifera: ZoophyteBase - an open access and searchable database of a coral genome

    PubMed Central

    2013-01-01

    Background Contemporary coral reef research has firmly established that a genomic approach is urgently needed to better understand the effects of anthropogenic environmental stress and global climate change on coral holobiont interactions. Here we present KEGG orthology-based annotation of the complete genome sequence of the scleractinian coral Acropora digitifera and provide the first comprehensive view of the genome of a reef-building coral by applying advanced bioinformatics. Description Sequences from the KEGG database of protein function were used to construct hidden Markov models. These models were used to search the predicted proteome of A. digitifera to establish complete genomic annotation. The annotated dataset is published in ZoophyteBase, an open access format with different options for searching the data. A particularly useful feature is the ability to use a Google-like search engine that links query words to protein attributes. We present features of the annotation that underpin the molecular structure of key processes of coral physiology that include (1) regulatory proteins of symbiosis, (2) planula and early developmental proteins, (3) neural messengers, receptors and sensory proteins, (4) calcification and Ca2+-signalling proteins, (5) plant-derived proteins, (6) proteins of nitrogen metabolism, (7) DNA repair proteins, (8) stress response proteins, (9) antioxidant and redox-protective proteins, (10) proteins of cellular apoptosis, (11) microbial symbioses and pathogenicity proteins, (12) proteins of viral pathogenicity, (13) toxins and venom, (14) proteins of the chemical defensome and (15) coral epigenetics. Conclusions We advocate that providing annotation in an open-access searchable database available to the public domain will give an unprecedented foundation to interrogate the fundamental molecular structure and interactions of coral symbiosis and allow critical questions to be addressed at the genomic level based on combined aspects of

  6. NDER: A novel web application using annotated whole slide images for rapid improvements in human pattern recognition

    PubMed Central

    Reder, Nicholas P.; Glasser, Daniel; Dintzis, Suzanne M.; Rendi, Mara H.; Garcia, Rochelle L.; Henriksen, Jonathan C.; Kilgore, Mark R.

    2016-01-01

    Context: Whole-slide images (WSIs) present a rich source of information for education, training, and quality assurance. However, they are often used in a fashion similar to glass slides rather than in novel ways that leverage the advantages of WSI. We have created a pipeline to transform annotated WSI into pattern recognition training, and quality assurance web application called novel diagnostic electronic resource (NDER). Aims: Create an efficient workflow for extracting annotated WSI for use by NDER, an attractive web application that provides high-throughput training. Materials and Methods: WSI were annotated by a resident and classified into five categories. Two methods of extracting images and creating image databases were compared. Extraction Method 1: Manual extraction of still images and validation of each image by four breast pathologists. Extraction Method 2: Validation of annotated regions on the WSI by a single experienced breast pathologist and automated extraction of still images tagged by diagnosis. The extracted still images were used by NDER. NDER briefly displays an image, requires users to classify the image after time has expired, then gives users immediate feedback. Results: The NDER workflow is efficient: annotation of a WSI requires 5 min and validation by an expert pathologist requires An additional one to 2 min. The pipeline is highly automated, with only annotation and validation requiring human input. NDER effectively displays hundreds of high-quality, high-resolution images and provides immediate feedback to users during a 30 min session. Conclusions: NDER efficiently uses annotated WSI to rapidly increase pattern recognition and evaluate for diagnostic proficiency. PMID:27563490

  7. SigmoID: a user-friendly tool for improving bacterial genome annotation through analysis of transcription control signals

    PubMed Central

    Damienikan, Aliaksandr U.

    2016-01-01

    The majority of bacterial genome annotations are currently automated and based on a ‘gene by gene’ approach. Regulatory signals and operon structures are rarely taken into account which often results in incomplete and even incorrect gene function assignments. Here we present SigmoID, a cross-platform (OS X, Linux and Windows) open-source application aiming at simplifying the identification of transcription regulatory sites (promoters, transcription factor binding sites and terminators) in bacterial genomes and providing assistance in correcting annotations in accordance with regulatory information. SigmoID combines a user-friendly graphical interface to well known command line tools with a genome browser for visualising regulatory elements in genomic context. Integrated access to online databases with regulatory information (RegPrecise and RegulonDB) and web-based search engines speeds up genome analysis and simplifies correction of genome annotation. We demonstrate some features of SigmoID by constructing a series of regulatory protein binding site profiles for two groups of bacteria: Soft Rot Enterobacteriaceae (Pectobacterium and Dickeya spp.) and Pseudomonas spp. Furthermore, we inferred over 900 transcription factor binding sites and alternative sigma factor promoters in the annotated genome of Pectobacterium atrosepticum. These regulatory signals control putative transcription units covering about 40% of the P. atrosepticum chromosome. Reviewing the annotation in cases where it didn’t fit with regulatory information allowed us to correct product and gene names for over 300 loci. PMID:27257541

  8. SigmoID: a user-friendly tool for improving bacterial genome annotation through analysis of transcription control signals.

    PubMed

    Nikolaichik, Yevgeny; Damienikan, Aliaksandr U

    2016-01-01

    The majority of bacterial genome annotations are currently automated and based on a 'gene by gene' approach. Regulatory signals and operon structures are rarely taken into account which often results in incomplete and even incorrect gene function assignments. Here we present SigmoID, a cross-platform (OS X, Linux and Windows) open-source application aiming at simplifying the identification of transcription regulatory sites (promoters, transcription factor binding sites and terminators) in bacterial genomes and providing assistance in correcting annotations in accordance with regulatory information. SigmoID combines a user-friendly graphical interface to well known command line tools with a genome browser for visualising regulatory elements in genomic context. Integrated access to online databases with regulatory information (RegPrecise and RegulonDB) and web-based search engines speeds up genome analysis and simplifies correction of genome annotation. We demonstrate some features of SigmoID by constructing a series of regulatory protein binding site profiles for two groups of bacteria: Soft Rot Enterobacteriaceae (Pectobacterium and Dickeya spp.) and Pseudomonas spp. Furthermore, we inferred over 900 transcription factor binding sites and alternative sigma factor promoters in the annotated genome of Pectobacterium atrosepticum. These regulatory signals control putative transcription units covering about 40% of the P. atrosepticum chromosome. Reviewing the annotation in cases where it didn't fit with regulatory information allowed us to correct product and gene names for over 300 loci.

  9. SigmoID: a user-friendly tool for improving bacterial genome annotation through analysis of transcription control signals.

    PubMed

    Nikolaichik, Yevgeny; Damienikan, Aliaksandr U

    2016-01-01

    The majority of bacterial genome annotations are currently automated and based on a 'gene by gene' approach. Regulatory signals and operon structures are rarely taken into account which often results in incomplete and even incorrect gene function assignments. Here we present SigmoID, a cross-platform (OS X, Linux and Windows) open-source application aiming at simplifying the identification of transcription regulatory sites (promoters, transcription factor binding sites and terminators) in bacterial genomes and providing assistance in correcting annotations in accordance with regulatory information. SigmoID combines a user-friendly graphical interface to well known command line tools with a genome browser for visualising regulatory elements in genomic context. Integrated access to online databases with regulatory information (RegPrecise and RegulonDB) and web-based search engines speeds up genome analysis and simplifies correction of genome annotation. We demonstrate some features of SigmoID by constructing a series of regulatory protein binding site profiles for two groups of bacteria: Soft Rot Enterobacteriaceae (Pectobacterium and Dickeya spp.) and Pseudomonas spp. Furthermore, we inferred over 900 transcription factor binding sites and alternative sigma factor promoters in the annotated genome of Pectobacterium atrosepticum. These regulatory signals control putative transcription units covering about 40% of the P. atrosepticum chromosome. Reviewing the annotation in cases where it didn't fit with regulatory information allowed us to correct product and gene names for over 300 loci. PMID:27257541

  10. The new modern era of yeast genomics: community sequencing and the resulting annotation of multiple Saccharomyces cerevisiae strains at the Saccharomyces Genome Database

    PubMed Central

    Engel, Stacia R.; Cherry, J. Michael

    2013-01-01

    The first completed eukaryotic genome sequence was that of the yeast Saccharomyces cerevisiae, and the Saccharomyces Genome Database (SGD; http://www.yeastgenome.org/) is the original model organism database. SGD remains the authoritative community resource for the S. cerevisiae reference genome sequence and its annotation, and continues to provide comprehensive biological information correlated with S. cerevisiae genes and their products. A diverse set of yeast strains have been sequenced to explore commercial and laboratory applications, and a brief history of those strains is provided. The publication of these new genomes has motivated the creation of new tools, and SGD will annotate and provide comparative analyses of these sequences, correlating changes with variations in strain phenotypes and protein function. We are entering a new era at SGD, as we incorporate these new sequences and make them accessible to the scientific community, all in an effort to continue in our mission of educating researchers and facilitating discovery. Database URL: http://www.yeastgenome.org/ PMID:23487186

  11. dbNSFP v3.0: A One-Stop Database of Functional Predictions and Annotations for Human Nonsynonymous and Splice-Site SNVs.

    PubMed

    Liu, Xiaoming; Wu, Chunlei; Li, Chang; Boerwinkle, Eric

    2016-03-01

    The purpose of the dbNSFP is to provide a one-stop resource for functional predictions and annotations for human nonsynonymous single-nucleotide variants (nsSNVs) and splice-site variants (ssSNVs), and to facilitate the steps of filtering and prioritizing SNVs from a large list of SNVs discovered in an exome-sequencing study. A list of all potential nsSNVs and ssSNVs based on the human reference sequence were created and functional predictions and annotations were curated and compiled for each SNV. Here, we report a recent major update of the database to version 3.0. The SNV list has been rebuilt based on GENCODE 22 and currently the database includes 82,832,027 nsSNVs and ssSNVs. An attached database dbscSNV, which compiled all potential human SNVs within splicing consensus regions and their deleteriousness predictions, add another 15,030,459 potentially functional SNVs. Eleven prediction scores (MetaSVM, MetaLR, CADD, VEST3, PROVEAN, 4× fitCons, fathmm-MKL, and DANN) and allele frequencies from the UK10K cohorts and the Exome Aggregation Consortium (ExAC), among others, have been added. The original seven prediction scores in v2.0 (SIFT, 2× Polyphen2, LRT, MutationTaster, MutationAssessor, and FATHMM) as well as many SNV and gene functional annotations have been updated. dbNSFP v3.0 is freely available at http://sites.google.com/site/jpopgen/dbNSFP. PMID:26555599

  12. dbNSFP v3.0: A One-Stop Database of Functional Predictions and Annotations for Human Nonsynonymous and Splice-Site SNVs.

    PubMed

    Liu, Xiaoming; Wu, Chunlei; Li, Chang; Boerwinkle, Eric

    2016-03-01

    The purpose of the dbNSFP is to provide a one-stop resource for functional predictions and annotations for human nonsynonymous single-nucleotide variants (nsSNVs) and splice-site variants (ssSNVs), and to facilitate the steps of filtering and prioritizing SNVs from a large list of SNVs discovered in an exome-sequencing study. A list of all potential nsSNVs and ssSNVs based on the human reference sequence were created and functional predictions and annotations were curated and compiled for each SNV. Here, we report a recent major update of the database to version 3.0. The SNV list has been rebuilt based on GENCODE 22 and currently the database includes 82,832,027 nsSNVs and ssSNVs. An attached database dbscSNV, which compiled all potential human SNVs within splicing consensus regions and their deleteriousness predictions, add another 15,030,459 potentially functional SNVs. Eleven prediction scores (MetaSVM, MetaLR, CADD, VEST3, PROVEAN, 4× fitCons, fathmm-MKL, and DANN) and allele frequencies from the UK10K cohorts and the Exome Aggregation Consortium (ExAC), among others, have been added. The original seven prediction scores in v2.0 (SIFT, 2× Polyphen2, LRT, MutationTaster, MutationAssessor, and FATHMM) as well as many SNV and gene functional annotations have been updated. dbNSFP v3.0 is freely available at http://sites.google.com/site/jpopgen/dbNSFP.

  13. Improving Functional Annotation in the DRE-TIM Metallolyase Superfamily through Identification of Active Site Fingerprints.

    PubMed

    Kumar, Garima; Johnson, Jordyn L; Frantom, Patrick A

    2016-03-29

    Within the DRE-TIM metallolyase superfamily, members of the Claisen-like condensation (CC-like) subgroup catalyze C-C bond-forming reactions between various α-ketoacids and acetyl-coenzyme A. These reactions are important in the metabolic pathways of many bacterial pathogens and serve as engineering scaffolds for the production of long-chain alcohol biofuels. To improve functional annotation and identify sequences that might use novel substrates in the CC-like subgroup, a combination of structural modeling and multiple-sequence alignments identified active site residues on the third, fourth, and fifth β-strands of the TIM-barrel catalytic domain that are differentially conserved within the substrate-diverse enzyme families. Using α-isopropylmalate synthase and citramalate synthase from Methanococcus jannaschii (MjIPMS and MjCMS), site-directed mutagenesis was used to test the role of each identified position in substrate selectivity. Kinetic data suggest that residues at the β3-5 and β4-7 positions play a significant role in the selection of α-ketoisovalerate over pyruvate in MjIPMS. However, complementary substitutions in MjCMS fail to alter substrate specificity, suggesting residues in these positions do not contribute to substrate selectivity in this enzyme. Analysis of the kinetic data with respect to a protein similarity network for the CC-like subgroup suggests that evolutionarily distinct forms of IPMS utilize residues at the β3-5 and β4-7 positions to affect substrate selectivity while the different versions of CMS use unique architectures. Importantly, mapping the identities of residues at the β3-5 and β4-7 positions onto the protein similarity network allows for rapid annotation of probable IPMS enzymes as well as several outlier sequences that may represent novel functions in the subgroup. PMID:26935545

  14. Improving GENCODE reference gene annotation using a high-stringency proteogenomics workflow

    PubMed Central

    Wright, James C.; Mudge, Jonathan; Weisser, Hendrik; Barzine, Mitra P.; Gonzalez, Jose M.; Brazma, Alvis; Choudhary, Jyoti S.; Harrow, Jennifer

    2016-01-01

    Complete annotation of the human genome is indispensable for medical research. The GENCODE consortium strives to provide this, augmenting computational and experimental evidence with manual annotation. The rapidly developing field of proteogenomics provides evidence for the translation of genes into proteins and can be used to discover and refine gene models. However, for both the proteomics and annotation groups, there is a lack of guidelines for integrating this data. Here we report a stringent workflow for the interpretation of proteogenomic data that could be used by the annotation community to interpret novel proteogenomic evidence. Based on reprocessing of three large-scale publicly available human data sets, we show that a conservative approach, using stringent filtering is required to generate valid identifications. Evidence has been found supporting 16 novel protein-coding genes being added to GENCODE. Despite this many peptide identifications in pseudogenes cannot be annotated due to the absence of orthogonal supporting evidence. PMID:27250503

  15. Improving GENCODE reference gene annotation using a high-stringency proteogenomics workflow.

    PubMed

    Wright, James C; Mudge, Jonathan; Weisser, Hendrik; Barzine, Mitra P; Gonzalez, Jose M; Brazma, Alvis; Choudhary, Jyoti S; Harrow, Jennifer

    2016-01-01

    Complete annotation of the human genome is indispensable for medical research. The GENCODE consortium strives to provide this, augmenting computational and experimental evidence with manual annotation. The rapidly developing field of proteogenomics provides evidence for the translation of genes into proteins and can be used to discover and refine gene models. However, for both the proteomics and annotation groups, there is a lack of guidelines for integrating this data. Here we report a stringent workflow for the interpretation of proteogenomic data that could be used by the annotation community to interpret novel proteogenomic evidence. Based on reprocessing of three large-scale publicly available human data sets, we show that a conservative approach, using stringent filtering is required to generate valid identifications. Evidence has been found supporting 16 novel protein-coding genes being added to GENCODE. Despite this many peptide identifications in pseudogenes cannot be annotated due to the absence of orthogonal supporting evidence. PMID:27250503

  16. Image Annotation and Database Mining to Create a Novel Screen for the Chemotype-Dependent Crystallization of HCV NS3 Protease

    SciTech Connect

    H Klei; K Kish; M Russo; S Michalczyk; M Cahn; J Tredup; C Chang; J Khan; E Baldwin

    2011-12-31

    An effective process for screening, imaging, and optimizing crystallization trials using a combination of external and internal hardware and software has been deployed. The combination of this infrastructure with a vast annotated crystallization database enables the creation of custom crystallization screening strategies. Because of the strong chemotype-dependent crystallization observed with HCV NS3 protease (HCVPr), this strategy was applied to a chemotype resistant to all prior crystallization efforts. The crystallization database was mined for ingredients used to generate earlier HCVPr/inhibitor co-crystals. A random screen was created from the most prolific ingredients. A previously untested combination of proven ingredients was identified that led to a successful crystallization condition for the resistant chemotype.

  17. Correction of the Caulobacter crescentus NA1000 genome annotation.

    PubMed

    Ely, Bert; Scott, LaTia Etheredge

    2014-01-01

    Bacterial genome annotations are accumulating rapidly in the GenBank database and the use of automated annotation technologies to create these annotations has become the norm. However, these automated methods commonly result in a small, but significant percentage of genome annotation errors. To improve accuracy and reliability, we analyzed the Caulobacter crescentus NA1000 genome utilizing computer programs Artemis and MICheck to manually examine the third codon position GC content, alignment to a third codon position GC frame plot peak, and matches in the GenBank database. We identified 11 new genes, modified the start site of 113 genes, and changed the reading frame of 38 genes that had been incorrectly annotated. Furthermore, our manual method of identifying protein-coding genes allowed us to remove 112 non-coding regions that had been designated as coding regions. The improved NA1000 genome annotation resulted in a reduction in the use of rare codons since noncoding regions with atypical codon usage were removed from the annotation and 49 new coding regions were added to the annotation. Thus, a more accurate codon usage table was generated as well. These results demonstrate that a comparison of the location of peaks third codon position GC content to the location of protein coding regions could be used to verify the annotation of any genome that has a GC content that is greater than 60%.

  18. Expression profiling of hypothetical genes in Desulfovibrio vulgaris leads to improved functional annotation

    SciTech Connect

    Elias, Dwayne A.; Mukhopadhyay, Aindrila; Joachimiak, Marcin P.; Drury, Elliott C.; Redding, Alyssa M.; Yen, Huei-Che B.; Fields, Matthew W.; Hazen, Terry C.; Arkin, Adam P.; Keasling, Jay D.; Wall, Judy D.

    2008-10-27

    Hypothetical and conserved hypothetical genes account for>30percent of sequenced bacterial genomes. For the sulfate-reducing bacterium Desulfovibrio vulgaris Hildenborough, 347 of the 3634 genes were annotated as conserved hypothetical (9.5percent) along with 887 hypothetical genes (24.4percent). Given the large fraction of the genome, it is plausible that some of these genes serve critical cellular roles. The study goals were to determine which genes were expressed and provide a more functionally based annotation. To accomplish this, expression profiles of 1234 hypothetical and conserved genes were used from transcriptomic datasets of 11 environmental stresses, complemented with shotgun LC-MS/MS and AMT tag proteomic data. Genes were divided into putatively polycistronic operons and those predicted to be monocistronic, then classified by basal expression levels and grouped according to changes in expression for one or multiple stresses. 1212 of these genes were transcribed with 786 producing detectable proteins. There was no evidence for expression of 17 predicted genes. Except for the latter, monocistronic gene annotation was expanded using the above criteria along with matching Clusters of Orthologous Groups. Polycistronic genes were annotated in the same manner with inferences from their proximity to more confidently annotated genes. Two targeted deletion mutants were used as test cases to determine the relevance of the inferred functional annotations.

  19. Development of the Community Health Improvement Navigator Database of Interventions.

    PubMed

    Roy, Brita; Stanojevich, Joel; Stange, Paul; Jiwani, Nafisa; King, Raymond; Koo, Denise

    2016-02-26

    With the passage of the Patient Protection and Affordable Care Act, the requirements for hospitals to achieve tax-exempt status include performing a triennial community health needs assessment and developing a plan to address identified needs. To address community health needs, multisector collaborative efforts to improve both health care and non-health care determinants of health outcomes have been the most effective and sustainable. In 2015, CDC released the Community Health Improvement Navigator to facilitate the development of these efforts. This report describes the development of the database of interventions included in the Community Health Improvement Navigator. The database of interventions allows the user to easily search for multisector, collaborative, evidence-based interventions to address the underlying causes of the greatest morbidity and mortality in the United States: tobacco use and exposure, physical inactivity, unhealthy diet, high cholesterol, high blood pressure, diabetes, and obesity.

  20. A Coding System with Independent Annotations of Gesture Forms and Functions during Verbal Communication: Development of a Database of Speech and GEsture (DoSaGE)

    PubMed Central

    Kong, Anthony Pak-Hin; Law, Sam-Po; Kwan, Connie Ching-Yin; Lai, Christy; Lam, Vivian

    2014-01-01

    Gestures are commonly used together with spoken language in human communication. One major limitation of gesture investigations in the existing literature lies in the fact that the coding of forms and functions of gestures has not been clearly differentiated. This paper first described a recently developed Database of Speech and GEsture (DoSaGE) based on independent annotation of gesture forms and functions among 119 neurologically unimpaired right-handed native speakers of Cantonese (divided into three age and two education levels), and presented findings of an investigation examining how gesture use was related to age and linguistic performance. Consideration of these two factors, for which normative data are currently very limited or lacking in the literature, is relevant and necessary when one evaluates gesture employment among individuals with and without language impairment. Three speech tasks, including monologue of a personally important event, sequential description, and story-telling, were used for elicitation. The EUDICO Linguistic ANnotator (ELAN) software was used to independently annotate each participant’s linguistic information of the transcript, forms of gestures used, and the function for each gesture. About one-third of the subjects did not use any co-verbal gestures. While the majority of gestures were non-content-carrying, which functioned mainly for reinforcing speech intonation or controlling speech flow, the content-carrying ones were used to enhance speech content. Furthermore, individuals who are younger or linguistically more proficient tended to use fewer gestures, suggesting that normal speakers gesture differently as a function of age and linguistic performance. PMID:25667563

  1. GO annotation in InterPro: why stability does not indicate accuracy in a sea of changing annotations.

    PubMed

    Sangrador-Vegas, Amaia; Mitchell, Alex L; Chang, Hsin-Yu; Yong, Siew-Yit; Finn, Robert D

    2016-01-01

    The removal of annotation from biological databases is often perceived as an indicator of erroneous annotation. As a corollary, annotation stability is considered to be a measure of reliability. However, diverse data-driven events can affect the stability of annotations in both primary protein sequence databases and the protein family databases that are built upon the sequence databases and used to help annotate them. Here, we describe some of these events and their consequences for the InterPro database, and demonstrate that annotation removal or reassignment is not always linked to incorrect annotation by the curator. Database URL: http://www.ebi.ac.uk/interpro.

  2. Facilitating functional annotation of chicken microarray data

    PubMed Central

    2009-01-01

    Background Modeling results from chicken microarray studies is challenging for researchers due to little functional annotation associated with these arrays. The Affymetrix GenChip chicken genome array, one of the biggest arrays that serve as a key research tool for the study of chicken functional genomics, is among the few arrays that link gene products to Gene Ontology (GO). However the GO annotation data presented by Affymetrix is incomplete, for example, they do not show references linked to manually annotated functions. In addition, there is no tool that facilitates microarray researchers to directly retrieve functional annotations for their datasets from the annotated arrays. This costs researchers amount of time in searching multiple GO databases for functional information. Results We have improved the breadth of functional annotations of the gene products associated with probesets on the Affymetrix chicken genome array by 45% and the quality of annotation by 14%. We have also identified the most significant diseases and disorders, different types of genes, and known drug targets represented on Affymetrix chicken genome array. To facilitate functional annotation of other arrays and microarray experimental datasets we developed an Array GO Mapper (AGOM) tool to help researchers to quickly retrieve corresponding functional information for their dataset. Conclusion Results from this study will directly facilitate annotation of other chicken arrays and microarray experimental datasets. Researchers will be able to quickly model their microarray dataset into more reliable biological functional information by using AGOM tool. The disease, disorders, gene types and drug targets revealed in the study will allow researchers to learn more about how genes function in complex biological systems and may lead to new drug discovery and development of therapies. The GO annotation data generated will be available for public use via AgBase website and will be updated on regular

  3. ACID: annotation of cassette and integron data

    PubMed Central

    Joss, Michael J; Koenig, Jeremy E; Labbate, Maurizio; Polz, Martin F; Gillings, Michael R; Stokes, Harold W; Doolittle, W Ford; Boucher, Yan

    2009-01-01

    Background Although integrons and their associated gene cassettes are present in ~10% of bacteria and can represent up to 3% of the genome in which they are found, very few have been properly identified and annotated in public databases. These genetic elements have been overlooked in comparison to other vectors that facilitate lateral gene transfer between microorganisms. Description By automating the identification of integron integrase genes and of the non-coding cassette-associated attC recombination sites, we were able to assemble a database containing all publicly available sequence information regarding these genetic elements. Specialists manually curated the database and this information was used to improve the automated detection and annotation of integrons and their encoded gene cassettes. ACID (annotation of cassette and integron data) can be searched using a range of queries and the data can be downloaded in a number of formats. Users can readily annotate their own data and integrate it into ACID using the tools provided. Conclusion ACID is a community resource providing easy access to annotations of integrons and making tools available to detect them in novel sequence data. ACID also hosts a forum to prompt integron-related discussion, which can hopefully lead to a more universal definition of this genetic element. PMID:19383137

  4. AraPPISite: a database of fine-grained protein-protein interaction site annotations for Arabidopsis thaliana.

    PubMed

    Li, Hong; Yang, Shiping; Wang, Chuan; Zhou, Yuan; Zhang, Ziding

    2016-09-01

    Knowledge about protein interaction sites provides detailed information of protein-protein interactions (PPIs). To date, nearly 20,000 of PPIs from Arabidopsis thaliana have been identified. Nevertheless, the interaction site information has been largely missed by previously published PPI databases. Here, AraPPISite, a database that presents fine-grained interaction details for A. thaliana PPIs is established. First, the experimentally determined 3D structures of 27 A. thaliana PPIs are collected from the Protein Data Bank database and the predicted 3D structures of 3023 A. thaliana PPIs are modeled by using two well-established template-based docking methods. For each experimental/predicted complex structure, AraPPISite not only provides an interactive user interface for browsing interaction sites, but also lists detailed evolutionary and physicochemical properties of these sites. Second, AraPPISite assigns domain-domain interactions or domain-motif interactions to 4286 PPIs whose 3D structures cannot be modeled. In this case, users can easily query protein interaction regions at the sequence level. AraPPISite is a free and user-friendly database, which does not require user registration or any configuration on local machines. We anticipate AraPPISite can serve as a helpful database resource for the users with less experience in structural biology or protein bioinformatics to probe the details of PPIs, and thus accelerate the studies of plant genetics and functional genomics. AraPPISite is available at http://systbio.cau.edu.cn/arappisite/index.html .

  5. AraPPISite: a database of fine-grained protein-protein interaction site annotations for Arabidopsis thaliana.

    PubMed

    Li, Hong; Yang, Shiping; Wang, Chuan; Zhou, Yuan; Zhang, Ziding

    2016-09-01

    Knowledge about protein interaction sites provides detailed information of protein-protein interactions (PPIs). To date, nearly 20,000 of PPIs from Arabidopsis thaliana have been identified. Nevertheless, the interaction site information has been largely missed by previously published PPI databases. Here, AraPPISite, a database that presents fine-grained interaction details for A. thaliana PPIs is established. First, the experimentally determined 3D structures of 27 A. thaliana PPIs are collected from the Protein Data Bank database and the predicted 3D structures of 3023 A. thaliana PPIs are modeled by using two well-established template-based docking methods. For each experimental/predicted complex structure, AraPPISite not only provides an interactive user interface for browsing interaction sites, but also lists detailed evolutionary and physicochemical properties of these sites. Second, AraPPISite assigns domain-domain interactions or domain-motif interactions to 4286 PPIs whose 3D structures cannot be modeled. In this case, users can easily query protein interaction regions at the sequence level. AraPPISite is a free and user-friendly database, which does not require user registration or any configuration on local machines. We anticipate AraPPISite can serve as a helpful database resource for the users with less experience in structural biology or protein bioinformatics to probe the details of PPIs, and thus accelerate the studies of plant genetics and functional genomics. AraPPISite is available at http://systbio.cau.edu.cn/arappisite/index.html . PMID:27338257

  6. The Plant Ontology Database: A community resource for plant structure and developmental stages controlled vocabulary and annotations

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The Plant Ontology Consortium (POC, http://www.plantontology.org) is a collaborative effort among model plant genome databases and plant researchers that aim to create, maintain, and facilitate the use of a controlled vocabulary(ontology) for plants. The ontology allows users to ascribe attributes o...

  7. The Plant Ontology Database: A Community Resource for Plant Structure and Developmental Stages Controlled Vocabulary and Annotations

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The Plant Ontology Consortium (POC, http://www.plantontology.org) is a collaborative effort among model plant genome databases and plant researchers that aims to create, maintain and facilitate the use of a controlled vocabulary(ontology) for plants. The ontology allows users to ascribe attributes o...

  8. Aviation and the Environment. A Selected, Annotated Bibliography Related to Aviation's Responses Toward Improving the Environment.

    ERIC Educational Resources Information Center

    Marshall, Jane

    This informal, brief bibliography attempts to stress the positive side of aviation, annotating documents that explain how the airlines, aircraft engine manufacturers, government agencies, military aviation, and general aviation are meeting their responsibilities in solving environmental problems. Topics arousing public concern are identified:…

  9. Improving knowledge management through the support of image examination and data annotation using DICOM structured reporting.

    PubMed

    Torres, José Salavert; Damian Segrelles Quilis, J; Espert, Ignacio Blanquer; García, Vicente Hernandez

    2012-12-01

    An important effort has been invested on improving the image diagnosis process in different medical areas using information technologies. The field of medical imaging involves two main data types: medical imaging and reports. Developments based on the DICOM standard have demonstrated to be a convenient and widespread solution among the medical community. The main objective of this work is to design a Web application prototype that will be able to improve diagnosis and follow-on of breast cancer patients. It is based on TRENCADIS middleware, which provides a knowledge-oriented storage model composed by federated repositories of DICOM image studies and DICOM-SR medical reports. The full structure and contents of the diagnosis reports are used as metadata for indexing images. The TRENCADIS infrastructure takes full advantage of Grid technologies by deploying multi-resource grid services that enable multiple views (reports schemes) of the knowledge database. The paper presents a real deployment of such Web application prototype in the Dr. Peset Hospital providing radiologists with a tool to create, store and search diagnostic reports based on breast cancer explorations (mammography, magnetic resonance, ultrasound, pre-surgery biopsy and post-surgery biopsy), improving support for diagnostics decisions. A technical details for use cases (outlining enhanced multi-resource grid services communication and processing steps) and interactions between actors and the deployed prototype are described. As a result, information is more structured, the logic is clearer, network messages have been reduced and, in general, the system is more resistant to failures.

  10. Improving knowledge management through the support of image examination and data annotation using DICOM structured reporting.

    PubMed

    Torres, José Salavert; Damian Segrelles Quilis, J; Espert, Ignacio Blanquer; García, Vicente Hernandez

    2012-12-01

    An important effort has been invested on improving the image diagnosis process in different medical areas using information technologies. The field of medical imaging involves two main data types: medical imaging and reports. Developments based on the DICOM standard have demonstrated to be a convenient and widespread solution among the medical community. The main objective of this work is to design a Web application prototype that will be able to improve diagnosis and follow-on of breast cancer patients. It is based on TRENCADIS middleware, which provides a knowledge-oriented storage model composed by federated repositories of DICOM image studies and DICOM-SR medical reports. The full structure and contents of the diagnosis reports are used as metadata for indexing images. The TRENCADIS infrastructure takes full advantage of Grid technologies by deploying multi-resource grid services that enable multiple views (reports schemes) of the knowledge database. The paper presents a real deployment of such Web application prototype in the Dr. Peset Hospital providing radiologists with a tool to create, store and search diagnostic reports based on breast cancer explorations (mammography, magnetic resonance, ultrasound, pre-surgery biopsy and post-surgery biopsy), improving support for diagnostics decisions. A technical details for use cases (outlining enhanced multi-resource grid services communication and processing steps) and interactions between actors and the deployed prototype are described. As a result, information is more structured, the logic is clearer, network messages have been reduced and, in general, the system is more resistant to failures. PMID:22841747

  11. The Plant Ontology Database: a community resource for plant structure and developmental stages controlled vocabulary and annotations.

    PubMed

    Avraham, Shulamit; Tung, Chih-Wei; Ilic, Katica; Jaiswal, Pankaj; Kellogg, Elizabeth A; McCouch, Susan; Pujar, Anuradha; Reiser, Leonore; Rhee, Seung Y; Sachs, Martin M; Schaeffer, Mary; Stein, Lincoln; Stevens, Peter; Vincent, Leszek; Zapata, Felipe; Ware, Doreen

    2008-01-01

    The Plant Ontology Consortium (POC, http://www.plantontology.org) is a collaborative effort among model plant genome databases and plant researchers that aims to create, maintain and facilitate the use of a controlled vocabulary (ontology) for plants. The ontology allows users to ascribe attributes of plant structure (anatomy and morphology) and developmental stages to data types, such as genes and phenotypes, to provide a semantic framework to make meaningful cross-species and database comparisons. The POC builds upon groundbreaking work by the Gene Ontology Consortium (GOC) by adopting and extending the GOC's principles, existing software and database structure. Over the past year, POC has added hundreds of ontology terms to associate with thousands of genes and gene products from Arabidopsis, rice and maize, which are available through a newly updated web-based browser (http://www.plantontology.org/amigo/go.cgi) for viewing, searching and querying. The Consortium has also implemented new functionalities to facilitate the application of PO in genomic research and updated the website to keep the contents current. In this report, we present a brief description of resources available from the website, changes to the interfaces, data updates, community activities and future enhancement.

  12. Algal functional annotation tool

    SciTech Connect

    2012-07-12

    Abstract BACKGROUND: Progress in genome sequencing is proceeding at an exponential pace, and several new algal genomes are becoming available every year. One of the challenges facing the community is the association of protein sequences encoded in the genomes with biological function. While most genome assembly projects generate annotations for predicted protein sequences, they are usually limited and integrate functional terms from a limited number of databases. Another challenge is the use of annotations to interpret large lists of 'interesting' genes generated by genome-scale datasets. Previously, these gene lists had to be analyzed across several independent biological databases, often on a gene-by-gene basis. In contrast, several annotation databases, such as DAVID, integrate data from multiple functional databases and reveal underlying biological themes of large gene lists. While several such databases have been constructed for animals, none is currently available for the study of algae. Due to renewed interest in algae as potential sources of biofuels and the emergence of multiple algal genome sequences, a significant need has arisen for such a database to process the growing compendiums of algal genomic data. DESCRIPTION: The Algal Functional Annotation Tool is a web-based comprehensive analysis suite integrating annotation data from several pathway, ontology, and protein family databases. The current version provides annotation for the model alga Chlamydomonas reinhardtii, and in the future will include additional genomes. The site allows users to interpret large gene lists by identifying associated functional terms, and their enrichment. Additionally, expression data for several experimental conditions were compiled and analyzed to provide an expression-based enrichment search. A tool to search for functionally-related genes based on gene expression across these conditions is also provided. Other features include dynamic visualization of genes on KEGG

  13. Algal functional annotation tool

    2012-07-12

    Abstract BACKGROUND: Progress in genome sequencing is proceeding at an exponential pace, and several new algal genomes are becoming available every year. One of the challenges facing the community is the association of protein sequences encoded in the genomes with biological function. While most genome assembly projects generate annotations for predicted protein sequences, they are usually limited and integrate functional terms from a limited number of databases. Another challenge is the use of annotations tomore » interpret large lists of 'interesting' genes generated by genome-scale datasets. Previously, these gene lists had to be analyzed across several independent biological databases, often on a gene-by-gene basis. In contrast, several annotation databases, such as DAVID, integrate data from multiple functional databases and reveal underlying biological themes of large gene lists. While several such databases have been constructed for animals, none is currently available for the study of algae. Due to renewed interest in algae as potential sources of biofuels and the emergence of multiple algal genome sequences, a significant need has arisen for such a database to process the growing compendiums of algal genomic data. DESCRIPTION: The Algal Functional Annotation Tool is a web-based comprehensive analysis suite integrating annotation data from several pathway, ontology, and protein family databases. The current version provides annotation for the model alga Chlamydomonas reinhardtii, and in the future will include additional genomes. The site allows users to interpret large gene lists by identifying associated functional terms, and their enrichment. Additionally, expression data for several experimental conditions were compiled and analyzed to provide an expression-based enrichment search. A tool to search for functionally-related genes based on gene expression across these conditions is also provided. Other features include dynamic visualization of genes on

  14. Negatome 2.0: a database of non-interacting proteins derived by literature mining, manual annotation and protein structure analysis.

    PubMed

    Blohm, Philipp; Frishman, Goar; Smialowski, Pawel; Goebels, Florian; Wachinger, Benedikt; Ruepp, Andreas; Frishman, Dmitrij

    2014-01-01

    Knowledge about non-interacting proteins (NIPs) is important for training the algorithms to predict protein-protein interactions (PPIs) and for assessing the false positive rates of PPI detection efforts. We present the second version of Negatome, a database of proteins and protein domains that are unlikely to engage in physical interactions (available online at http://mips.helmholtz-muenchen.de/proj/ppi/negatome). Negatome is derived by manual curation of literature and by analyzing three-dimensional structures of protein complexes. The main methodological innovation in Negatome 2.0 is the utilization of an advanced text mining procedure to guide the manual annotation process. Potential non-interactions were identified by a modified version of Excerbt, a text mining tool based on semantic sentence analysis. Manual verification shows that nearly a half of the text mining results with the highest confidence values correspond to NIP pairs. Compared to the first version the contents of the database have grown by over 300%.

  15. Managing the data deluge: data-driven GO category assignment improves while complexity of functional annotation increases.

    PubMed

    Gobeill, Julien; Pasche, Emilie; Vishnyakova, Dina; Ruch, Patrick

    2013-01-01

    The available curated data lag behind current biological knowledge contained in the literature. Text mining can assist biologists and curators to locate and access this knowledge, for instance by characterizing the functional profile of publications. Gene Ontology (GO) category assignment in free text already supports various applications, such as powering ontology-based search engines, finding curation-relevant articles (triage) or helping the curator to identify and encode functions. Popular text mining tools for GO classification are based on so called thesaurus-based--or dictionary-based--approaches, which exploit similarities between the input text and GO terms themselves. But their effectiveness remains limited owing to the complex nature of GO terms, which rarely occur in text. In contrast, machine learning approaches exploit similarities between the input text and already curated instances contained in a knowledge base to infer a functional profile. GO Annotations (GOA) and MEDLINE make possible to exploit a growing amount of curated abstracts (97 000 in November 2012) for populating this knowledge base. Our study compares a state-of-the-art thesaurus-based system with a machine learning system (based on a k-Nearest Neighbours algorithm) for the task of proposing a functional profile for unseen MEDLINE abstracts, and shows how resources and performances have evolved. Systems are evaluated on their ability to propose for a given abstract the GO terms (2.8 on average) used for curation in GOA. We show that since 2006, although a massive effort was put into adding synonyms in GO (+300%), our thesaurus-based system effectiveness is rather constant, reaching from 0.28 to 0.31 for Recall at 20 (R20). In contrast, thanks to its knowledge base growth, our machine learning system has steadily improved, reaching from 0.38 in 2006 to 0.56 for R20 in 2012. Integrated in semi-automatic workflows or in fully automatic pipelines, such systems are more and more efficient

  16. Managing the data deluge: data-driven GO category assignment improves while complexity of functional annotation increases.

    PubMed

    Gobeill, Julien; Pasche, Emilie; Vishnyakova, Dina; Ruch, Patrick

    2013-01-01

    The available curated data lag behind current biological knowledge contained in the literature. Text mining can assist biologists and curators to locate and access this knowledge, for instance by characterizing the functional profile of publications. Gene Ontology (GO) category assignment in free text already supports various applications, such as powering ontology-based search engines, finding curation-relevant articles (triage) or helping the curator to identify and encode functions. Popular text mining tools for GO classification are based on so called thesaurus-based--or dictionary-based--approaches, which exploit similarities between the input text and GO terms themselves. But their effectiveness remains limited owing to the complex nature of GO terms, which rarely occur in text. In contrast, machine learning approaches exploit similarities between the input text and already curated instances contained in a knowledge base to infer a functional profile. GO Annotations (GOA) and MEDLINE make possible to exploit a growing amount of curated abstracts (97 000 in November 2012) for populating this knowledge base. Our study compares a state-of-the-art thesaurus-based system with a machine learning system (based on a k-Nearest Neighbours algorithm) for the task of proposing a functional profile for unseen MEDLINE abstracts, and shows how resources and performances have evolved. Systems are evaluated on their ability to propose for a given abstract the GO terms (2.8 on average) used for curation in GOA. We show that since 2006, although a massive effort was put into adding synonyms in GO (+300%), our thesaurus-based system effectiveness is rather constant, reaching from 0.28 to 0.31 for Recall at 20 (R20). In contrast, thanks to its knowledge base growth, our machine learning system has steadily improved, reaching from 0.38 in 2006 to 0.56 for R20 in 2012. Integrated in semi-automatic workflows or in fully automatic pipelines, such systems are more and more efficient

  17. DSSTOX STRUCTURE-SEARCHABLE PUBLIC TOXICITY DATABASE NETWORK: CURRENT PROGRESS AND NEW INITIATIVES TO IMPROVE CHEMO-BIOINFORMATICS CAPABILITIES

    EPA Science Inventory

    The EPA DSSTox website (http://www/epa.gov/nheerl/dsstox) publishes standardized, structure-annotated toxicity databases, covering a broad range of toxicity disciplines. Each DSSTox database features documentation written in collaboration with the source authors and toxicity expe...

  18. Information Retrieval in Domain-Specific Databases: An Analysis To Improve the User Interface of the Alcohol Studies Database.

    ERIC Educational Resources Information Center

    Jantz, Ronald

    2003-01-01

    Describes the methodology and results of the log analysis for the Alcohol Studies Database (ASDB), a domain-specific database supported by the Center of Alcohol Studies at Rutgers University Libraries. The objectives were to better understand user search behavior, to analyze failure rates, and to develop approaches for improving the user…

  19. Expression profiling of hypothetical genes in Desulfovibrio vulgaris leads to improved functional annotation

    SciTech Connect

    Elias, Dwayne A.; Mukhopadhyay, Aindrila; Joachimiak, Marcine P.; Drury, Elliott C.; Redding, Alyssa M.; Yen, Huei-Che B.; Fields, Matthew; Hazen, Terry C.; Arkin, Adam P.; Keasling, Jay D.; Wall, Judy D.

    2009-03-17

    Hypothetical (HyP) and conserved HyP genes account for >30% of sequenced bacterial genomes. For the sulfate-reducing bacterium Desulfovibrio vulgaris Hildenborough, 347 of the 3634 genes were annotated as conserved HyP (9.5%) along with 887 HyP genes (24.4%). Given the large fraction of the genome, it is plausible that some of these genes serve critical cellular roles. The study goals were to determine which genes were expressed and provide a more functionally based annotation. To accomplish this, expression profiles of 1234 HyP and conserved genes were used from transcriptomic datasets of 11 environmental stresses, complemented with shotgun LC–MS/MS and AMT tag proteomic data. Genes were divided into putatively polycistronic operons and those predicted to be monocistronic, then classified by basal expression levels and grouped according to changes in expression for one or multiple stresses. One thousand two hundred and twelve of these genes were transcribed with 786 producing detectable proteins. There was no evidence for expression of 17 predicted genes.

  20. Novel scripts for improved annotation and selection of variants from whole exome sequencing in cancer research.

    PubMed

    Hansen, Marcus Celik; Nederby, Line; Roug, Anne; Villesen, Palle; Kjeldsen, Eigil; Nyvold, Charlotte Guldborg; Hokland, Peter

    2015-01-01

    Sequencing the exome is quickly becoming the preferred method for discovering disease-inducing mutations. While obtaining data sets is a straightforward procedure, the subsequent analysis and interpretation of the data is a limiting step for clinical applications. Thus, while the initial mutation and variant calling can be performed by a bioinformatician or trained researcher, the output from robust packages such as MuTect and GATK is not directly informative for the general life scientists. In attempt to obviate this problem we have created complementary Wolfram scripts, which enable easy downstream annotation and selection, presented here in the perspective of hematological relevance. It also provides the researcher with the opportunity to extend the analysis by having a full-fledged programming and analysis environment of Mathematica at hand. In brief, post-processing is performed by: •Mapping of germ line and somatic variants to coding regions, and defining variant sets within Mathematica.•Processing of variants in variant effect predictor.•Extended annotation, relevance scoring and defining focus areas through the provided functions. PMID:26150983

  1. Improving the quality of genome, protein sequence, and taxonomy databases: a prerequisite for microbiome meta-omics 2.0.

    PubMed

    Pible, Olivier; Armengaud, Jean

    2015-10-01

    High-throughput shotgun metaproteomic approaches on environmental or medical microbiomes are producing huge amounts of tandem mass spectrometry data. These can be interpreted either with a general protein sequence database comprising tens of thousands of sequenced genomes or with a more customized database such as those obtained after metagenome sequencing of the DNA extracted from the same sample. However, not all entries in a nucleotide or protein sequence database are of equal quality and this can critically impact metaproteomic data interpretation. In this viewpoint article, we exemplify several key issues. First, either genome or transcriptome data interpretation due to inaccurate contig assembly and gene prediction may be erroneous, for its mitigation the metaproteogenomic strategies could have an interesting perspective. Errors in sample handling and taxonomical characterization may also be problematic. Cross-contamination of genome sequences is also underestimated while frequent. As a consequence of these structural errors regarding protein sequences and additional problems due to homology-based functional annotation of proteins, specific efforts for better interpretation of metaproteomic data are required. We propose the development of new bioinformatic pipelines devoted to detection and correction of errors and contaminations to improve the overall quality of sequence and taxonomy databases for metaproteomics. PMID:26038180

  2. Improving the quality of genome, protein sequence, and taxonomy databases: a prerequisite for microbiome meta-omics 2.0.

    PubMed

    Pible, Olivier; Armengaud, Jean

    2015-10-01

    High-throughput shotgun metaproteomic approaches on environmental or medical microbiomes are producing huge amounts of tandem mass spectrometry data. These can be interpreted either with a general protein sequence database comprising tens of thousands of sequenced genomes or with a more customized database such as those obtained after metagenome sequencing of the DNA extracted from the same sample. However, not all entries in a nucleotide or protein sequence database are of equal quality and this can critically impact metaproteomic data interpretation. In this viewpoint article, we exemplify several key issues. First, either genome or transcriptome data interpretation due to inaccurate contig assembly and gene prediction may be erroneous, for its mitigation the metaproteogenomic strategies could have an interesting perspective. Errors in sample handling and taxonomical characterization may also be problematic. Cross-contamination of genome sequences is also underestimated while frequent. As a consequence of these structural errors regarding protein sequences and additional problems due to homology-based functional annotation of proteins, specific efforts for better interpretation of metaproteomic data are required. We propose the development of new bioinformatic pipelines devoted to detection and correction of errors and contaminations to improve the overall quality of sequence and taxonomy databases for metaproteomics.

  3. Genic and Intergenic SSR Database Generation, SNPs Determination and Pathway Annotations, in Date Palm (Phoenix dactylifera L.).

    PubMed

    Mokhtar, Morad M; Adawy, Sami S; El-Assal, Salah El-Din S; Hussein, Ebtissam H A

    2016-01-01

    The present investigation was carried out aiming to use the bioinformatics tools in order to identify and characterize, simple sequence repeats within the third Version of the date palm genome and develop a new SSR primers database. In addition single nucleotide polymorphisms (SNPs) that are located within the SSR flanking regions were recognized. Moreover, the pathways for the sequences assigned by SSR primers, the biological functions and gene interaction were determined. A total of 172,075 SSR motifs was identified on date palm genome sequence with a frequency of 450.97 SSRs per Mb. Out of these, 130,014 SSRs (75.6%) were located within the intergenic regions with a frequency of 499 SSRs per Mb. While, only 42,061 SSRs (24.4%) were located within the genic regions with a frequency of 347.5 SSRs per Mb. A total of 111,403 of SSR primer pairs were designed, that represents 291.9 SSR primers per Mb. Out of the 111,403, only 31,380 SSR primers were in the genic regions, while 80,023 primers were in the intergenic regions. A number of 250,507 SNPs were recognized in 84,172 SSR flanking regions, which represents 75.55% of the total SSR flanking regions. Out of 12,274 genes only 463 genes comprising 896 SSR primers were mapped onto 111 pathways using KEGG data base. The most abundant enzymes were identified in the pathway related to the biosynthesis of antibiotics. We tested 1031 SSR primers using both publicly available date palm genome sequences as templates in the in silico PCR reactions. Concerning in vitro validation, 31 SSR primers among those used in the in silico PCR were synthesized and tested for their ability to detect polymorphism among six Egyptian date palm cultivars. All tested primers have successfully amplified products, but only 18 primers detected polymorphic amplicons among the studied date palm cultivars. PMID:27434138

  4. Genic and Intergenic SSR Database Generation, SNPs Determination and Pathway Annotations, in Date Palm (Phoenix dactylifera L.).

    PubMed

    Mokhtar, Morad M; Adawy, Sami S; El-Assal, Salah El-Din S; Hussein, Ebtissam H A

    2016-01-01

    The present investigation was carried out aiming to use the bioinformatics tools in order to identify and characterize, simple sequence repeats within the third Version of the date palm genome and develop a new SSR primers database. In addition single nucleotide polymorphisms (SNPs) that are located within the SSR flanking regions were recognized. Moreover, the pathways for the sequences assigned by SSR primers, the biological functions and gene interaction were determined. A total of 172,075 SSR motifs was identified on date palm genome sequence with a frequency of 450.97 SSRs per Mb. Out of these, 130,014 SSRs (75.6%) were located within the intergenic regions with a frequency of 499 SSRs per Mb. While, only 42,061 SSRs (24.4%) were located within the genic regions with a frequency of 347.5 SSRs per Mb. A total of 111,403 of SSR primer pairs were designed, that represents 291.9 SSR primers per Mb. Out of the 111,403, only 31,380 SSR primers were in the genic regions, while 80,023 primers were in the intergenic regions. A number of 250,507 SNPs were recognized in 84,172 SSR flanking regions, which represents 75.55% of the total SSR flanking regions. Out of 12,274 genes only 463 genes comprising 896 SSR primers were mapped onto 111 pathways using KEGG data base. The most abundant enzymes were identified in the pathway related to the biosynthesis of antibiotics. We tested 1031 SSR primers using both publicly available date palm genome sequences as templates in the in silico PCR reactions. Concerning in vitro validation, 31 SSR primers among those used in the in silico PCR were synthesized and tested for their ability to detect polymorphism among six Egyptian date palm cultivars. All tested primers have successfully amplified products, but only 18 primers detected polymorphic amplicons among the studied date palm cultivars.

  5. Genic and Intergenic SSR Database Generation, SNPs Determination and Pathway Annotations, in Date Palm (Phoenix dactylifera L.)

    PubMed Central

    2016-01-01

    The present investigation was carried out aiming to use the bioinformatics tools in order to identify and characterize, simple sequence repeats within the third Version of the date palm genome and develop a new SSR primers database. In addition single nucleotide polymorphisms (SNPs) that are located within the SSR flanking regions were recognized. Moreover, the pathways for the sequences assigned by SSR primers, the biological functions and gene interaction were determined. A total of 172,075 SSR motifs was identified on date palm genome sequence with a frequency of 450.97 SSRs per Mb. Out of these, 130,014 SSRs (75.6%) were located within the intergenic regions with a frequency of 499 SSRs per Mb. While, only 42,061 SSRs (24.4%) were located within the genic regions with a frequency of 347.5 SSRs per Mb. A total of 111,403 of SSR primer pairs were designed, that represents 291.9 SSR primers per Mb. Out of the 111,403, only 31,380 SSR primers were in the genic regions, while 80,023 primers were in the intergenic regions. A number of 250,507 SNPs were recognized in 84,172 SSR flanking regions, which represents 75.55% of the total SSR flanking regions. Out of 12,274 genes only 463 genes comprising 896 SSR primers were mapped onto 111 pathways using KEGG data base. The most abundant enzymes were identified in the pathway related to the biosynthesis of antibiotics. We tested 1031 SSR primers using both publicly available date palm genome sequences as templates in the in silico PCR reactions. Concerning in vitro validation, 31 SSR primers among those used in the in silico PCR were synthesized and tested for their ability to detect polymorphism among six Egyptian date palm cultivars. All tested primers have successfully amplified products, but only 18 primers detected polymorphic amplicons among the studied date palm cultivars. PMID:27434138

  6. U.S. EPA computational toxicology programs: Central role of chemical-annotation efforts and molecular databases

    EPA Science Inventory

    EPA’s National Center for Computational Toxicology is engaged in high-profile research efforts to improve the ability to more efficiently and effectively prioritize and screen thousands of environmental chemicals for potential toxicity. A central component of these efforts invol...

  7. The Ensembl gene annotation system.

    PubMed

    Aken, Bronwen L; Ayling, Sarah; Barrell, Daniel; Clarke, Laura; Curwen, Valery; Fairley, Susan; Fernandez Banet, Julio; Billis, Konstantinos; García Girón, Carlos; Hourlier, Thibaut; Howe, Kevin; Kähäri, Andreas; Kokocinski, Felix; Martin, Fergal J; Murphy, Daniel N; Nag, Rishi; Ruffier, Magali; Schuster, Michael; Tang, Y Amy; Vogel, Jan-Hinnerk; White, Simon; Zadissa, Amonida; Flicek, Paul; Searle, Stephen M J

    2016-01-01

    The Ensembl gene annotation system has been used to annotate over 70 different vertebrate species across a wide range of genome projects. Furthermore, it generates the automatic alignment-based annotation for the human and mouse GENCODE gene sets. The system is based on the alignment of biological sequences, including cDNAs, proteins and RNA-seq reads, to the target genome in order to construct candidate transcript models. Careful assessment and filtering of these candidate transcripts ultimately leads to the final gene set, which is made available on the Ensembl website. Here, we describe the annotation process in detail.Database URL: http://www.ensembl.org/index.html. PMID:27337980

  8. The Ensembl gene annotation system

    PubMed Central

    Aken, Bronwen L.; Ayling, Sarah; Barrell, Daniel; Clarke, Laura; Curwen, Valery; Fairley, Susan; Fernandez Banet, Julio; Billis, Konstantinos; García Girón, Carlos; Hourlier, Thibaut; Howe, Kevin; Kähäri, Andreas; Kokocinski, Felix; Martin, Fergal J.; Murphy, Daniel N.; Nag, Rishi; Ruffier, Magali; Schuster, Michael; Tang, Y. Amy; Vogel, Jan-Hinnerk; White, Simon; Zadissa, Amonida; Flicek, Paul

    2016-01-01

    The Ensembl gene annotation system has been used to annotate over 70 different vertebrate species across a wide range of genome projects. Furthermore, it generates the automatic alignment-based annotation for the human and mouse GENCODE gene sets. The system is based on the alignment of biological sequences, including cDNAs, proteins and RNA-seq reads, to the target genome in order to construct candidate transcript models. Careful assessment and filtering of these candidate transcripts ultimately leads to the final gene set, which is made available on the Ensembl website. Here, we describe the annotation process in detail. Database URL: http://www.ensembl.org/index.html PMID:27337980

  9. Improvement of barley genome annotations by deciphering the Haruna Nijo genome

    PubMed Central

    Sato, Kazuhiro; Tanaka, Tsuyoshi; Shigenobu, Shuji; Motoi, Yuka; Wu, Jianzhong; Itoh, Takeshi

    2016-01-01

    Full-length (FL) cDNA sequences provide the most reliable evidence for the presence of genes in genomes. In this report, detailed gene structures of barley, whole genome shotgun (WGS) and additional transcript data of the cultivar Haruna Nijo were quality controlled and compared with the published Morex genome information. Haruna Nijo scaffolds have longer total sequence length with much higher N50 and fewer sequences than those in Morex WGS contigs. The longer Haruna Nijo scaffolds provided efficient FLcDNA mapping, resulting in high coverage and detection of the transcription start sites. In combination with FLcDNAs and RNA-Seq data from four different tissue samples of Haruna Nijo, we identified 51,249 gene models on 30,606 loci. Overall sequence similarity between Haruna Nijo and Morex genome was 95.99%, while that of exon regions was higher (99.71%). These sequence and annotation data of Haruna Nijo are combined with Morex genome data and released from a genome browser. The genome sequence of Haruna Nijo may provide detailed gene structures in addition to the current Morex barley genome information. PMID:26622062

  10. Pathway Analysis Software: Annotation Errors and Solutions

    PubMed Central

    Henderson-MacLennan, Nicole K.; Papp, Jeanette C.; Talbot, C. Conover; McCabe, Edward R.B.; Presson, Angela P.

    2010-01-01

    Genetic databases contain a variety of annotation errors that often go unnoticed due to the large size of modern genetic data sets. Interpretation of these data sets requires bioinformatics tools that may contribute to this problem. While providing gene symbol annotations for identifiers (IDs) such as microarray probeset, RefSeq, GenBank and Entrez Gene is seemingly trivial, the accuracy is fundamental to any subsequent conclusions. We examine gene symbol annotations and results from three commercial pathway analysis software (PAS) packages: Ingenuity Pathways Analysis, GeneGO and Pathway Studio. We compare gene symbol annotations and canonical pathway results over time and among different input ID types. We find that PAS results can be affected by variation in gene symbol annotations across software releases and the input ID type analyzed. As a result, we offer suggestions for using commercial PAS and reporting microarray results to improve research quality. We propose a wiki type website to facilitate communication of bioinformatics software problems within the scientific community. PMID:20663702

  11. Leveraging Genomic Annotations and Pleiotropic Enrichment for Improved Replication Rates in Schizophrenia GWAS

    PubMed Central

    Wang, Yunpeng; Thompson, Wesley K.; Schork, Andrew J.; Holland, Dominic; Chen, Chi-Hua; Bettella, Francesco; Desikan, Rahul S.; Li, Wen; Witoelar, Aree; Zuber, Verena; Devor, Anna; Nöthen, Markus M.; Rietschel, Marcella; Chen, Qiang; Werge, Thomas; Cichon, Sven; Weinberger, Daniel R.; Djurovic, Srdjan; O’Donovan, Michael; Visscher, Peter M.; Andreassen, Ole A.; Dale, Anders M.

    2016-01-01

    Most of the genetic architecture of schizophrenia (SCZ) has not yet been identified. Here, we apply a novel statistical algorithm called Covariate-Modulated Mixture Modeling (CM3), which incorporates auxiliary information (heterozygosity, total linkage disequilibrium, genomic annotations, pleiotropy) for each single nucleotide polymorphism (SNP) to enable more accurate estimation of replication probabilities, conditional on the observed test statistic (“z-score”) of the SNP. We use a multiple logistic regression on z-scores to combine information from auxiliary information to derive a “relative enrichment score” for each SNP. For each stratum of these relative enrichment scores, we obtain nonparametric estimates of posterior expected test statistics and replication probabilities as a function of discovery z-scores, using a resampling-based approach that repeatedly and randomly partitions meta-analysis sub-studies into training and replication samples. We fit a scale mixture of two Gaussians model to each stratum, obtaining parameter estimates that minimize the sum of squared differences of the scale-mixture model with the stratified nonparametric estimates. We apply this approach to the recent genome-wide association study (GWAS) of SCZ (n = 82,315), obtaining a good fit between the model-based and observed effect sizes and replication probabilities. We observed that SNPs with low enrichment scores replicate with a lower probability than SNPs with high enrichment scores even when both they are genome-wide significant (p < 5x10-8). There were 693 and 219 independent loci with model-based replication rates ≥80% and ≥90%, respectively. Compared to analyses not incorporating relative enrichment scores, CM3 increased out-of-sample yield for SNPs that replicate at a given rate. This demonstrates that replication probabilities can be more accurately estimated using prior enrichment information with CM3. PMID:26808560

  12. Algal functional annotation tool

    SciTech Connect

    Lopez, D.; Casero, D.; Cokus, S. J.; Merchant, S. S.; Pellegrini, M.

    2012-07-01

    The Algal Functional Annotation Tool is a web-based comprehensive analysis suite integrating annotation data from several pathway, ontology, and protein family databases. The current version provides annotation for the model alga Chlamydomonas reinhardtii, and in the future will include additional genomes. The site allows users to interpret large gene lists by identifying associated functional terms, and their enrichment. Additionally, expression data for several experimental conditions were compiled and analyzed to provide an expression-based enrichment search. A tool to search for functionally-related genes based on gene expression across these conditions is also provided. Other features include dynamic visualization of genes on KEGG pathway maps and batch gene identifier conversion.

  13. Improving the gene structure annotation of the apicomplexan parasite Neospora caninum fulfils a vital requirement towards an in silico-derived vaccine.

    PubMed

    Goodswen, Stephen J; Barratt, Joel L N; Kennedy, Paul J; Ellis, John T

    2015-04-01

    Neospora caninum is an apicomplexan parasite which can cause abortion in cattle, instigating major economic burden. Vaccination has been proposed as the most cost-effective control measure to alleviate this burden. Consequently the overriding aspiration for N. caninum research is the identification and subsequent evaluation of vaccine candidates in animal models. To save time, cost and effort, it is now feasible to use an in silico approach for vaccine candidate prediction. Precise protein sequences, derived from the correct open reading frame, are paramount and arguably the most important factor determining the success or failure of this approach. The challenge is that publicly available N. caninum sequences are mostly derived from gene predictions. Annotated inaccuracies can lead to erroneously predicted vaccine candidates by bioinformatics programs. This study evaluates the current N. caninum annotation for potential inaccuracies. Comparisons with annotation from a closely related pathogen, Toxoplasma gondii, are also made to distinguish patterns of inconsistency. More importantly, a mRNA sequencing (RNA-Seq) experiment is used to validate the annotation. Potential discrepancies originating from a questionable start codon context and exon boundaries were identified in 1943 protein coding sequences. We conclude, where experimental data were available, that the majority of N. caninum gene sequences were reliably predicted. Nevertheless, almost 28% of genes were identified as questionable. Given the limitations of RNA-Seq, the intention of this study was not to replace the existing annotation but to support or oppose particular aspects of it. Ideally, many studies aimed at improving the annotation are required to build a consensus. We believe this study, in providing a new resource on gene structure and annotation, is a worthy contributor to this endeavour. PMID:25747726

  14. Next Generation Models for Storage and Representation of Microbial Biological Annotation

    SciTech Connect

    Quest, Daniel J; Land, Miriam L; Brettin, Thomas S; Cottingham, Robert W

    2010-01-01

    Background Traditional genome annotation systems were developed in a very different computing era, one where the World Wide Web was just emerging. Consequently, these systems are built as centralized black boxes focused on generating high quality annotation submissions to GenBank/EMBL supported by expert manual curation. The exponential growth of sequence data drives a growing need for increasingly higher quality and automatically generated annotation. Typical annotation pipelines utilize traditional database technologies, clustered computing resources, Perl, C, and UNIX file systems to process raw sequence data, identify genes, and predict and categorize gene function. These technologies tightly couple the annotation software system to hardware and third party software (e.g. relational database systems and schemas). This makes annotation systems hard to reproduce, inflexible to modification over time, difficult to assess, difficult to partition across multiple geographic sites, and difficult to understand for those who are not domain experts. These systems are not readily open to scrutiny and therefore not scientifically tractable. The advent of Semantic Web standards such as Resource Description Framework (RDF) and OWL Web Ontology Language (OWL) enables us to construct systems that address these challenges in a new comprehensive way. Results Here, we develop a framework for linking traditional data to OWL-based ontologies in genome annotation. We show how data standards can decouple hardware and third party software tools from annotation pipelines, thereby making annotation pipelines easier to reproduce and assess. An illustrative example shows how TURTLE (Terse RDF Triple Language) can be used as a human readable, but also semantically-aware, equivalent to GenBank/EMBL files. Conclusions The power of this approach lies in its ability to assemble annotation data from multiple databases across multiple locations into a representation that is understandable to

  15. Improved annotation of antibiotic resistance determinants reveals microbial resistomes cluster by ecology.

    PubMed

    Gibson, Molly K; Forsberg, Kevin J; Dantas, Gautam

    2015-01-01

    Antibiotic resistance is a dire clinical problem with important ecological dimensions. While antibiotic resistance in human pathogens continues to rise at alarming rates, the impact of environmental resistance on human health is still unclear. To investigate the relationship between human-associated and environmental resistomes, we analyzed functional metagenomic selections for resistance against 18 clinically relevant antibiotics from soil and human gut microbiota as well as a set of multidrug-resistant cultured soil isolates. These analyses were enabled by Resfams, a new curated database of protein families and associated highly precise and accurate profile hidden Markov models, confirmed for antibiotic resistance function and organized by ontology. We demonstrate that the antibiotic resistance functions that give rise to the resistance profiles observed in environmental and human-associated microbial communities significantly differ between ecologies. Antibiotic resistance functions that most discriminate between ecologies provide resistance to β-lactams and tetracyclines, two of the most widely used classes of antibiotics in the clinic and agriculture. We also analyzed the antibiotic resistance gene composition of over 6000 sequenced microbial genomes, revealing significant enrichment of resistance functions by both ecology and phylogeny. Together, our results indicate that environmental and human-associated microbial communities harbor distinct resistance genes, suggesting that antibiotic resistance functions are largely constrained by ecology.

  16. Adaptation and Recommendation Techniques to Improve the Quality of Annotations and the Relevance of Resources in Web 2.0 and Semantic Web-Based Applications

    NASA Astrophysics Data System (ADS)

    Torre, Ilaria

    The Web 2.0 and the Semantic Web represent different forms of evolution of the first-generation Web, and both of them enrich Web resources with semantic annotations. Recommendation and personalization of Web resources is another trend that becomes more and more important with the growth of information, and both the Web 2.0 and the Semantic Web are deeply connected to it. The objective of this paper is to analyze the contribution of recommendation and adaptation techniques to these paradigms and to investigate if these techniques can be used as a bridge for their integration. More specifically, the paper will focus on the contribution of adaptation and recommendation techniques to improve the quality of annotations in the Web 2.0, Semantic Web, and mixed approaches and the relevance of annotated resources that are retrieved or filtered to users.

  17. Improving data accuracy of commercial food outlet databases.

    PubMed

    Ohri-Vachaspati, Punam; Martinez, Diane; Yedidia, Michael J; Petlick, Nirvana

    2011-01-01

    PURPOSE. Assessing food environments often requires using commercially available data. Disparate methods used for classifying food outlets in these databases call for creating a classification approach using common definitions. A systematic strategy for reclassifying food stores and restaurants, as they appear in commercial databases, into categories that differentiate the availability of healthy options is described here. DESIGN AND SETTING. Commercially available data on food outlets including names, addresses, North American Industry Classification System codes, and associated characteristics was obtained for five New Jersey communities. ANALYSIS. A reclassification methodology was developed using criteria and definitions from the literature to categorize food outlets based on availability of healthy options. Information in the database was supplemented by systematic Internet and key word searches, and from phone calls to food outlets. RESULTS. The methodology resulted in 622 supermarket/grocery stores, 183 convenience stores, and 148 specialty stores in the original data to be reclassified into 58 supermarkets, 30 grocery stores, 692 convenience stores, and 115 specialty stores. Outlets from the original list of 1485 full-service restaurants and 506 limited-service restaurants were reclassified as 563 full-service restaurants and 1247 limited-service restaurants. Reclassification resulted in less than one-seventh the number of supermarkets and grocery stores, more than three times the number of convenience stores, and twice as many limited-service restaurants-a much less healthy profile than the one generated by using exclusively the commercial databases. CONCLUSION. An explicit and replicable strategy is proposed for reclassifying food outlets in commercial databases into categories that differentiate on the basis of healthy food availability. The intent is to contribute towards building a consensus among researchers on definitions used in public health

  18. WOVOdat, A Worldwide Volcano Unrest Database, to Improve Eruption Forecasts

    NASA Astrophysics Data System (ADS)

    Widiwijayanti, C.; Costa, F.; Win, N. T. Z.; Tan, K.; Newhall, C. G.; Ratdomopurbo, A.

    2015-12-01

    WOVOdat is the World Organization of Volcano Observatories' Database of Volcanic Unrest. An international effort to develop common standards for compiling and storing data on volcanic unrests in a centralized database and freely web-accessible for reference during volcanic crises, comparative studies, and basic research on pre-eruption processes. WOVOdat will be to volcanology as an epidemiological database is to medicine. Despite the large spectrum of monitoring techniques, the interpretation of monitoring data throughout the evolution of the unrest and making timely forecasts remain the most challenging tasks for volcanologists. The field of eruption forecasting is becoming more quantitative, based on the understanding of the pre-eruptive magmatic processes and dynamic interaction between variables that are at play in a volcanic system. Such forecasts must also acknowledge and express the uncertainties, therefore most of current research in this field focused on the application of event tree analysis to reflect multiple possible scenarios and the probability of each scenario. Such forecasts are critically dependent on comprehensive and authoritative global volcano unrest data sets - the very information currently collected in WOVOdat. As the database becomes more complete, Boolean searches, side-by-side digital and thus scalable comparisons of unrest, pattern recognition, will generate reliable results. Statistical distribution obtained from WOVOdat can be then used to estimate the probabilities of each scenario after specific patterns of unrest. We established main web interface for data submission and visualizations, and have now incorporated ~20% of worldwide unrest data into the database, covering more than 100 eruptive episodes. In the upcoming years we will concentrate in acquiring data from volcano observatories develop a robust data query interface, optimizing data mining, and creating tools by which WOVOdat can be used for probabilistic eruption

  19. DSSTOX WEBSITE LAUNCH: IMPROVING PUBLIC ACCESS TO DATABASES FOR BUILDING STRUCTURE-TOXICITY PREDICTION MODELS

    EPA Science Inventory

    DSSTox Website Launch: Improving Public Access to Databases for Building Structure-Toxicity Prediction Models
    Ann M. Richard
    US Environmental Protection Agency, Research Triangle Park, NC, USA

    Distributed: Decentralized set of standardized, field-delimited databases,...

  20. Chemical annotation of small and peptide-like molecules at the Protein Data Bank.

    PubMed

    Young, Jasmine Y; Feng, Zukang; Dimitropoulos, Dimitris; Sala, Raul; Westbrook, John; Zhuravleva, Marina; Shao, Chenghua; Quesada, Martha; Peisach, Ezra; Berman, Helen M

    2013-01-01

    Over the past decade, the number of polymers and their complexes with small molecules in the Protein Data Bank archive (PDB) has continued to increase significantly. To support scientific advancements and ensure the best quality and completeness of the data files over the next 10 years and beyond, the Worldwide PDB partnership that manages the PDB archive is developing a new deposition and annotation system. This system focuses on efficient data capture across all supported experimental methods. The new deposition and annotation system is composed of four major modules that together support all of the processing requirements for a PDB entry. In this article, we describe one such module called the Chemical Component Annotation Tool. This tool uses information from both the Chemical Component Dictionary and Biologically Interesting molecule Reference Dictionary to aid in annotation. Benchmark studies have shown that the Chemical Component Annotation Tool provides significant improvements in processing efficiency and data quality. Database URL: http://wwpdb.org. PMID:24291661

  1. Chemical annotation of small and peptide-like molecules at the Protein Data Bank.

    PubMed

    Young, Jasmine Y; Feng, Zukang; Dimitropoulos, Dimitris; Sala, Raul; Westbrook, John; Zhuravleva, Marina; Shao, Chenghua; Quesada, Martha; Peisach, Ezra; Berman, Helen M

    2013-01-01

    Over the past decade, the number of polymers and their complexes with small molecules in the Protein Data Bank archive (PDB) has continued to increase significantly. To support scientific advancements and ensure the best quality and completeness of the data files over the next 10 years and beyond, the Worldwide PDB partnership that manages the PDB archive is developing a new deposition and annotation system. This system focuses on efficient data capture across all supported experimental methods. The new deposition and annotation system is composed of four major modules that together support all of the processing requirements for a PDB entry. In this article, we describe one such module called the Chemical Component Annotation Tool. This tool uses information from both the Chemical Component Dictionary and Biologically Interesting molecule Reference Dictionary to aid in annotation. Benchmark studies have shown that the Chemical Component Annotation Tool provides significant improvements in processing efficiency and data quality. Database URL: http://wwpdb.org.

  2. The National Clinical Database as an Initiative for Quality Improvement in Japan

    PubMed Central

    Murakami, Arata; Hirata, Yasutaka; Motomura, Noboru; Miyata, Hiroaki; Iwanaka, Tadashi; Takamoto, Shinichi

    2014-01-01

    The JCVSD (Japan Cardiovascular Surgery Database) was organized in 2000 to improve the quality of cardiovascular surgery in Japan. Web-based data harvesting on adult cardiac surgery was started (Japan Adult Cardiovascular Surgery Database, JACVSD) in 2001, and on congenital heart surgery (Japan Congenital Cardiovascular Surgery Database, JCCVSD) in 2008. Both databases grew to become national databases by the end of 2013. This was influenced by the success of the Society for Thoracic Surgeons’ National Database, which contains comparable input items. In 2011, the Japanese Board of Cardiovascular Surgery announced that the JACVSD and JCCVSD data are to be used for board certification, which improved the quality of the first paperless and web-based board certification review undertaken in 2013. These changes led to a further step. In 2011, the National Clinical Database (NCD) was organized to investigate the feasibility of clinical databases in other medical fields, especially surgery. In the NCD, the board certification system of the Japan Surgical Society, the basic association of surgery was set as the first level in the hierarchy of specialties, and nine associations and six board certification systems were set at the second level as subspecialties. The NCD grew rapidly, and now covers 95% of total surgical procedures. The participating associations will release or have released risk models, and studies that use ‘big data’ from these databases have been published. The national databases have contributed to evidence-based medicine, to the accountability of medical professionals, and to quality assessment and quality improvement of surgery in Japan. PMID:25346898

  3. An improved FORTRAN 77 recombinant DNA database management system with graphic extensions in GKS.

    PubMed

    Van Rompuy, L L; Lesage, C; Vanderhaegen, M E; Telemans, M P; Zabeau, M F

    1986-12-01

    We have improved an existing clone database management system written in FORTRAN 77 and adapted it to our software environment. Improvements are that the database can be interrogated for any type of information, not just keywords. Also, recombinant DNA constructions can be represented in a simplified 'shorthand', whereafter a program assembles the full nucleotide sequence from the contributing fragments, which may be obtained from nucleotide sequence databases. Another improvement is the replacement of the database manager by programs, running in batch to maintain the databank and verify its consistency automatically. Finally, graphic extensions are written in Graphical Kernel System, to draw linear and circular restriction maps of recombinants. Besides restriction sites, recombinant features can be presented from the feature lines of recombinant database entries, or from the feature tables of nucleotide databases. The clone database management system is fully integrated into the sequence analysis software package from the Pasteur Institute, Paris, and is made accessible through the same menu. As a result, recombinant DNA sequences can directly be analysed by the sequence analysis programs.

  4. eggNOG 4.5: a hierarchical orthology framework with improved functional annotations for eukaryotic, prokaryotic and viral sequences.

    PubMed

    Huerta-Cepas, Jaime; Szklarczyk, Damian; Forslund, Kristoffer; Cook, Helen; Heller, Davide; Walter, Mathias C; Rattei, Thomas; Mende, Daniel R; Sunagawa, Shinichi; Kuhn, Michael; Jensen, Lars Juhl; von Mering, Christian; Bork, Peer

    2016-01-01

    eggNOG is a public resource that provides Orthologous Groups (OGs) of proteins at different taxonomic levels, each with integrated and summarized functional annotations. Developments since the latest public release include changes to the algorithm for creating OGs across taxonomic levels, making nested groups hierarchically consistent. This allows for a better propagation of functional terms across nested OGs and led to the novel annotation of 95 890 previously uncharacterized OGs, increasing overall annotation coverage from 67% to 72%. The functional annotations of OGs have been expanded to also provide Gene Ontology terms, KEGG pathways and SMART/Pfam domains for each group. Moreover, eggNOG now provides pairwise orthology relationships within OGs based on analysis of phylogenetic trees. We have also incorporated a framework for quickly mapping novel sequences to OGs based on precomputed HMM profiles. Finally, eggNOG version 4.5 incorporates a novel data set spanning 2605 viral OGs, covering 5228 proteins from 352 viral proteomes. All data are accessible for bulk downloading, as a web-service, and through a completely redesigned web interface. The new access points provide faster searches and a number of new browsing and visualization capabilities, facilitating the needs of both experts and less experienced users. eggNOG v4.5 is available at http://eggnog.embl.de. PMID:26582926

  5. eggNOG 4.5: a hierarchical orthology framework with improved functional annotations for eukaryotic, prokaryotic and viral sequences

    PubMed Central

    Huerta-Cepas, Jaime; Szklarczyk, Damian; Forslund, Kristoffer; Cook, Helen; Heller, Davide; Walter, Mathias C.; Rattei, Thomas; Mende, Daniel R.; Sunagawa, Shinichi; Kuhn, Michael; Jensen, Lars Juhl; von Mering, Christian; Bork, Peer

    2016-01-01

    eggNOG is a public resource that provides Orthologous Groups (OGs) of proteins at different taxonomic levels, each with integrated and summarized functional annotations. Developments since the latest public release include changes to the algorithm for creating OGs across taxonomic levels, making nested groups hierarchically consistent. This allows for a better propagation of functional terms across nested OGs and led to the novel annotation of 95 890 previously uncharacterized OGs, increasing overall annotation coverage from 67% to 72%. The functional annotations of OGs have been expanded to also provide Gene Ontology terms, KEGG pathways and SMART/Pfam domains for each group. Moreover, eggNOG now provides pairwise orthology relationships within OGs based on analysis of phylogenetic trees. We have also incorporated a framework for quickly mapping novel sequences to OGs based on precomputed HMM profiles. Finally, eggNOG version 4.5 incorporates a novel data set spanning 2605 viral OGs, covering 5228 proteins from 352 viral proteomes. All data are accessible for bulk downloading, as a web-service, and through a completely redesigned web interface. The new access points provide faster searches and a number of new browsing and visualization capabilities, facilitating the needs of both experts and less experienced users. eggNOG v4.5 is available at http://eggnog.embl.de. PMID:26582926

  6. eggNOG 4.5: a hierarchical orthology framework with improved functional annotations for eukaryotic, prokaryotic and viral sequences.

    PubMed

    Huerta-Cepas, Jaime; Szklarczyk, Damian; Forslund, Kristoffer; Cook, Helen; Heller, Davide; Walter, Mathias C; Rattei, Thomas; Mende, Daniel R; Sunagawa, Shinichi; Kuhn, Michael; Jensen, Lars Juhl; von Mering, Christian; Bork, Peer

    2016-01-01

    eggNOG is a public resource that provides Orthologous Groups (OGs) of proteins at different taxonomic levels, each with integrated and summarized functional annotations. Developments since the latest public release include changes to the algorithm for creating OGs across taxonomic levels, making nested groups hierarchically consistent. This allows for a better propagation of functional terms across nested OGs and led to the novel annotation of 95 890 previously uncharacterized OGs, increasing overall annotation coverage from 67% to 72%. The functional annotations of OGs have been expanded to also provide Gene Ontology terms, KEGG pathways and SMART/Pfam domains for each group. Moreover, eggNOG now provides pairwise orthology relationships within OGs based on analysis of phylogenetic trees. We have also incorporated a framework for quickly mapping novel sequences to OGs based on precomputed HMM profiles. Finally, eggNOG version 4.5 incorporates a novel data set spanning 2605 viral OGs, covering 5228 proteins from 352 viral proteomes. All data are accessible for bulk downloading, as a web-service, and through a completely redesigned web interface. The new access points provide faster searches and a number of new browsing and visualization capabilities, facilitating the needs of both experts and less experienced users. eggNOG v4.5 is available at http://eggnog.embl.de.

  7. PolyQ 2.0: an improved version of PolyQ, a database of human polyglutamine proteins.

    PubMed

    Li, Chen; Nagel, Jeremy; Androulakis, Steve; Song, Jiangning; Buckle, Ashley M

    2016-01-01

    Proteins with expanded polyglutamine (polyQ) repeats are involved in human neurodegenerative diseases, via a gain-of-function mechanism of neuronal toxicity involving protein conformational changes that result in the formation and deposition of β-sheet-rich aggregates. Aggregation is dependent on the context and properties of the host protein, such as domain context and location of the repeat tract. In order to explore this relationship in greater detail, here we describe PolyQ 2.0, an updated database that provides a comprehensive knowledgebase for human polyQ proteins. Compared with the previous PolyQ database, our new database provides a variety of substantial updates including detailed biological annotations and search options. Biological annotations in terms of domain context information, protein structural and functional annotation, single point mutations, predicted disordered regions, protein-protein interaction partners, metabolic/signaling pathways, post-translational modification sites and evolutionary information are made available. Several new database functionalities have also been provided, including search using multiple/combinatory keywords, and submission of new data entries. Also, several third-party plug-ins are employed to enhance data visualization in PolyQ 2.0. In PolyQ 2.0 the proteins are reclassified into 3 new categories and contain 9 reviewed disease-associated polyQ proteins, 105 reviewed non-disease polyQ proteins and 146 un-reviewed polyQ proteins (reviewed by UniProt curators). We envisage that this updated database will be a useful resource for functional and structural investigation of human polyQ proteins. Database URL: http://lightning.med.monash.edu/polyq2/.

  8. PolyQ 2.0: an improved version of PolyQ, a database of human polyglutamine proteins.

    PubMed

    Li, Chen; Nagel, Jeremy; Androulakis, Steve; Song, Jiangning; Buckle, Ashley M

    2016-01-01

    Proteins with expanded polyglutamine (polyQ) repeats are involved in human neurodegenerative diseases, via a gain-of-function mechanism of neuronal toxicity involving protein conformational changes that result in the formation and deposition of β-sheet-rich aggregates. Aggregation is dependent on the context and properties of the host protein, such as domain context and location of the repeat tract. In order to explore this relationship in greater detail, here we describe PolyQ 2.0, an updated database that provides a comprehensive knowledgebase for human polyQ proteins. Compared with the previous PolyQ database, our new database provides a variety of substantial updates including detailed biological annotations and search options. Biological annotations in terms of domain context information, protein structural and functional annotation, single point mutations, predicted disordered regions, protein-protein interaction partners, metabolic/signaling pathways, post-translational modification sites and evolutionary information are made available. Several new database functionalities have also been provided, including search using multiple/combinatory keywords, and submission of new data entries. Also, several third-party plug-ins are employed to enhance data visualization in PolyQ 2.0. In PolyQ 2.0 the proteins are reclassified into 3 new categories and contain 9 reviewed disease-associated polyQ proteins, 105 reviewed non-disease polyQ proteins and 146 un-reviewed polyQ proteins (reviewed by UniProt curators). We envisage that this updated database will be a useful resource for functional and structural investigation of human polyQ proteins. Database URL: http://lightning.med.monash.edu/polyq2/. PMID:26980520

  9. Improved white spruce (Picea glauca) genome assemblies and annotation of large gene families of conifer terpenoid and phenolic defense metabolism.

    PubMed

    Warren, René L; Keeling, Christopher I; Yuen, Macaire Man Saint; Raymond, Anthony; Taylor, Greg A; Vandervalk, Benjamin P; Mohamadi, Hamid; Paulino, Daniel; Chiu, Readman; Jackman, Shaun D; Robertson, Gordon; Yang, Chen; Boyle, Brian; Hoffmann, Margarete; Weigel, Detlef; Nelson, David R; Ritland, Carol; Isabel, Nathalie; Jaquish, Barry; Yanchuk, Alvin; Bousquet, Jean; Jones, Steven J M; MacKay, John; Birol, Inanc; Bohlmann, Joerg

    2015-07-01

    White spruce (Picea glauca), a gymnosperm tree, has been established as one of the models for conifer genomics. We describe the draft genome assemblies of two white spruce genotypes, PG29 and WS77111, innovative tools for the assembly of very large genomes, and the conifer genomics resources developed in this process. The two white spruce genotypes originate from distant geographic regions of western (PG29) and eastern (WS77111) North America, and represent elite trees in two Canadian tree-breeding programs. We present an update (V3 and V4) for a previously reported PG29 V2 draft genome assembly and introduce a second white spruce genome assembly for genotype WS77111. Assemblies of the PG29 and WS77111 genomes confirm the reconstructed white spruce genome size in the 20 Gbp range, and show broad synteny. Using the PG29 V3 assembly and additional white spruce genomics and transcriptomics resources, we performed MAKER-P annotation and meticulous expert annotation of very large gene families of conifer defense metabolism, the terpene synthases and cytochrome P450s. We also comprehensively annotated the white spruce mevalonate, methylerythritol phosphate and phenylpropanoid pathways. These analyses highlighted the large extent of gene and pseudogene duplications in a conifer genome, in particular for genes of secondary (i.e. specialized) metabolism, and the potential for gain and loss of function for defense and adaptation. PMID:26017574

  10. Improved white spruce (Picea glauca) genome assemblies and annotation of large gene families of conifer terpenoid and phenolic defense metabolism.

    PubMed

    Warren, René L; Keeling, Christopher I; Yuen, Macaire Man Saint; Raymond, Anthony; Taylor, Greg A; Vandervalk, Benjamin P; Mohamadi, Hamid; Paulino, Daniel; Chiu, Readman; Jackman, Shaun D; Robertson, Gordon; Yang, Chen; Boyle, Brian; Hoffmann, Margarete; Weigel, Detlef; Nelson, David R; Ritland, Carol; Isabel, Nathalie; Jaquish, Barry; Yanchuk, Alvin; Bousquet, Jean; Jones, Steven J M; MacKay, John; Birol, Inanc; Bohlmann, Joerg

    2015-07-01

    White spruce (Picea glauca), a gymnosperm tree, has been established as one of the models for conifer genomics. We describe the draft genome assemblies of two white spruce genotypes, PG29 and WS77111, innovative tools for the assembly of very large genomes, and the conifer genomics resources developed in this process. The two white spruce genotypes originate from distant geographic regions of western (PG29) and eastern (WS77111) North America, and represent elite trees in two Canadian tree-breeding programs. We present an update (V3 and V4) for a previously reported PG29 V2 draft genome assembly and introduce a second white spruce genome assembly for genotype WS77111. Assemblies of the PG29 and WS77111 genomes confirm the reconstructed white spruce genome size in the 20 Gbp range, and show broad synteny. Using the PG29 V3 assembly and additional white spruce genomics and transcriptomics resources, we performed MAKER-P annotation and meticulous expert annotation of very large gene families of conifer defense metabolism, the terpene synthases and cytochrome P450s. We also comprehensively annotated the white spruce mevalonate, methylerythritol phosphate and phenylpropanoid pathways. These analyses highlighted the large extent of gene and pseudogene duplications in a conifer genome, in particular for genes of secondary (i.e. specialized) metabolism, and the potential for gain and loss of function for defense and adaptation.

  11. Ranking biomedical annotations with annotator's semantic relevancy.

    PubMed

    Wu, Aihua

    2014-01-01

    Biomedical annotation is a common and affective artifact for researchers to discuss, show opinion, and share discoveries. It becomes increasing popular in many online research communities, and implies much useful information. Ranking biomedical annotations is a critical problem for data user to efficiently get information. As the annotator's knowledge about the annotated entity normally determines quality of the annotations, we evaluate the knowledge, that is, semantic relationship between them, in two ways. The first is extracting relational information from credible websites by mining association rules between an annotator and a biomedical entity. The second way is frequent pattern mining from historical annotations, which reveals common features of biomedical entities that an annotator can annotate with high quality. We propose a weighted and concept-extended RDF model to represent an annotator, a biomedical entity, and their background attributes and merge information from the two ways as the context of an annotator. Based on that, we present a method to rank the annotations by evaluating their correctness according to user's vote and the semantic relevancy between the annotator and the annotated entity. The experimental results show that the approach is applicable and efficient even when data set is large. PMID:24899918

  12. Ranking Biomedical Annotations with Annotator's Semantic Relevancy

    PubMed Central

    2014-01-01

    Biomedical annotation is a common and affective artifact for researchers to discuss, show opinion, and share discoveries. It becomes increasing popular in many online research communities, and implies much useful information. Ranking biomedical annotations is a critical problem for data user to efficiently get information. As the annotator's knowledge about the annotated entity normally determines quality of the annotations, we evaluate the knowledge, that is, semantic relationship between them, in two ways. The first is extracting relational information from credible websites by mining association rules between an annotator and a biomedical entity. The second way is frequent pattern mining from historical annotations, which reveals common features of biomedical entities that an annotator can annotate with high quality. We propose a weighted and concept-extended RDF model to represent an annotator, a biomedical entity, and their background attributes and merge information from the two ways as the context of an annotator. Based on that, we present a method to rank the annotations by evaluating their correctness according to user's vote and the semantic relevancy between the annotator and the annotated entity. The experimental results show that the approach is applicable and efficient even when data set is large. PMID:24899918

  13. UCSC Data Integrator and Variant Annotation Integrator

    PubMed Central

    Hinrichs, Angie S.; Raney, Brian J.; Speir, Matthew L.; Rhead, Brooke; Casper, Jonathan; Karolchik, Donna; Kuhn, Robert M.; Rosenbloom, Kate R.; Zweig, Ann S.; Haussler, David; Kent, W. James

    2016-01-01

    Summary: Two new tools on the UCSC Genome Browser web site provide improved ways of combining information from multiple datasets, optionally including the user's own custom track data and/or data from track hubs. The Data Integrator combines columns from multiple data tracks, showing all items from the first track along with overlapping items from the other tracks. The Variant Annotation Integrator is tailored to adding functional annotations to variant calls; it offers a more restricted set of underlying data tracks but adds predictions of each variant's consequences for any overlapping or nearby gene transcript. When available, it optionally adds additional annotations including effect prediction scores from dbNSFP for missense mutations, ENCODE regulatory summary tracks and conservation scores. Availability and implementation: The web tools are freely available at http://genome.ucsc.edu/ and the underlying database is available for download at http://hgdownload.cse.ucsc.edu/. The software (written in C and Javascript) is available from https://genome-store.ucsc.edu/ and is freely available for academic and non-profit usage; commercial users must obtain a license. Contact: angie@soe.ucsc.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:26740527

  14. Towards a Library of Standard Operating Procedures (SOPs) for (meta)genomic annotation

    SciTech Connect

    Kyrpides, Nikos; Angiuoli, Samuel V.; Cochrane, Guy; Field, Dawn; Garrity, George; Gussman, Aaron; Kodira, Chinnappa D.; Klimke, William; Kyrpides, Nikos; Madupu, Ramana; Markowitz, Victor; Tatusova, Tatiana; Thomson, Nick; White, Owen

    2008-04-01

    Genome annotations describe the features of genomes and accompany sequences in genome databases. The methodologies used to generate genome annotation are diverse and typically vary amongst groups. Descriptions of the annotation procedure are helpful in interpreting genome annotation data. Standard Operating Procedures (SOPs) for genome annotation describe the processes that generate genome annotations. Some groups are currently documenting procedures but standards are lacking for structure and content of annotation SOPs. In addition, there is no central repository to store and disseminate procedures and protocols for genome annotation. We highlight the importance of SOPs for genome annotation and endorse a central online repository of SOPs.

  15. Improvements to the Magnetics Information Consortium (MagIC) Paleo and Rock Magnetic Database

    NASA Astrophysics Data System (ADS)

    Jarboe, N.; Minnett, R.; Tauxe, L.; Koppers, A. A. P.; Constable, C.; Jonestrask, L.

    2015-12-01

    The Magnetic Information Consortium (MagIC) database (http://earthref.org/MagIC/) continues to improve the ease of data uploading and editing, the creation of complex searches, data visualization, and data downloads for the paleomagnetic, geomagnetic, and rock magnetic communities. Online data editing is now available and the need for proprietary spreadsheet software is therefore entirely negated. The data owner can change values in the database or delete entries through an HTML 5 web interface that resembles typical spreadsheets in behavior and uses. Additive uploading now allows for additions to data sets to be uploaded with a simple drag and drop interface. Searching the database has improved with the addition of more sophisticated search parameters and with the facility to use them in complex combinations. A comprehensive summary view of a search result has been added for increased quick data comprehension while a raw data view is available if one desires to see all data columns as stored in the database. Data visualization plots (ARAI, equal area, demagnetization, Zijderveld, etc.) are presented with the data when appropriate to aid the user in understanding the dataset. MagIC data associated with individual contributions or from online searches may be downloaded in the tab delimited MagIC text file format for susbsequent offline use and analysis. With input from the paleomagnetic, geomagnetic, and rock magnetic communities, the MagIC database will continue to improve as a data warehouse and resource.

  16. Adopting a corporate perspective on databases. Improving support for research and decision making.

    PubMed

    Meistrell, M; Schlehuber, C

    1996-03-01

    The Veterans Health Administration (VHA) is at the forefront of designing and managing health care information systems that accommodate the needs of clinicians, researchers, and administrators at all levels. Rather than using one single-site, centralized corporate database VHA has constructed several large databases with different configurations to meet the needs of users with different perspectives. The largest VHA database is the Decentralized Hospital Computer Program (DHCP), a multisite, distributed data system that uses decoupled hospital databases. The centralization of DHCP policy has promoted data coherence, whereas the decentralization of DHCP management has permitted system development to be done with maximum relevance to the users'local practices. A more recently developed VHA data system, the Event Driven Reporting system (EDR), uses multiple, highly coupled databases to provide workload data at facility, regional, and national levels. The EDR automatically posts a subset of DHCP data to local and national VHA management. The development of the EDR illustrates how adoption of a corporate perspective can offer significant database improvements at reasonable cost and with modest impact on the legacy system. PMID:8598692

  17. The Protein Information Resource: an integrated public resource of functional annotation of proteins

    PubMed Central

    Wu, Cathy H.; Huang, Hongzhan; Arminski, Leslie; Castro-Alvear, Jorge; Chen, Yongxing; Hu, Zhang-Zhi; Ledley, Robert S.; Lewis, Kali C.; Mewes, Hans-Werner; Orcutt, Bruce C.; Suzek, Baris E.; Tsugita, Akira; Vinayaka, C. R.; Yeh, Lai-Su L.; Zhang, Jian; Barker, Winona C.

    2002-01-01

    The Protein Information Resource (PIR) serves as an integrated public resource of functional annotation of protein data to support genomic/proteomic research and scientific discovery. The PIR, in collaboration with the Munich Information Center for Protein Sequences (MIPS) and the Japan International Protein Information Database (JIPID), produces the PIR-International Protein Sequence Database (PSD), the major annotated protein sequence database in the public domain, containing about 250 000 proteins. To improve protein annotation and the coverage of experimentally validated data, a bibliography submission system is developed for scientists to submit, categorize and retrieve literature information. Comprehensive protein information is available from iProClass, which includes family classification at the superfamily, domain and motif levels, structural and functional features of proteins, as well as cross-references to over 40 biological databases. To provide timely and comprehensive protein data with source attribution, we have introduced a non-redundant reference protein database, PIR-NREF. The database consists of about 800 000 proteins collected from PIR-PSD, SWISS-PROT, TrEMBL, GenPept, RefSeq and PDB, with composite protein names and literature data. To promote database interoperability, we provide XML data distribution and open database schema, and adopt common ontologies. The PIR web site (http://pir.georgetown.edu/) features data mining and sequence analysis tools for information retrieval and functional identification of proteins based on both sequence and annotation information. The PIR databases and other files are also available by FTP (ftp://nbrfa.georgetown.edu/pir_databases). PMID:11752247

  18. Lessons learned while building the Deepwater Horizon Database: Toward improved data sharing in coastal science

    NASA Astrophysics Data System (ADS)

    Thessen, Anne E.; McGinnis, Sean; North, Elizabeth W.

    2016-02-01

    Process studies and coupled-model validation efforts in geosciences often require integration of multiple data types across time and space. For example, improved prediction of hydrocarbon fate and transport is an important societal need which fundamentally relies upon synthesis of oceanography and hydrocarbon chemistry. Yet, there are no publically accessible databases which integrate these diverse data types in a georeferenced format, nor are there guidelines for developing such a database. The objective of this research was to analyze the process of building one such database to provide baseline information on data sources and data sharing and to document the challenges and solutions that arose during this major undertaking. The resulting Deepwater Horizon Database was approximately 2.4 GB in size and contained over 8 million georeferenced data points collected from industry, government databases, volunteer networks, and individual researchers. The major technical challenges that were overcome were reconciliation of terms, units, and quality flags which were necessary to effectively integrate the disparate data sets. Assembling this database required the development of relationships with individual researchers and data managers which often involved extensive e-mail contacts. The average number of emails exchanged per data set was 7.8. Of the 95 relevant data sets that were discovered, 38 (40%) were obtained, either in whole or in part. Over one third (36%) of the requests for data went unanswered. The majority of responses were received after the first request (64%) and within the first week of the first request (67%). Although fewer than half of the potentially relevant datasets were incorporated into the database, the level of sharing (40%) was high compared to some other disciplines where sharing can be as low as 10%. Our suggestions for building integrated databases include budgeting significant time for e-mail exchanges, being cognizant of the cost versus

  19. Improving Child Outcomes with Data-Based Decision Making: Interpreting and Using Data

    ERIC Educational Resources Information Center

    Gischlar, Karen L.; Hojnoski, Robin L.; Missall, Kristen N.

    2009-01-01

    This article is the third in a series describing the steps in using data-based decision making to inform intervention and, ultimately, improve outcomes for children. Whereas the first two articles describe identifying and measuring important behaviors to target for intervention, the purpose of this article is to describe basic considerations in…

  20. Information Technologies in Public Health Management: A Database on Biocides to Improve Quality of Life

    PubMed Central

    Roman, C; Scripcariu, L; Diaconescu, RM; Grigoriu, A

    2012-01-01

    Background Biocides for prolonging the shelf life of a large variety of materials have been extensively used over the last decades. It has estimated that the worldwide biocide consumption to be about 12.4 billion dollars in 2011, and is expected to increase in 2012. As biocides are substances we get in contact with in our everyday lives, access to this type of information is of paramount importance in order to ensure an appropriate living environment. Consequently, a database where information may be quickly processed, sorted, and easily accessed, according to different search criteria, is the most desirable solution. The main aim of this work was to design and implement a relational database with complete information about biocides used in public health management to improve the quality of life. Methods: Design and implementation of a relational database for biocides, by using the software “phpMyAdmin”. Results: A database, which allows for an efficient collection, storage, and management of information including chemical properties and applications of a large quantity of biocides, as well as its adequate dissemination into the public health environment. Conclusion: The information contained in the database herein presented promotes an adequate use of biocides, by means of information technologies, which in consequence may help achieve important improvement in our quality of life. PMID:23113190

  1. Gene Ontology annotations and resources.

    PubMed

    Blake, J A; Dolan, M; Drabkin, H; Hill, D P; Li, Ni; Sitnikov, D; Bridges, S; Burgess, S; Buza, T; McCarthy, F; Peddinti, D; Pillai, L; Carbon, S; Dietze, H; Ireland, A; Lewis, S E; Mungall, C J; Gaudet, P; Chrisholm, R L; Fey, P; Kibbe, W A; Basu, S; Siegele, D A; McIntosh, B K; Renfro, D P; Zweifel, A E; Hu, J C; Brown, N H; Tweedie, S; Alam-Faruque, Y; Apweiler, R; Auchinchloss, A; Axelsen, K; Bely, B; Blatter, M -C; Bonilla, C; Bouguerleret, L; Boutet, E; Breuza, L; Bridge, A; Chan, W M; Chavali, G; Coudert, E; Dimmer, E; Estreicher, A; Famiglietti, L; Feuermann, M; Gos, A; Gruaz-Gumowski, N; Hieta, R; Hinz, C; Hulo, C; Huntley, R; James, J; Jungo, F; Keller, G; Laiho, K; Legge, D; Lemercier, P; Lieberherr, D; Magrane, M; Martin, M J; Masson, P; Mutowo-Muellenet, P; O'Donovan, C; Pedruzzi, I; Pichler, K; Poggioli, D; Porras Millán, P; Poux, S; Rivoire, C; Roechert, B; Sawford, T; Schneider, M; Stutz, A; Sundaram, S; Tognolli, M; Xenarios, I; Foulgar, R; Lomax, J; Roncaglia, P; Khodiyar, V K; Lovering, R C; Talmud, P J; Chibucos, M; Giglio, M Gwinn; Chang, H -Y; Hunter, S; McAnulla, C; Mitchell, A; Sangrador, A; Stephan, R; Harris, M A; Oliver, S G; Rutherford, K; Wood, V; Bahler, J; Lock, A; Kersey, P J; McDowall, D M; Staines, D M; Dwinell, M; Shimoyama, M; Laulederkind, S; Hayman, T; Wang, S -J; Petri, V; Lowry, T; D'Eustachio, P; Matthews, L; Balakrishnan, R; Binkley, G; Cherry, J M; Costanzo, M C; Dwight, S S; Engel, S R; Fisk, D G; Hitz, B C; Hong, E L; Karra, K; Miyasato, S R; Nash, R S; Park, J; Skrzypek, M S; Weng, S; Wong, E D; Berardini, T Z; Huala, E; Mi, H; Thomas, P D; Chan, J; Kishore, R; Sternberg, P; Van Auken, K; Howe, D; Westerfield, M

    2013-01-01

    The Gene Ontology (GO) Consortium (GOC, http://www.geneontology.org) is a community-based bioinformatics resource that classifies gene product function through the use of structured, controlled vocabularies. Over the past year, the GOC has implemented several processes to increase the quantity, quality and specificity of GO annotations. First, the number of manual, literature-based annotations has grown at an increasing rate. Second, as a result of a new 'phylogenetic annotation' process, manually reviewed, homology-based annotations are becoming available for a broad range of species. Third, the quality of GO annotations has been improved through a streamlined process for, and automated quality checks of, GO annotations deposited by different annotation groups. Fourth, the consistency and correctness of the ontology itself has increased by using automated reasoning tools. Finally, the GO has been expanded not only to cover new areas of biology through focused interaction with experts, but also to capture greater specificity in all areas of the ontology using tools for adding new combinatorial terms. The GOC works closely with other ontology developers to support integrated use of terminologies. The GOC supports its user community through the use of e-mail lists, social media and web-based resources.

  2. Gene Ontology annotations and resources.

    PubMed

    Blake, J A; Dolan, M; Drabkin, H; Hill, D P; Li, Ni; Sitnikov, D; Bridges, S; Burgess, S; Buza, T; McCarthy, F; Peddinti, D; Pillai, L; Carbon, S; Dietze, H; Ireland, A; Lewis, S E; Mungall, C J; Gaudet, P; Chrisholm, R L; Fey, P; Kibbe, W A; Basu, S; Siegele, D A; McIntosh, B K; Renfro, D P; Zweifel, A E; Hu, J C; Brown, N H; Tweedie, S; Alam-Faruque, Y; Apweiler, R; Auchinchloss, A; Axelsen, K; Bely, B; Blatter, M -C; Bonilla, C; Bouguerleret, L; Boutet, E; Breuza, L; Bridge, A; Chan, W M; Chavali, G; Coudert, E; Dimmer, E; Estreicher, A; Famiglietti, L; Feuermann, M; Gos, A; Gruaz-Gumowski, N; Hieta, R; Hinz, C; Hulo, C; Huntley, R; James, J; Jungo, F; Keller, G; Laiho, K; Legge, D; Lemercier, P; Lieberherr, D; Magrane, M; Martin, M J; Masson, P; Mutowo-Muellenet, P; O'Donovan, C; Pedruzzi, I; Pichler, K; Poggioli, D; Porras Millán, P; Poux, S; Rivoire, C; Roechert, B; Sawford, T; Schneider, M; Stutz, A; Sundaram, S; Tognolli, M; Xenarios, I; Foulgar, R; Lomax, J; Roncaglia, P; Khodiyar, V K; Lovering, R C; Talmud, P J; Chibucos, M; Giglio, M Gwinn; Chang, H -Y; Hunter, S; McAnulla, C; Mitchell, A; Sangrador, A; Stephan, R; Harris, M A; Oliver, S G; Rutherford, K; Wood, V; Bahler, J; Lock, A; Kersey, P J; McDowall, D M; Staines, D M; Dwinell, M; Shimoyama, M; Laulederkind, S; Hayman, T; Wang, S -J; Petri, V; Lowry, T; D'Eustachio, P; Matthews, L; Balakrishnan, R; Binkley, G; Cherry, J M; Costanzo, M C; Dwight, S S; Engel, S R; Fisk, D G; Hitz, B C; Hong, E L; Karra, K; Miyasato, S R; Nash, R S; Park, J; Skrzypek, M S; Weng, S; Wong, E D; Berardini, T Z; Huala, E; Mi, H; Thomas, P D; Chan, J; Kishore, R; Sternberg, P; Van Auken, K; Howe, D; Westerfield, M

    2013-01-01

    The Gene Ontology (GO) Consortium (GOC, http://www.geneontology.org) is a community-based bioinformatics resource that classifies gene product function through the use of structured, controlled vocabularies. Over the past year, the GOC has implemented several processes to increase the quantity, quality and specificity of GO annotations. First, the number of manual, literature-based annotations has grown at an increasing rate. Second, as a result of a new 'phylogenetic annotation' process, manually reviewed, homology-based annotations are becoming available for a broad range of species. Third, the quality of GO annotations has been improved through a streamlined process for, and automated quality checks of, GO annotations deposited by different annotation groups. Fourth, the consistency and correctness of the ontology itself has increased by using automated reasoning tools. Finally, the GO has been expanded not only to cover new areas of biology through focused interaction with experts, but also to capture greater specificity in all areas of the ontology using tools for adding new combinatorial terms. The GOC works closely with other ontology developers to support integrated use of terminologies. The GOC supports its user community through the use of e-mail lists, social media and web-based resources. PMID:23161678

  3. Curation of the genome annotation of Pichia pastoris (Komagataella phaffii) CBS7435 from gene level to protein function.

    PubMed

    Valli, Minoska; Tatto, Nadine E; Peymann, Armin; Gruber, Clemens; Landes, Nils; Ekker, Heinz; Thallinger, Gerhard G; Mattanovich, Diethard; Gasser, Brigitte; Graf, Alexandra B

    2016-09-01

    As manually curated and non-automated BLAST analysis of the published Pichia pastoris genome sequences revealed many differences between the gene annotations of the strains GS115 and CBS7435, RNA-Seq analysis, supported by proteomics, was performed to improve the genome annotation. Detailed analysis of sequence alignment and protein domain predictions were made to extend the functional genome annotation to all P. pastoris sequences. This allowed the identification of 492 new ORFs, 4916 hypothetical UTRs and the correction of 341 incorrect ORF predictions, which were mainly due to the presence of upstream ATG or erroneous intron predictions. Moreover, 175 previously erroneously annotated ORFs need to be removed from the annotation. In total, we have annotated 5325 ORFs. Regarding the functionality of those genes, we improved all gene and protein descriptions. Thereby, the percentage of ORFs with functional annotation was increased from 48% to 73%. Furthermore, we defined functional groups, covering 25 biological cellular processes of interest, by grouping all genes that are part of the defined process. All data are presented in the newly launched genome browser and database available at www.pichiagenome.org In summary, we present a wide spectrum of curation of the P. pastoris genome annotation from gene level to protein function. PMID:27388471

  4. Annotating the biomedical literature for the human variome

    PubMed Central

    Verspoor, Karin; Jimeno Yepes, Antonio; Cavedon, Lawrence; McIntosh, Tara; Herten-Crabb, Asha; Thomas, Zoë; Plazzer, John-Paul

    2013-01-01

    This article introduces the Variome Annotation Schema, a schema that aims to capture the core concepts and relations relevant to cataloguing and interpreting human genetic variation and its relationship to disease, as described in the published literature. The schema was inspired by the needs of the database curators of the International Society for Gastrointestinal Hereditary Tumours (InSiGHT) database, but is intended to have application to genetic variation information in a range of diseases. The schema has been applied to a small corpus of full text journal publications on the subject of inherited colorectal cancer. We show that the inter-annotator agreement on annotation of this corpus ranges from 0.78 to 0.95 F-score across different entity types when exact matching is measured, and improves to a minimum F-score of 0.87 when boundary matching is relaxed. Relations show more variability in agreement, but several are reliable, with the highest, cohort-has-size, reaching 0.90 F-score. We also explore the relevance of the schema to the InSiGHT database curation process. The schema and the corpus represent an important new resource for the development of text mining solutions that address relationships among patient cohorts, disease and genetic variation, and therefore, we also discuss the role text mining might play in the curation of information related to the human variome. The corpus is available at http://opennicta.com/home/health/variome. PMID:23584833

  5. CASME II: an improved spontaneous micro-expression database and the baseline evaluation.

    PubMed

    Yan, Wen-Jing; Li, Xiaobai; Wang, Su-Jing; Zhao, Guoying; Liu, Yong-Jin; Chen, Yu-Hsin; Fu, Xiaolan

    2014-01-01

    A robust automatic micro-expression recognition system would have broad applications in national safety, police interrogation, and clinical diagnosis. Developing such a system requires high quality databases with sufficient training samples which are currently not available. We reviewed the previously developed micro-expression databases and built an improved one (CASME II), with higher temporal resolution (200 fps) and spatial resolution (about 280×340 pixels on facial area). We elicited participants' facial expressions in a well-controlled laboratory environment and proper illumination (such as removing light flickering). Among nearly 3000 facial movements, 247 micro-expressions were selected for the database with action units (AUs) and emotions labeled. For baseline evaluation, LBP-TOP and SVM were employed respectively for feature extraction and classifier with the leave-one-subject-out cross-validation method. The best performance is 63.41% for 5-class classification.

  6. CASME II: An Improved Spontaneous Micro-Expression Database and the Baseline Evaluation

    PubMed Central

    Yan, Wen-Jing; Li, Xiaobai; Wang, Su-Jing; Zhao, Guoying; Liu, Yong-Jin; Chen, Yu-Hsin; Fu, Xiaolan

    2014-01-01

    A robust automatic micro-expression recognition system would have broad applications in national safety, police interrogation, and clinical diagnosis. Developing such a system requires high quality databases with sufficient training samples which are currently not available. We reviewed the previously developed micro-expression databases and built an improved one (CASME II), with higher temporal resolution (200 fps) and spatial resolution (about 280×340 pixels on facial area). We elicited participants' facial expressions in a well-controlled laboratory environment and proper illumination (such as removing light flickering). Among nearly 3000 facial movements, 247 micro-expressions were selected for the database with action units (AUs) and emotions labeled. For baseline evaluation, LBP-TOP and SVM were employed respectively for feature extraction and classifier with the leave-one-subject-out cross-validation method. The best performance is 63.41% for 5-class classification. PMID:24475068

  7. Publicly Available Database : Improved Spectral Line Measurements In SDSS DR7 Galaxies

    NASA Astrophysics Data System (ADS)

    Oh, Kyuseok; Sarzi, M.; Schawinski, K.; Yi, S. K.

    2012-01-01

    We present a new database of absorption and emission line measurements based on the Sloan Digital Sky Survey 7th data release for the galaxies within a redshift of 0.2. Our work makes use of the publicly available penalized pixel-fitting(pPXF) and GANDALF codes, aiming to improve the existing measurements for stellar kinematics, the strength of various absorption-line features, and the flux and width of the emissions from different species of ionized gas. The absorption line strengths measured by SDSS pipeline are seriously contaminated by emission fill-in. We effectively separate emission lines from absorption lines. For instance, this work successfully extract [NI] doublet from Mgb and it leads to more realistic result of alpha enhancement on late-type galaxies compared to the previous database. Besides accurately measuring line strengths, the database provides new parameters that are indicative of line strength measurement quality. Users can build a subset of database optimal for their studies using specific cuts in the fitting quality parameters as well as empirical signal-to-noise. Applying these parameters, we found `hidden’ broad-line-region galaxies and they turned out to be Seyfert I nuclei that were not picked up as AGN by SDSS. The database is publicly available at http://gem.yonsei.ac.kr/ossy

  8. Computational algorithms to predict Gene Ontology annotations

    PubMed Central

    2015-01-01

    Background Gene function annotations, which are associations between a gene and a term of a controlled vocabulary describing gene functional features, are of paramount importance in modern biology. Datasets of these annotations, such as the ones provided by the Gene Ontology Consortium, are used to design novel biological experiments and interpret their results. Despite their importance, these sources of information have some known issues. They are incomplete, since biological knowledge is far from being definitive and it rapidly evolves, and some erroneous annotations may be present. Since the curation process of novel annotations is a costly procedure, both in economical and time terms, computational tools that can reliably predict likely annotations, and thus quicken the discovery of new gene annotations, are very useful. Methods We used a set of computational algorithms and weighting schemes to infer novel gene annotations from a set of known ones. We used the latent semantic analysis approach, implementing two popular algorithms (Latent Semantic Indexing and Probabilistic Latent Semantic Analysis) and propose a novel method, the Semantic IMproved Latent Semantic Analysis, which adds a clustering step on the set of considered genes. Furthermore, we propose the improvement of these algorithms by weighting the annotations in the input set. Results We tested our methods and their weighted variants on the Gene Ontology annotation sets of three model organism genes (Bos taurus, Danio rerio and Drosophila melanogaster ). The methods showed their ability in predicting novel gene annotations and the weighting procedures demonstrated to lead to a valuable improvement, although the obtained results vary according to the dimension of the input annotation set and the considered algorithm. Conclusions Out of the three considered methods, the Semantic IMproved Latent Semantic Analysis is the one that provides better results. In particular, when coupled with a proper

  9. TriAnnot: A Versatile and High Performance Pipeline for the Automated Annotation of Plant Genomes

    PubMed Central

    Leroy, Philippe; Guilhot, Nicolas; Sakai, Hiroaki; Bernard, Aurélien; Choulet, Frédéric; Theil, Sébastien; Reboux, Sébastien; Amano, Naoki; Flutre, Timothée; Pelegrin, Céline; Ohyanagi, Hajime; Seidel, Michael; Giacomoni, Franck; Reichstadt, Mathieu; Alaux, Michael; Gicquello, Emmanuelle; Legeai, Fabrice; Cerutti, Lorenzo; Numa, Hisataka; Tanaka, Tsuyoshi; Mayer, Klaus; Itoh, Takeshi; Quesneville, Hadi; Feuillet, Catherine

    2012-01-01

    In support of the international effort to obtain a reference sequence of the bread wheat genome and to provide plant communities dealing with large and complex genomes with a versatile, easy-to-use online automated tool for annotation, we have developed the TriAnnot pipeline. Its modular architecture allows for the annotation and masking of transposable elements, the structural, and functional annotation of protein-coding genes with an evidence-based quality indexing, and the identification of conserved non-coding sequences and molecular markers. The TriAnnot pipeline is parallelized on a 712 CPU computing cluster that can run a 1-Gb sequence annotation in less than 5 days. It is accessible through a web interface for small scale analyses or through a server for large scale annotations. The performance of TriAnnot was evaluated in terms of sensitivity, specificity, and general fitness using curated reference sequence sets from rice and wheat. In less than 8 h, TriAnnot was able to predict more than 83% of the 3,748 CDS from rice chromosome 1 with a fitness of 67.4%. On a set of 12 reference Mb-sized contigs from wheat chromosome 3B, TriAnnot predicted and annotated 93.3% of the genes among which 54% were perfectly identified in accordance with the reference annotation. It also allowed the curation of 12 genes based on new biological evidences, increasing the percentage of perfect gene prediction to 63%. TriAnnot systematically showed a higher fitness than other annotation pipelines that are not improved for wheat. As it is easily adaptable to the annotation of other plant genomes, TriAnnot should become a useful resource for the annotation of large and complex genomes in the future. PMID:22645565

  10. Recent improvements of the ProDom database of protein domain families.

    PubMed

    Corpet, F; Gouzy, J; Kahn, D

    1999-01-01

    The ProDom database contains protein domain families generated from the SWISS-PROT database by automated sequence comparisons. The current version was built with a new improved procedure based on recursive PSI-BLAST homology searches. ProDom can be searched on the World Wide Web to study domain arrangements within either known families or new proteins, with the help of a user-friendly graphical interface (http://www.toulouse.inra.fr/prodom.html). Recent improvements to the ProDom server include: ProDom queries under the SRS Sequence Retrieval System; links to the PredictProtein server; phylogenetic trees and condensed multiple alignments for a better representation of large domain families, with zooming in and out capabilities. In addition, a similar server was set up to display the outcome of whole genome domain analysis as applied to 17 completed microbial genomes (http://www.toulouse.inra.fr/prodomCG.html ).

  11. Learning from decoys to improve the sensitivity and specificity of proteomics database search results.

    PubMed

    Yadav, Amit Kumar; Kumar, Dhirendra; Dash, Debasis

    2012-01-01

    The statistical validation of database search results is a complex issue in bottom-up proteomics. The correct and incorrect peptide spectrum match (PSM) scores overlap significantly, making an accurate assessment of true peptide matches challenging. Since the complete separation between the true and false hits is practically never achieved, there is need for better methods and rescoring algorithms to improve upon the primary database search results. Here we describe the calibration and False Discovery Rate (FDR) estimation of database search scores through a dynamic FDR calculation method, FlexiFDR, which increases both the sensitivity and specificity of search results. Modelling a simple linear regression on the decoy hits for different charge states, the method maximized the number of true positives and reduced the number of false negatives in several standard datasets of varying complexity (18-mix, 49-mix, 200-mix) and few complex datasets (E. coli and Yeast) obtained from a wide variety of MS platforms. The net positive gain for correct spectral and peptide identifications was up to 14.81% and 6.2% respectively. The approach is applicable to different search methodologies--separate as well as concatenated database search, high mass accuracy, and semi-tryptic and modification searches. FlexiFDR was also applied to Mascot results and showed better performance than before. We have shown that appropriate threshold learnt from decoys, can be very effective in improving the database search results. FlexiFDR adapts itself to different instruments, data types and MS platforms. It learns from the decoy hits and sets a flexible threshold that automatically aligns itself to the underlying variables of data quality and size.

  12. Dictionary-driven protein annotation.

    PubMed

    Rigoutsos, Isidore; Huynh, Tien; Floratos, Aris; Parida, Laxmi; Platt, Daniel

    2002-09-01

    Computational methods seeking to automatically determine the properties (functional, structural, physicochemical, etc.) of a protein directly from the sequence have long been the focus of numerous research groups. With the advent of advanced sequencing methods and systems, the number of amino acid sequences that are being deposited in the public databases has been increasing steadily. This has in turn generated a renewed demand for automated approaches that can annotate individual sequences and complete genomes quickly, exhaustively and objectively. In this paper, we present one such approach that is centered around and exploits the Bio-Dictionary, a collection of amino acid patterns that completely covers the natural sequence space and can capture functional and structural signals that have been reused during evolution, within and across protein families. Our annotation approach also makes use of a weighted, position-specific scoring scheme that is unaffected by the over-representation of well-conserved proteins and protein fragments in the databases used. For a given query sequence, the method permits one to determine, in a single pass, the following: local and global similarities between the query and any protein already present in a public database; the likeness of the query to all available archaeal/ bacterial/eukaryotic/viral sequences in the database as a function of amino acid position within the query; the character of secondary structure of the query as a function of amino acid position within the query; the cytoplasmic, transmembrane or extracellular behavior of the query; the nature and position of binding domains, active sites, post-translationally modified sites, signal peptides, etc. In terms of performance, the proposed method is exhaustive, objective and allows for the rapid annotation of individual sequences and full genomes. Annotation examples are presented and discussed in Results, including individual queries and complete genomes that were

  13. Computer systems for annotation of single molecule fragments

    DOEpatents

    Schwartz, David Charles; Severin, Jessica

    2016-07-19

    There are provided computer systems for visualizing and annotating single molecule images. Annotation systems in accordance with this disclosure allow a user to mark and annotate single molecules of interest and their restriction enzyme cut sites thereby determining the restriction fragments of single nucleic acid molecules. The markings and annotations may be automatically generated by the system in certain embodiments and they may be overlaid translucently onto the single molecule images. An image caching system may be implemented in the computer annotation systems to reduce image processing time. The annotation systems include one or more connectors connecting to one or more databases capable of storing single molecule data as well as other biomedical data. Such diverse array of data can be retrieved and used to validate the markings and annotations. The annotation systems may be implemented and deployed over a computer network. They may be ergonomically optimized to facilitate user interactions.

  14. Validating Annotations for Uncharacterized Proteins in Shewanella oneidensis

    PubMed Central

    Louie, Brenton; Tarczy-Hornoch, Peter; Higdon, Roger

    2008-01-01

    Abstract Proteins of unknown function are a barrier to our understanding of molecular biology. Assigning function to these “uncharacterized” proteins is imperative, but challenging. The usual approach is similarity searches using annotation databases, which are useful for predicting function. However, since the performance of these databases on uncharacterized proteins is basically unknown, the accuracy of their predictions is suspect, making annotation difficult. To address this challenge, we developed a benchmark annotation dataset of 30 proteins in Shewanella oneidensis. The proteins in the dataset were originally uncharacterized after the initial annotation of the S. oneidensis proteome in 2002. In the intervening 5 years, the accumulation of new experimental evidence has enabled specific functions to be predicted. We utilized this benchmark dataset to evaluate several commonly utilized annotation databases. According to our criteria, six annotation databases accurately predicted functions for at least 60% of proteins in our dataset. Two of these six even had a “conditional accuracy” of 90%. Conditional accuracy is another evaluation metric we developed which excludes results from databases where no function was predicted. Also, 27 of the 30 proteins' functions were correctly predicted by at least one database. These represent one of the first performance evaluations of annotation databases on uncharacterized proteins. Our evaluation indicates that these databases readily incorporate new information and are accurate in predicting functions for uncharacterized proteins, provided that experimental function evidence exists. PMID:18687039

  15. Support Vector Machines for Improved Peptide Identification from Tandem Mass Spectrometry Database Search

    SciTech Connect

    Webb-Robertson, Bobbie-Jo M.

    2009-05-06

    Accurate identification of peptides is a current challenge in mass spectrometry (MS) based proteomics. The standard approach uses a search routine to compare tandem mass spectra to a database of peptides associated with the target organism. These database search routines yield multiple metrics associated with the quality of the mapping of the experimental spectrum to the theoretical spectrum of a peptide. The structure of these results make separating correct from false identifications difficult and has created a false identification problem. Statistical confidence scores are an approach to battle this false positive problem that has led to significant improvements in peptide identification. We have shown that machine learning, specifically support vector machine (SVM), is an effective approach to separating true peptide identifications from false ones. The SVM-based peptide statistical scoring method transforms a peptide into a vector representation based on database search metrics to train and validate the SVM. In practice, following the database search routine, a peptides is denoted in its vector representation and the SVM generates a single statistical score that is then used to classify presence or absence in the sample

  16. An extended bioreaction database that significantly improves reconstruction and analysis of genome-scale metabolic networks.

    PubMed

    Stelzer, Michael; Sun, Jibin; Kamphans, Tom; Fekete, Sándor P; Zeng, An-Ping

    2011-11-01

    The bioreaction database established by Ma and Zeng (Bioinformatics, 2003, 19, 270-277) for in silico reconstruction of genome-scale metabolic networks has been widely used. Based on more recent information in the reference databases KEGG LIGAND and Brenda, we upgrade the bioreaction database in this work by almost doubling the number of reactions from 3565 to 6851. Over 70% of the reactions have been manually updated/revised in terms of reversibility, reactant pairs, currency metabolites and error correction. For the first time, 41 spontaneous sugar mutarotation reactions are introduced into the biochemical database. The upgrade significantly improves the reconstruction of genome scale metabolic networks. Many gaps or missing biochemical links can be recovered, as exemplified with three model organisms Homo sapiens, Aspergillus niger, and Escherichia coli. The topological parameters of the constructed networks were also largely affected, however, the overall network structure remains scale-free. Furthermore, we consider the problem of computing biologically feasible shortest paths in reconstructed metabolic networks. We show that these paths are hard to compute and present solutions to find such paths in networks of small and medium size.

  17. The UCSC Genome Browser database: 2014 update.

    PubMed

    Karolchik, Donna; Barber, Galt P; Casper, Jonathan; Clawson, Hiram; Cline, Melissa S; Diekhans, Mark; Dreszer, Timothy R; Fujita, Pauline A; Guruvadoo, Luvina; Haeussler, Maximilian; Harte, Rachel A; Heitner, Steve; Hinrichs, Angie S; Learned, Katrina; Lee, Brian T; Li, Chin H; Raney, Brian J; Rhead, Brooke; Rosenbloom, Kate R; Sloan, Cricket A; Speir, Matthew L; Zweig, Ann S; Haussler, David; Kuhn, Robert M; Kent, W James

    2014-01-01

    The University of California Santa Cruz (UCSC) Genome Browser (http://genome.ucsc.edu) offers online public access to a growing database of genomic sequence and annotations for a large collection of organisms, primarily vertebrates, with an emphasis on the human and mouse genomes. The Browser's web-based tools provide an integrated environment for visualizing, comparing, analysing and sharing both publicly available and user-generated genomic data sets. As of September 2013, the database contained genomic sequence and a basic set of annotation 'tracks' for ∼90 organisms. Significant new annotations include a 60-species multiple alignment conservation track on the mouse, updated UCSC Genes tracks for human and mouse, and several new sets of variation and ENCODE data. New software tools include a Variant Annotation Integrator that returns predicted functional effects of a set of variants uploaded as a custom track, an extension to UCSC Genes that displays haplotype alleles for protein-coding genes and an expansion of data hubs that includes the capability to display remotely hosted user-provided assembly sequence in addition to annotation data. To improve European access, we have added a Genome Browser mirror (http://genome-euro.ucsc.edu) hosted at Bielefeld University in Germany.

  18. The UCSC Genome Browser database: 2014 update

    PubMed Central

    Karolchik, Donna; Barber, Galt P.; Casper, Jonathan; Clawson, Hiram; Cline, Melissa S.; Diekhans, Mark; Dreszer, Timothy R.; Fujita, Pauline A.; Guruvadoo, Luvina; Haeussler, Maximilian; Harte, Rachel A.; Heitner, Steve; Hinrichs, Angie S.; Learned, Katrina; Lee, Brian T.; Li, Chin H.; Raney, Brian J.; Rhead, Brooke; Rosenbloom, Kate R.; Sloan, Cricket A.; Speir, Matthew L.; Zweig, Ann S.; Haussler, David; Kuhn, Robert M.; Kent, W. James

    2014-01-01

    The University of California Santa Cruz (UCSC) Genome Browser (http://genome.ucsc.edu) offers online public access to a growing database of genomic sequence and annotations for a large collection of organisms, primarily vertebrates, with an emphasis on the human and mouse genomes. The Browser’s web-based tools provide an integrated environment for visualizing, comparing, analysing and sharing both publicly available and user-generated genomic data sets. As of September 2013, the database contained genomic sequence and a basic set of annotation ‘tracks’ for ∼90 organisms. Significant new annotations include a 60-species multiple alignment conservation track on the mouse, updated UCSC Genes tracks for human and mouse, and several new sets of variation and ENCODE data. New software tools include a Variant Annotation Integrator that returns predicted functional effects of a set of variants uploaded as a custom track, an extension to UCSC Genes that displays haplotype alleles for protein-coding genes and an expansion of data hubs that includes the capability to display remotely hosted user-provided assembly sequence in addition to annotation data. To improve European access, we have added a Genome Browser mirror (http://genome-euro.ucsc.edu) hosted at Bielefeld University in Germany. PMID:24270787

  19. Improvement of the Database on the 1.13-microns Band of Water Vapor

    NASA Technical Reports Server (NTRS)

    Giver, Lawrence P.; Schwenke, David W.; Chackerian, Charles, Jr.; Varanasi, Prasad; Freedman, Richard S.; Gore, Warren J. (Technical Monitor)

    2000-01-01

    Corrections have recently been reported (Giver et al.) on the short-wave (visible and near-infrared) line intensities of water vapor that were catalogued in the spectroscopic database known as HITRAN. These updates have been posted on www.hitran.com, and are being used to reanalyze the polar stratospheric absorption in the 0.94 microns band as observed in POAM. We are currently investigating additional improvement in the 1.13 microns band using data obtained by us with an absorption path length of 1.107 km and 4 torr of water vapor and the ab initio line list of Partridge and Schwenke (needs ref). We are proposing the following four types of improvement of the HITRAN database in this region: 1) HITRAN has nearly 200 lines in this region without proper assignments of rotational quantum levels. Nearly all of them can now be assigned. 2) We have measured positions of the observable H2O-17 and H2O-18 lines. These lines in HITRAN currently have approximate positions based upon rather aged computations. 3) Some additional lines are observed and assigned which should be included in the database. 4) Corrections are necessary for the lower state energies E" for the HITRAN lines of the 121-010 "hot" band.

  20. The SILVA ribosomal RNA gene database project: improved data processing and web-based tools.

    PubMed

    Quast, Christian; Pruesse, Elmar; Yilmaz, Pelin; Gerken, Jan; Schweer, Timmy; Yarza, Pablo; Peplies, Jörg; Glöckner, Frank Oliver

    2013-01-01

    SILVA (from Latin silva, forest, http://www.arb-silva.de) is a comprehensive web resource for up to date, quality-controlled databases of aligned ribosomal RNA (rRNA) gene sequences from the Bacteria, Archaea and Eukaryota domains and supplementary online services. The referred database release 111 (July 2012) contains 3 194 778 small subunit and 288 717 large subunit rRNA gene sequences. Since the initial description of the project, substantial new features have been introduced, including advanced quality control procedures, an improved rRNA gene aligner, online tools for probe and primer evaluation and optimized browsing, searching and downloading on the website. Furthermore, the extensively curated SILVA taxonomy and the new non-redundant SILVA datasets provide an ideal reference for high-throughput classification of data from next-generation sequencing approaches.

  1. HERVd: the Human Endogenous RetroViruses Database: update.

    PubMed

    Paces, Jan; Pavlícek, Adam; Zika, Radek; Kapitonov, Vladimir V; Jurka, Jerzy; Paces, Václav

    2004-01-01

    An elaboration of HERVd (http://herv.img.cas.cz) is being carried out in two directions. One of them is the integration and better classification of families that diverge considerably from typical retroviral genomes. This leads to a more precise identification of members with individual families. The second improvement is better accessibility of the database and connection with human genome annotation.

  2. Recommendations for Improving the National Education Fiscal Database. Education Data Improvement Project.

    ERIC Educational Resources Information Center

    Clements, Barbara S.; And Others

    A summary of recommendations for improving the fiscal data portion of the Center for Education Statistics' Common Core of Data includes a discussion of the issues surrounding each recommendation. The following actions are recommended: (1) revenues and expenditures should include a breakdown of function by funds, and further detail should be…

  3. MicroScope: a platform for microbial genome annotation and comparative genomics.

    PubMed

    Vallenet, D; Engelen, S; Mornico, D; Cruveiller, S; Fleury, L; Lajus, A; Rouy, Z; Roche, D; Salvignol, G; Scarpelli, C; Médigue, C

    2009-01-01

    The initial outcome of genome sequencing is the creation of long text strings written in a four letter alphabet. The role of in silico sequence analysis is to assist biologists in the act of associating biological knowledge with these sequences, allowing investigators to make inferences and predictions that can be tested experimentally. A wide variety of software is available to the scientific community, and can be used to identify genomic objects, before predicting their biological functions. However, only a limited number of biologically interesting features can be revealed from an isolated sequence. Comparative genomics tools, on the other hand, by bringing together the information contained in numerous genomes simultaneously, allow annotators to make inferences based on the idea that evolution and natural selection are central to the definition of all biological processes. We have developed the MicroScope platform in order to offer a web-based framework for the systematic and efficient revision of microbial genome annotation and comparative analysis (http://www.genoscope.cns.fr/agc/microscope). Starting with the description of the flow chart of the annotation processes implemented in the MicroScope pipeline, and the development of traditional and novel microbial annotation and comparative analysis tools, this article emphasizes the essential role of expert annotation as a complement of automatic annotation. Several examples illustrate the use of implemented tools for the review and curation of annotations of both new and publicly available microbial genomes within MicroScope's rich integrated genome framework. The platform is used as a viewer in order to browse updated annotation information of available microbial genomes (more than 440 organisms to date), and in the context of new annotation projects (117 bacterial genomes). The human expertise gathered in the MicroScope database (about 280,000 independent annotations) contributes to improve the quality of

  4. Optimization of filtering criterion for SEQUEST database searching to improve proteome coverage in shotgun proteomics

    PubMed Central

    Jiang, Xinning; Jiang, Xiaogang; Han, Guanghui; Ye, Mingliang; Zou, Hanfa

    2007-01-01

    Background In proteomic analysis, MS/MS spectra acquired by mass spectrometer are assigned to peptides by database searching algorithms such as SEQUEST. The assignations of peptides to MS/MS spectra by SEQUEST searching algorithm are defined by several scores including Xcorr, ΔCn, Sp, Rsp, matched ion count and so on. Filtering criterion using several above scores is used to isolate correct identifications from random assignments. However, the filtering criterion was not favorably optimized up to now. Results In this study, we implemented a machine learning approach known as predictive genetic algorithm (GA) for the optimization of filtering criteria to maximize the number of identified peptides at fixed false-discovery rate (FDR) for SEQUEST database searching. As the FDR was directly determined by decoy database search scheme, the GA based optimization approach did not require any pre-knowledge on the characteristics of the data set, which represented significant advantages over statistical approaches such as PeptideProphet. Compared with PeptideProphet, the GA based approach can achieve similar performance in distinguishing true from false assignment with only 1/10 of the processing time. Moreover, the GA based approach can be easily extended to process other database search results as it did not rely on any assumption on the data. Conclusion Our results indicated that filtering criteria should be optimized individually for different samples. The new developed software using GA provides a convenient and fast way to create tailored optimal criteria for different proteome samples to improve proteome coverage. PMID:17761002

  5. Concept annotation in the CRAFT corpus

    PubMed Central

    2012-01-01

    Background Manually annotated corpora are critical for the training and evaluation of automated methods to identify concepts in biomedical text. Results This paper presents the concept annotations of the Colorado Richly Annotated Full-Text (CRAFT) Corpus, a collection of 97 full-length, open-access biomedical journal articles that have been annotated both semantically and syntactically to serve as a research resource for the biomedical natural-language-processing (NLP) community. CRAFT identifies all mentions of nearly all concepts from nine prominent biomedical ontologies and terminologies: the Cell Type Ontology, the Chemical Entities of Biological Interest ontology, the NCBI Taxonomy, the Protein Ontology, the Sequence Ontology, the entries of the Entrez Gene database, and the three subontologies of the Gene Ontology. The first public release includes the annotations for 67 of the 97 articles, reserving two sets of 15 articles for future text-mining competitions (after which these too will be released). Concept annotations were created based on a single set of guidelines, which has enabled us to achieve consistently high interannotator agreement. Conclusions As the initial 67-article release contains more than 560,000 tokens (and the full set more than 790,000 tokens), our corpus is among the largest gold-standard annotated biomedical corpora. Unlike most others, the journal articles that comprise the corpus are drawn from diverse biomedical disciplines and are marked up in their entirety. Additionally, with a concept-annotation count of nearly 100,000 in the 67-article subset (and more than 140,000 in the full collection), the scale of conceptual markup is also among the largest of comparable corpora. The concept annotations of the CRAFT Corpus have the potential to significantly advance biomedical text mining by providing a high-quality gold standard for NLP systems. The corpus, annotation guidelines, and other associated resources are freely available at http

  6. Retrieval-based Face Annotation by Weak Label Regularized Local Coordinate Coding.

    PubMed

    Wang, Dayong; Hoi, Steven C H; He, Ying; Zhu, Jianke; Mei, Tao; Luo, Jiebo

    2013-08-01

    Retrieval-based face annotation is a promising paradigm of mining massive web facial images for automated face annotation. This paper addresses a critical problem of such paradigm, i.e., how to effectively perform annotation by exploiting the similar facial images and their weak labels which are often noisy and incomplete. In particular, we propose an effective Weak Label Regularized Local Coordinate Coding (WLRLCC) technique, which exploits the principle of local coordinate coding in learning sparse features, and employs the idea of graph-based weak label regularization to enhance the weak labels of the similar facial images. We present an efficient optimization algorithm to solve the WLRLCC task. We conduct extensive empirical studies on two large-scale web facial image databases: (i) a Western celebrity database with a total of $6,025$ persons and $714,454$ web facial images, and (ii)an Asian celebrity database with $1,200$ persons and $126,070$ web facial images. The encouraging results validate the efficacy of the proposed WLRLCC algorithm. To further improve the efficiency and scalability, we also propose a PCA-based approximation scheme and an offline approximation scheme (AWLRLCC), which generally maintains comparable results but significantly saves much time cost. Finally, we show that WLRLCC can also tackle two existing face annotation tasks with promising performance.

  7. Collaborative annotation of 3D crystallographic models.

    PubMed

    Hunter, J; Henderson, M; Khan, I

    2007-01-01

    This paper describes the AnnoCryst system-a tool that was designed to enable authenticated collaborators to share online discussions about 3D crystallographic structures through the asynchronous attachment, storage, and retrieval of annotations. Annotations are personal comments, interpretations, questions, assessments, or references that can be attached to files, data, digital objects, or Web pages. The AnnoCryst system enables annotations to be attached to 3D crystallographic models retrieved from either private local repositories (e.g., Fedora) or public online databases (e.g., Protein Data Bank or Inorganic Crystal Structure Database) via a Web browser. The system uses the Jmol plugin for viewing and manipulating the 3D crystal structures but extends Jmol by providing an additional interface through which annotations can be created, attached, stored, searched, browsed, and retrieved. The annotations are stored on a standardized Web annotation server (Annotea), which has been extended to support 3D macromolecular structures. Finally, the system is embedded within a security framework that is capable of authenticating users and restricting access only to trusted colleagues.

  8. Database Constraints Applied to Metabolic Pathway Reconstruction Tools

    PubMed Central

    Vilaplana, Jordi; Solsona, Francesc; Teixido, Ivan; Usié, Anabel; Karathia, Hiren; Alves, Rui; Mateo, Jordi

    2014-01-01

    Our group developed two biological applications, Biblio-MetReS and Homol-MetReS, accessing the same database of organisms with annotated genes. Biblio-MetReS is a data-mining application that facilitates the reconstruction of molecular networks based on automated text-mining analysis of published scientific literature. Homol-MetReS allows functional (re)annotation of proteomes, to properly identify both the individual proteins involved in the process(es) of interest and their function. It also enables the sets of proteins involved in the process(es) in different organisms to be compared directly. The efficiency of these biological applications is directly related to the design of the shared database. We classified and analyzed the different kinds of access to the database. Based on this study, we tried to adjust and tune the configurable parameters of the database server to reach the best performance of the communication data link to/from the database system. Different database technologies were analyzed. We started the study with a public relational SQL database, MySQL. Then, the same database was implemented by a MapReduce-based database named HBase. The results indicated that the standard configuration of MySQL gives an acceptable performance for low or medium size databases. Nevertheless, tuning database parameters can greatly improve the performance and lead to very competitive runtimes. PMID:25202745

  9. Improving Quality and Quantity of Contributions: Two Models for Promoting Knowledge Exchange with Shared Databases

    ERIC Educational Resources Information Center

    Cress, U.; Barquero, B.; Schwan, S.; Hesse, F. W.

    2007-01-01

    Shared databases are used for knowledge exchange in groups. Whether a person is willing to contribute knowledge to a shared database presents a social dilemma: Each group member saves time and energy by not contributing any information to the database and by using the database only to retrieve information which was contributed by others. But if…

  10. Selectome update: quality control and computational improvements to a database of positive selection.

    PubMed

    Moretti, Sébastien; Laurenczy, Balazs; Gharib, Walid H; Castella, Briséïs; Kuzniar, Arnold; Schabauer, Hannes; Studer, Romain A; Valle, Mario; Salamin, Nicolas; Stockinger, Heinz; Robinson-Rechavi, Marc

    2014-01-01

    Selectome (http://selectome.unil.ch/) is a database of positive selection, based on a branch-site likelihood test. This model estimates the number of nonsynonymous substitutions (dN) and synonymous substitutions (dS) to evaluate the variation in selective pressure (dN/dS ratio) over branches and over sites. Since the original release of Selectome, we have benchmarked and implemented a thorough quality control procedure on multiple sequence alignments, aiming to provide minimum false-positive results. We have also improved the computational efficiency of the branch-site test implementation, allowing larger data sets and more frequent updates. Release 6 of Selectome includes all gene trees from Ensembl for Primates and Glires, as well as a large set of vertebrate gene trees. A total of 6810 gene trees have some evidence of positive selection. Finally, the web interface has been improved to be more responsive and to facilitate searches and browsing.

  11. Integrative Tissue-Specific Functional Annotations in the Human Genome Provide Novel Insights on Many Complex Traits and Improve Signal Prioritization in Genome Wide Association Studies

    PubMed Central

    Wang, Qian; He, Beixin Julie; Zhao, Hongyu

    2016-01-01

    Extensive efforts have been made to understand genomic function through both experimental and computational approaches, yet proper annotation still remains challenging, especially in non-coding regions. In this manuscript, we introduce GenoSkyline, an unsupervised learning framework to predict tissue-specific functional regions through integrating high-throughput epigenetic annotations. GenoSkyline successfully identified a variety of non-coding regulatory machinery including enhancers, regulatory miRNA, and hypomethylated transposable elements in extensive case studies. Integrative analysis of GenoSkyline annotations and results from genome-wide association studies (GWAS) led to novel biological insights on the etiologies of a number of human complex traits. We also explored using tissue-specific functional annotations to prioritize GWAS signals and predict relevant tissue types for each risk locus. Brain and blood-specific annotations led to better prioritization performance for schizophrenia than standard GWAS p-values and non-tissue-specific annotations. As for coronary artery disease, heart-specific functional regions was highly enriched of GWAS signals, but previously identified risk loci were found to be most functional in other tissues, suggesting a substantial proportion of still undetected heart-related loci. In summary, GenoSkyline annotations can guide genetic studies at multiple resolutions and provide valuable insights in understanding complex diseases. GenoSkyline is available at http://genocanyon.med.yale.edu/GenoSkyline. PMID:27058395

  12. Improved annotation of 3' untranslated regions and complex loci by combination of strand-specific direct RNA sequencing, RNA-Seq and ESTs.

    PubMed

    Schurch, Nicholas J; Cole, Christian; Sherstnev, Alexander; Song, Junfang; Duc, Céline; Storey, Kate G; McLean, W H Irwin; Brown, Sara J; Simpson, Gordon G; Barton, Geoffrey J

    2014-01-01

    The reference annotations made for a genome sequence provide the framework for all subsequent analyses of the genome. Correct and complete annotation in addition to the underlying genomic sequence is particularly important when interpreting the results of RNA-seq experiments where short sequence reads are mapped against the genome and assigned to genes according to the annotation. Inconsistencies in annotations between the reference and the experimental system can lead to incorrect interpretation of the effect on RNA expression of an experimental treatment or mutation in the system under study. Until recently, the genome-wide annotation of 3' untranslated regions received less attention than coding regions and the delineation of intron/exon boundaries. In this paper, data produced for samples in Human, Chicken and A. thaliana by the novel single-molecule, strand-specific, Direct RNA Sequencing technology from Helicos Biosciences which locates 3' polyadenylation sites to within +/- 2 nt, were combined with archival EST and RNA-Seq data. Nine examples are illustrated where this combination of data allowed: (1) gene and 3' UTR re-annotation (including extension of one 3' UTR by 5.9 kb); (2) disentangling of gene expression in complex regions; (3) clearer interpretation of small RNA expression and (4) identification of novel genes. While the specific examples displayed here may become obsolete as genome sequences and their annotations are refined, the principles laid out in this paper will be of general use both to those annotating genomes and those seeking to interpret existing publically available annotations in the context of their own experimental data.

  13. Orienteering: An Annotated Bibliography = Orientierungslauf: Eine kommentierte Bibliographie.

    ERIC Educational Resources Information Center

    Seiler, Roland, Ed.; Hartmann, Wolfgang, Ed.

    1994-01-01

    Annotated bibliography of 220 books, monographs, and journal articles on orienteering published 1984-94, from SPOLIT database of the Federal Institute of Sport Science (Cologne, Germany). Annotations in English or German. Ten sections including psychological, physiological, health, sociological, and environmental aspects; training and coaching;…

  14. The PIR-International Protein Sequence Database.

    PubMed

    Barker, W C; Garavelli, J S; McGarvey, P B; Marzec, C R; Orcutt, B C; Srinivasarao, G Y; Yeh, L S; Ledley, R S; Mewes, H W; Pfeiffer, F; Tsugita, A; Wu, C

    1999-01-01

    The Protein Information Resource (PIR; http://www-nbrf.georgetown. edu/pir/) supports research on molecular evolution, functional genomics, and computational biology by maintaining a comprehensive, non-redundant, well-organized and freely available protein sequence database. Since 1988 the database has been maintained collaboratively by PIR-International, an international association of data collection centers cooperating to develop this resource during a period of explosive growth in new sequence data and new computer technologies. The PIR Protein Sequence Database entries are classified into superfamilies, families and homology domains, for which sequence alignments are available. Full-scale family classification supports comparative genomics research, aids sequence annotation, assists database organization and improves database integrity. The PIR WWW server supports direct on-line sequence similarity searches, information retrieval, and knowledge discovery by providing the Protein Sequence Database and other supplementary databases. Sequence entries are extensively cross-referenced and hypertext-linked to major nucleic acid, literature, genome, structure, sequence alignment and family databases. The weekly release of the Protein Sequence Database can be accessed through the PIR Web site. The quarterly release of the database is freely available from our anonymous FTP server and is also available on CD-ROM with the accompanying ATLAS database search program.

  15. The University of Minnesota Biocatalysis/Biodegradation Database: improving public access.

    PubMed

    Gao, Junfeng; Ellis, Lynda B M; Wackett, Lawrence P

    2010-01-01

    The University of Minnesota Biocatalysis/Biodegradation Database (UM-BBD, http://umbbd.msi.umn.edu/) began in 1995 and now contains information on almost 1200 compounds, over 800 enzymes, almost 1300 reactions and almost 500 microorganism entries. Besides these data, it includes a Biochemical Periodic Table (UM-BPT) and a rule-based Pathway Prediction System (UM-PPS) (http://umbbd.msi.umn.edu/predict/) that predicts plausible pathways for microbial degradation of organic compounds. Currently, the UM-PPS contains 260 biotransformation rules derived from reactions found in the UM-BBD and scientific literature. Public access to UM-BBD data is increasing. UM-BBD compound data are now contributed to PubChem and ChemSpider, the public chemical databases. A new mirror website of the UM-BBD, UM-BPT and UM-PPS is being developed at ETH Zürich to improve speed and reliability of online access from anywhere in the world.

  16. Web-based Video Annotation and its Applications

    NASA Astrophysics Data System (ADS)

    Yamamoto, Daisuke; Nagao, Katashi

    In this paper, we developed a Web-based video annotation system, named iVAS (intelligent Video Annotation Server). Audiences can associate any video content on the Internet with annotations. The system analyzes video content in order to acquire cut/shot information and color histograms. And it also automatically generates a Web page for editing annotations. Then, audiences can create annotation data by two methods. The first one helps the users to create text data such as person/object names, scene descriptions, and comments interactively. The second method facilitates the users associating any video fragments with their subjective impression by just clicking a mouse button. The generated annotation data are accumulated and managed by an XML database connected with iVAS. We also developed some application systems based on annotations such as video retrieval, video simplification, and video-content-based community support. One of the major advantages of our approach is easy integration of hand-coded and automatically-generated (such as color histograms and cut/shot information) annotations. Additionally, since our annotation system is open for public, we must consider some reliability or correctness of annotation data. We also developed an automatic evaluation method of annotation reliability using the users' feedback. In the future, these fundamental technologies will contribute to the formation of new communities centered around video content.

  17. Galileo Reader and Annotator

    NASA Astrophysics Data System (ADS)

    Besomi, O.

    2011-06-01

    In his readings, Galileo made frequent use of annotations. Here, I will offer a general glance at them by discussing the case of the annotations to the Libra astronomica published in 1619 by Orazio Grassi, a Jesuit mathematician of the Collegio Romano. The annotations directly reflect Galileo's reaction to Grassi's book in a heated debate between the two astronomers. Galileo and Grassi had opposite ideas about the nature of the comets, which resulted in different scientific and theological implications. The annotations represent the starting point for Galileo's reply to the Libra, namely Il Saggiatore, which was published four years later and dedicated to the new pope Urban VIII.

  18. T4SP Database 2.0: An Improved Database for Type IV Secretion Systems in Bacterial Genomes with New Online Analysis Tools

    PubMed Central

    Han, Na; Yu, Weiwen; Qiang, Yujun

    2016-01-01

    Type IV secretion system (T4SS) can mediate the passage of macromolecules across cellular membranes and is essential for virulent and genetic material exchange among bacterial species. The Type IV Secretion Project 2.0 (T4SP 2.0) database is an improved and extended version of the platform released in 2013 aimed at assisting with the detection of Type IV secretion systems (T4SS) in bacterial genomes. This advanced version provides users with web server tools for detecting the existence and variations of T4SS genes online. The new interface for the genome browser provides a user-friendly access to the most complete and accurate resource of T4SS gene information (e.g., gene number, name, type, position, sequence, related articles, and quick links to other webs). Currently, this online database includes T4SS information of 5239 bacterial strains. Conclusions. T4SS is one of the most versatile secretion systems necessary for the virulence and survival of bacteria and the secretion of protein and/or DNA substrates from a donor to a recipient cell. This database on virB/D genes of the T4SS system will help scientists worldwide to improve their knowledge on secretion systems and also identify potential pathogenic mechanisms of various microbial species. PMID:27738451

  19. Evaluating techniques for metagenome annotation using simulated sequence data.

    PubMed

    Randle-Boggis, Richard J; Helgason, Thorunn; Sapp, Melanie; Ashton, Peter D

    2016-07-01

    The advent of next-generation sequencing has allowed huge amounts of DNA sequence data to be produced, advancing the capabilities of microbial ecosystem studies. The current challenge is to identify from which microorganisms and genes the DNA originated. Several tools and databases are available for annotating DNA sequences. The tools, databases and parameters used can have a significant impact on the results: naïve choice of these factors can result in a false representation of community composition and function. We use a simulated metagenome to show how different parameters affect annotation accuracy by evaluating the sequence annotation performances of MEGAN, MG-RAST, One Codex and Megablast. This simulated metagenome allowed the recovery of known organism and function abundances to be quantitatively evaluated, which is not possible for environmental metagenomes. The performance of each program and database varied, e.g. One Codex correctly annotated many sequences at the genus level, whereas MG-RAST RefSeq produced many false positive annotations. This effect decreased as the taxonomic level investigated increased. Selecting more stringent parameters decreases the annotation sensitivity, but increases precision. Ultimately, there is a trade-off between taxonomic resolution and annotation accuracy. These results should be considered when annotating metagenomes and interpreting results from previous studies. PMID:27162180

  20. Evaluating techniques for metagenome annotation using simulated sequence data

    PubMed Central

    Randle-Boggis, Richard J.; Helgason, Thorunn; Sapp, Melanie; Ashton, Peter D.

    2016-01-01

    The advent of next-generation sequencing has allowed huge amounts of DNA sequence data to be produced, advancing the capabilities of microbial ecosystem studies. The current challenge is to identify from which microorganisms and genes the DNA originated. Several tools and databases are available for annotating DNA sequences. The tools, databases and parameters used can have a significant impact on the results: naïve choice of these factors can result in a false representation of community composition and function. We use a simulated metagenome to show how different parameters affect annotation accuracy by evaluating the sequence annotation performances of MEGAN, MG-RAST, One Codex and Megablast. This simulated metagenome allowed the recovery of known organism and function abundances to be quantitatively evaluated, which is not possible for environmental metagenomes. The performance of each program and database varied, e.g. One Codex correctly annotated many sequences at the genus level, whereas MG-RAST RefSeq produced many false positive annotations. This effect decreased as the taxonomic level investigated increased. Selecting more stringent parameters decreases the annotation sensitivity, but increases precision. Ultimately, there is a trade-off between taxonomic resolution and annotation accuracy. These results should be considered when annotating metagenomes and interpreting results from previous studies. PMID:27162180

  1. A Radiocarbon Database for Improving Understanding of Global Soil Carbon Dynamics: Part I

    NASA Astrophysics Data System (ADS)

    Torn, M. S.; Trumbore, S.; Smith, L. J.; Nave, L. E.; Sierra, C. A.; Harden, J. W.; Agarwal, D.; van Ingen, C.; Radiocarbon Database Workshop 2011

    2011-12-01

    Soils play a large role in the global carbon cycle, but soil carbon stocks and dynamics remain highly uncertain. Radiocarbon (14C) observations from soils and soil respiration provide one of the only ways to infer terrestrial carbon turnover times or to test ecosystem carbon models. Although a wealth of such observations exists, they are scattered in small data sets held by individual researchers, and have not been compiled in a form easy to use for multi-site analysis, global assessments, or model testing. Here we introduce a new, global radiocarbon database that will synthesize datasets from multiple contributors to facilitate research on three broad questions: (1) What are current patterns of soil carbon dynamics, and what factors influence these patterns? (2) What is the sequestration capacity of different soils? (3) What are likely impacts of global change on the soil resource? (4) How well do models represent important carbon cycle processes, and how can they be improved? In addition to assembling data in a common format for analyses, this database will offer query capabilities and the ability to combine data with gridded global products, such as temporally resolved temperature and precipitation, NPP and GPP, and a climate-based decomposition index. Some of the near-term synthesis goals include analyzing depth profiles of 14C for across gradients in ecosystem state factors (climate, organisms, relief, parent material, time, and human influence) and soil orders; mapping surface-soil 14C values on soil temperature and moisture; and comparing soil carbon turnover times to NPP and soil carbon stocks. We are currently incorporating data from 18 contributors and six continents, with 14C measurements from soils representing nine soil orders, plant and microbial tissues, and respiration fluxes. Our intention is to grow the database and make it available to a wide community of scientists. For example, observations for different disturbance, experimental treatment, or

  2. Scientific and Technical Document Database

    National Institute of Standards and Technology Data Gateway

    NIST Scientific and Technical Document Database (PC database for purchase)   The images in NIST Special Database 20 contain a very rich set of graphic elements from scientific and technical documents, such as graphs, tables, equations, two column text, maps, pictures, footnotes, annotations, and arrays of such elements.

  3. National Trauma Database (NTrD)--improving trauma care: first year report.

    PubMed

    Sabariah, F J; Ramesh, N; Mahathar, A W

    2008-09-01

    The first Malaysian National Trauma Database was launched in May 2006 with five tertiary referral centres to determine the fundamental data on major trauma, subsequently to evaluate the major trauma management and to come up with guidelines for improved trauma care. A prospective study, using standardized and validated questionnaires, was carried out from May 2006 till April 2007 for all cases admitted and referred to the participating hospitals. During the one year period, 123,916 trauma patients were registered, of which 933 (0.75%) were classified as major trauma. Patients with blunt injury made up for 83.9% of cases and RTA accounted for 72.6% of injuries with 64.9% involving motorcyclist and pillion rider. 42.8% had severe head injury with an admission Glasgow Coma Scale (GCS) of 3-8 and the Revised Trauma Score (RTS) of 5-6 were recorded in 28.8% of patients. The distribution of Injury Severity Score (ISS) showed that 42.9% of cases were in the range of 16-24. Only 1.9% and 6.3% of the patients were reviewed by the Emergency Physician and Surgeon respectively. Patients with admission systolic blood pressure of less than 90 mmHg had a death rate of 54.6%. Patients with severe head injury (GCS < 9), 45.1% died while 79% patients with moderate head injury survived. There were more survivors within the higher RTS range compared to the lower RTS. Patients with direct admission accounted for 52.3% of survivors and there were 61.7% survivors for referred cases. In conclusion, NTrD first report has successfully demonstrated its significance in giving essential data on major trauma in Malaysia, however further expansion of the study may reflect more comprehensive trauma database in this country.

  4. A statistical filtering procedure to improve the accuracy of estimating population parameters in feed composition databases.

    PubMed

    Yoder, P S; St-Pierre, N R; Weiss, W P

    2014-09-01

    Accurate estimates of mean nutrient composition of feeds, nutrient variance (i.e., standard deviation), and covariance (i.e., correlation) are needed to develop a more quantitative approach of formulating diets to reduce risk and optimize safety factors. Commercial feed-testing laboratories have large databases of composition values for many feeds, but because of potentially misidentified feeds or poorly defined feed names, these databases are possibly contaminated by incorrect results and could generate inaccurate statistics. The objectives of this research were to (1) design a procedure (also known as a mathematical filter) that generates accurate estimates of the first 2 moments [i.e., the mean and (co)variance] of the nutrient distributions for the largest subpopulation within a feed in the presence of outliers and multiple subpopulations, and (2) use the procedure to generate feed composition tables with accurate means, variances, and correlations. Feed composition data (>1,300,000 samples) were collected from 2 major US commercial laboratories. A combination of a univariate step and 2 multivariate steps (principal components analysis and cluster analysis) were used to filter the data. On average, 13.5% of the total samples of a particular feed population were removed, of which the multivariate steps removed the majority (66% of removed samples). For some feeds, inaccurate identification (e.g., corn gluten feed samples included in the corn gluten meal population) was a primary reason for outliers, whereas for other feeds, subpopulations of a broader population were identified (e.g., immature alfalfa silage within a broad population of alfalfa silage). Application of the procedure did not usually affect the mean concentration of nutrients but greatly reduced the standard deviation and often changed the correlation estimates among nutrients. More accurate estimates of the variation of feeds and how they tend to vary will improve the economic evaluation of feeds

  5. Automated Knowledge Annotation for Dynamic Collaborative Environments

    SciTech Connect

    Cowell, Andrew J.; Gregory, Michelle L.; Marshall, Eric J.; McGrath, Liam R.

    2009-05-19

    This paper describes the Knowledge Encapsulation Framework (KEF), a suite of tools to enable automated knowledge annotation for modeling and simulation projects. This framework can be used to capture evidence (e.g., facts extracted from journal articles and government reports), discover new evidence (from similar peer-reviewed material as well as social media), enable discussions surrounding domain-specific topics and provide automatically generated semantic annotations for improved corpus investigation. The current KEF implementation is presented within a wiki environment, providing a simple but powerful collaborative space for team members to review, annotate, discuss and align evidence with their modeling frameworks.

  6. Annotation extension through protein family annotation coherence metrics

    PubMed Central

    Bastos, Hugo P.; Clarke, Luka A.; Couto, Francisco M.

    2013-01-01

    Protein functional annotation consists in associating proteins with textual descriptors elucidating their biological roles. The bulk of annotation is done via automated procedures that ultimately rely on annotation transfer. Despite a large number of existing protein annotation procedures the ever growing protein space is never completely annotated. One of the facets of annotation incompleteness derives from annotation uncertainty. Often when protein function cannot be predicted with enough specificity it is instead conservatively annotated with more generic terms. In a scenario of protein families or functionally related (or even dissimilar) sets this leads to a more difficult task of using annotations to compare the extent of functional relatedness among all family or set members. However, we postulate that identifying sub-sets of functionally coherent proteins annotated at a very specific level, can help the annotation extension of other incompletely annotated proteins within the same family or functionally related set. As an example we analyse the status of annotation of a set of CAZy families belonging to the Polysaccharide Lyase class. We show that through the use of visualization methods and semantic similarity based metrics it is possible to identify families and respective annotation terms within them that are suitable for possible annotation extension. Based on our analysis we then propose a semi-automatic methodology leading to the extension of single annotation terms within these partially annotated protein sets or families. PMID:24130572

  7. Improving pharmaceutical innovation by building a more comprehensive database on drug development and use.

    PubMed

    Daniel, Gregory W; Cazé, Alexis; Romine, Morgan H; Audibert, Céline; Leff, Jonathan S; McClellan, Mark B

    2015-02-01

    New drugs and biologics have had a tremendous impact on the treatment of many diseases. However, available measures suggest that pharmaceutical innovation has remained relatively flat, despite substantial growth in research and development spending. We review recent literature on pharmaceutical innovation to identify limitations in measuring and assessing innovation, and we describe the framework and collaborative approach we are using to develop more comprehensive, publicly available metrics for innovation. Our research teams at the Brookings Institution and Deerfield Institute are collaborating with experts from multiple areas of drug development and regulatory review to identify and collect comprehensive data elements related to key development and regulatory characteristics for each new molecular entity approved over the past several decades in the United States and the European Union. Subsequent phases of our effort will add data on downstream product use and patient outcomes and will also include drugs that have failed or been abandoned in development. Such a database will enable researchers to better analyze the drivers of drug innovation, trends in the output of new medicines, and the effect of policy efforts designed to improve innovation.

  8. Improving pharmaceutical innovation by building a more comprehensive database on drug development and use.

    PubMed

    Daniel, Gregory W; Cazé, Alexis; Romine, Morgan H; Audibert, Céline; Leff, Jonathan S; McClellan, Mark B

    2015-02-01

    New drugs and biologics have had a tremendous impact on the treatment of many diseases. However, available measures suggest that pharmaceutical innovation has remained relatively flat, despite substantial growth in research and development spending. We review recent literature on pharmaceutical innovation to identify limitations in measuring and assessing innovation, and we describe the framework and collaborative approach we are using to develop more comprehensive, publicly available metrics for innovation. Our research teams at the Brookings Institution and Deerfield Institute are collaborating with experts from multiple areas of drug development and regulatory review to identify and collect comprehensive data elements related to key development and regulatory characteristics for each new molecular entity approved over the past several decades in the United States and the European Union. Subsequent phases of our effort will add data on downstream product use and patient outcomes and will also include drugs that have failed or been abandoned in development. Such a database will enable researchers to better analyze the drivers of drug innovation, trends in the output of new medicines, and the effect of policy efforts designed to improve innovation. PMID:25646113

  9. Functional annotation of hypothetical proteins - A review.

    PubMed

    Sivashankari, Selvarajan; Shanmughavel, Piramanayagam

    2006-12-29

    The complete human genome sequences in the public database provide ways to understand the blue print of life. As of June 29, 2006, 27 archaeal, 326 bacterial and 21 eukaryotes is complete genomes are available and the sequencing for 316 bacterial, 24 archaeal, 126 eukaryotic genomes are in progress. The traditional biochemical/molecular experiments can assign accurate functions for genes in these genomes. However, the process is time-consuming and costly. Despite several efforts, only 50-60 % of genes have been annotated in most completely sequenced genomes. Automated genome sequence analysis and annotation may provide ways to understand genomes. Thus, determination of protein function is one of the challenging problems of the post-genome era. This demands bioinformatics to predict functions of un-annotated protein sequences by developing efficient tools. Here, we discuss some of the recent and popular approaches developed in Bioinformatics to predict functions for hypothetical proteins.

  10. DDBJ progress report: a new submission system for leading to a correct annotation

    PubMed Central

    Kosuge, Takehide; Mashima, Jun; Kodama, Yuichi; Fujisawa, Takatomo; Kaminuma, Eli; Ogasawara, Osamu; Okubo, Kousaku; Takagi, Toshihisa; Nakamura, Yasukazu

    2014-01-01

    The DNA Data Bank of Japan (DDBJ; http://www.ddbj.nig.ac.jp) maintains and provides archival, retrieval and analytical resources for biological information. This database content is shared with the US National Center for Biotechnology Information (NCBI) and the European Bioinformatics Institute (EBI) within the framework of the International Nucleotide Sequence Database Collaboration (INSDC). DDBJ launched a new nucleotide sequence submission system for receiving traditional nucleotide sequence. We expect that the new submission system will be useful for many submitters to input accurate annotation and reduce the time needed for data input. In addition, DDBJ has started a new service, the Japanese Genotype–phenotype Archive (JGA), with our partner institute, the National Bioscience Database Center (NBDC). JGA permanently archives and shares all types of individual human genetic and phenotypic data. We also introduce improvements in the DDBJ services and databases made during the past year. PMID:24194602

  11. ERAIZDA: a model for holistic annotation of animal infectious and zoonotic diseases.

    PubMed

    Buza, Teresia M; Jack, Sherman W; Kirunda, Halid; Khaitsa, Margaret L; Lawrence, Mark L; Pruett, Stephen; Peterson, Daniel G

    2015-01-01

    There is an urgent need for a unified resource that integrates trans-disciplinary annotations of emerging and reemerging animal infectious and zoonotic diseases. Such data integration will provide wonderful opportunity for epidemiologists, researchers and health policy makers to make data-driven decisions designed to improve animal health. Integrating emerging and reemerging animal infectious and zoonotic disease data from a large variety of sources into a unified open-access resource provides more plausible arguments to achieve better understanding of infectious and zoonotic diseases. We have developed a model for interlinking annotations of these diseases. These diseases are of particular interest because of the threats they pose to animal health, human health and global health security. We demonstrated the application of this model using brucellosis, an infectious and zoonotic disease. Preliminary annotations were deposited into VetBioBase database (http://vetbiobase.igbb.msstate.edu). This database is associated with user-friendly tools to facilitate searching, retrieving and downloading of disease-related information. Database URL: http://vetbiobase.igbb.msstate.edu.

  12. ERAIZDA: a model for holistic annotation of animal infectious and zoonotic diseases

    PubMed Central

    Buza, Teresia M.; Jack, Sherman W.; Kirunda, Halid; Khaitsa, Margaret L.; Lawrence, Mark L.; Pruett, Stephen; Peterson, Daniel G.

    2015-01-01

    There is an urgent need for a unified resource that integrates trans-disciplinary annotations of emerging and reemerging animal infectious and zoonotic diseases. Such data integration will provide wonderful opportunity for epidemiologists, researchers and health policy makers to make data-driven decisions designed to improve animal health. Integrating emerging and reemerging animal infectious and zoonotic disease data from a large variety of sources into a unified open-access resource provides more plausible arguments to achieve better understanding of infectious and zoonotic diseases. We have developed a model for interlinking annotations of these diseases. These diseases are of particular interest because of the threats they pose to animal health, human health and global health security. We demonstrated the application of this model using brucellosis, an infectious and zoonotic disease. Preliminary annotations were deposited into VetBioBase database (http://vetbiobase.igbb.msstate.edu). This database is associated with user-friendly tools to facilitate searching, retrieving and downloading of disease-related information. Database URL: http://vetbiobase.igbb.msstate.edu PMID:26581408

  13. Deep Question Answering for protein annotation.

    PubMed

    Gobeill, Julien; Gaudinat, Arnaud; Pasche, Emilie; Vishnyakova, Dina; Gaudet, Pascale; Bairoch, Amos; Ruch, Patrick

    2015-01-01

    Biomedical professionals have access to a huge amount of literature, but when they use a search engine, they often have to deal with too many documents to efficiently find the appropriate information in a reasonable time. In this perspective, question-answering (QA) engines are designed to display answers, which were automatically extracted from the retrieved documents. Standard QA engines in literature process a user question, then retrieve relevant documents and finally extract some possible answers out of these documents using various named-entity recognition processes. In our study, we try to answer complex genomics questions, which can be adequately answered only using Gene Ontology (GO) concepts. Such complex answers cannot be found using state-of-the-art dictionary- and redundancy-based QA engines. We compare the effectiveness of two dictionary-based classifiers for extracting correct GO answers from a large set of 100 retrieved abstracts per question. In the same way, we also investigate the power of GOCat, a GO supervised classifier. GOCat exploits the GOA database to propose GO concepts that were annotated by curators for similar abstracts. This approach is called deep QA, as it adds an original classification step, and exploits curated biological data to infer answers, which are not explicitly mentioned in the retrieved documents. We show that for complex answers such as protein functional descriptions, the redundancy phenomenon has a limited effect. Similarly usual dictionary-based approaches are relatively ineffective. In contrast, we demonstrate how existing curated data, beyond information extraction, can be exploited by a supervised classifier, such as GOCat, to massively improve both the quantity and the quality of the answers with a +100% improvement for both recall and precision. Database URL: http://eagl.unige.ch/DeepQA4PA/. PMID:26384372

  14. Deep Question Answering for protein annotation.

    PubMed

    Gobeill, Julien; Gaudinat, Arnaud; Pasche, Emilie; Vishnyakova, Dina; Gaudet, Pascale; Bairoch, Amos; Ruch, Patrick

    2015-01-01

    Biomedical professionals have access to a huge amount of literature, but when they use a search engine, they often have to deal with too many documents to efficiently find the appropriate information in a reasonable time. In this perspective, question-answering (QA) engines are designed to display answers, which were automatically extracted from the retrieved documents. Standard QA engines in literature process a user question, then retrieve relevant documents and finally extract some possible answers out of these documents using various named-entity recognition processes. In our study, we try to answer complex genomics questions, which can be adequately answered only using Gene Ontology (GO) concepts. Such complex answers cannot be found using state-of-the-art dictionary- and redundancy-based QA engines. We compare the effectiveness of two dictionary-based classifiers for extracting correct GO answers from a large set of 100 retrieved abstracts per question. In the same way, we also investigate the power of GOCat, a GO supervised classifier. GOCat exploits the GOA database to propose GO concepts that were annotated by curators for similar abstracts. This approach is called deep QA, as it adds an original classification step, and exploits curated biological data to infer answers, which are not explicitly mentioned in the retrieved documents. We show that for complex answers such as protein functional descriptions, the redundancy phenomenon has a limited effect. Similarly usual dictionary-based approaches are relatively ineffective. In contrast, we demonstrate how existing curated data, beyond information extraction, can be exploited by a supervised classifier, such as GOCat, to massively improve both the quantity and the quality of the answers with a +100% improvement for both recall and precision. Database URL: http://eagl.unige.ch/DeepQA4PA/.

  15. An Introduction to Genome Annotation.

    PubMed

    Campbell, Michael S; Yandell, Mark

    2015-12-17

    Genome projects have evolved from large international undertakings to tractable endeavors for a single lab. Accurate genome annotation is critical for successful genomic, genetic, and molecular biology experiments. These annotations can be generated using a number of approaches and available software tools. This unit describes methods for genome annotation and a number of software tools commonly used in gene annotation.

  16. Improved systematic tRNA gene annotation allows new insights into the evolution of mitochondrial tRNA structures and into the mechanisms of mitochondrial genome rearrangements

    PubMed Central

    Jühling, Frank; Pütz, Joern; Bernt, Matthias; Donath, Alexander; Middendorf, Martin; Florentz, Catherine; Stadler, Peter F.

    2012-01-01

    Transfer RNAs (tRNAs) are present in all types of cells as well as in organelles. tRNAs of animal mitochondria show a low level of primary sequence conservation and exhibit ‘bizarre’ secondary structures, lacking complete domains of the common cloverleaf. Such sequences are hard to detect and hence frequently missed in computational analyses and mitochondrial genome annotation. Here, we introduce an automatic annotation procedure for mitochondrial tRNA genes in Metazoa based on sequence and structural information in manually curated covariance models. The method, applied to re-annotate 1876 available metazoan mitochondrial RefSeq genomes, allows to distinguish between remaining functional genes and degrading ‘pseudogenes’, even at early stages of divergence. The subsequent analysis of a comprehensive set of mitochondrial tRNA genes gives new insights into the evolution of structures of mitochondrial tRNA sequences as well as into the mechanisms of genome rearrangements. We find frequent losses of tRNA genes concentrated in basal Metazoa, frequent independent losses of individual parts of tRNA genes, particularly in Arthropoda, and wide-spread conserved overlaps of tRNAs in opposite reading direction. Direct evidence for several recent Tandem Duplication-Random Loss events is gained, demonstrating that this mechanism has an impact on the appearance of new mitochondrial gene orders. PMID:22139921

  17. Biomedical article retrieval using multimodal features and image annotations in region-based CBIR

    NASA Astrophysics Data System (ADS)

    You, Daekeun; Antani, Sameer; Demner-Fushman, Dina; Rahman, Md Mahmudur; Govindaraju, Venu; Thoma, George R.

    2010-01-01

    Biomedical images are invaluable in establishing diagnosis, acquiring technical skills, and implementing best practices in many areas of medicine. At present, images needed for instructional purposes or in support of clinical decisions appear in specialized databases and in biomedical articles, and are often not easily accessible to retrieval tools. Our goal is to automatically annotate images extracted from scientific publications with respect to their usefulness for clinical decision support and instructional purposes, and project the annotations onto images stored in databases by linking images through content-based image similarity. Authors often use text labels and pointers overlaid on figures and illustrations in the articles to highlight regions of interest (ROI). These annotations are then referenced in the caption text or figure citations in the article text. In previous research we have developed two methods (a heuristic and dynamic time warping-based methods) for localizing and recognizing such pointers on biomedical images. In this work, we add robustness to our previous efforts by using a machine learning based approach to localizing and recognizing the pointers. Identifying these can assist in extracting relevant image content at regions within the image that are likely to be highly relevant to the discussion in the article text. Image regions can then be annotated using biomedical concepts from extracted snippets of text pertaining to images in scientific biomedical articles that are identified using National Library of Medicine's Unified Medical Language System® (UMLS) Metathesaurus. The resulting regional annotation and extracted image content are then used as indices for biomedical article retrieval using the multimodal features and region-based content-based image retrieval (CBIR) techniques. The hypothesis that such an approach would improve biomedical document retrieval is validated through experiments on an expert-marked biomedical article

  18. IMPROVED SEARCH OF PRINCIPAL COMPONENT ANALYSIS DATABASES FOR SPECTRO-POLARIMETRIC INVERSION

    SciTech Connect

    Casini, R.; Lites, B. W.; Ramos, A. Asensio

    2013-08-20

    We describe a simple technique for the acceleration of spectro-polarimetric inversions based on principal component analysis (PCA) of Stokes profiles. This technique involves the indexing of the database models based on the sign of the projections (PCA coefficients) of the first few relevant orders of principal components of the four Stokes parameters. In this way, each model in the database can be attributed a distinctive binary number of 2{sup 4n} bits, where n is the number of PCA orders used for the indexing. Each of these binary numbers (indices) identifies a group of ''compatible'' models for the inversion of a given set of observed Stokes profiles sharing the same index. The complete set of the binary numbers so constructed evidently determines a partition of the database. The search of the database for the PCA inversion of spectro-polarimetric data can profit greatly from this indexing. In practical cases it becomes possible to approach the ideal acceleration factor of 2{sup 4n} as compared to the systematic search of a non-indexed database for a traditional PCA inversion. This indexing method relies on the existence of a physical meaning in the sign of the PCA coefficients of a model. For this reason, the presence of model ambiguities and of spectro-polarimetric noise in the observations limits in practice the number n of relevant PCA orders that can be used for the indexing.

  19. Improved Search of Principal Component Analysis Databases for Spectro-polarimetric Inversion

    NASA Astrophysics Data System (ADS)

    Casini, R.; Asensio Ramos, A.; Lites, B. W.; López Ariste, A.

    2013-08-01

    We describe a simple technique for the acceleration of spectro-polarimetric inversions based on principal component analysis (PCA) of Stokes profiles. This technique involves the indexing of the database models based on the sign of the projections (PCA coefficients) of the first few relevant orders of principal components of the four Stokes parameters. In this way, each model in the database can be attributed a distinctive binary number of 24n bits, where n is the number of PCA orders used for the indexing. Each of these binary numbers (indices) identifies a group of "compatible" models for the inversion of a given set of observed Stokes profiles sharing the same index. The complete set of the binary numbers so constructed evidently determines a partition of the database. The search of the database for the PCA inversion of spectro-polarimetric data can profit greatly from this indexing. In practical cases it becomes possible to approach the ideal acceleration factor of 24n as compared to the systematic search of a non-indexed database for a traditional PCA inversion. This indexing method relies on the existence of a physical meaning in the sign of the PCA coefficients of a model. For this reason, the presence of model ambiguities and of spectro-polarimetric noise in the observations limits in practice the number n of relevant PCA orders that can be used for the indexing.

  20. Improved locus-specific database for OPA1 mutations allows inclusion of advanced clinical data.

    PubMed

    Ferré, Marc; Caignard, Angélique; Milea, Dan; Leruez, Stéphanie; Cassereau, Julien; Chevrollier, Arnaud; Amati-Bonneau, Patrizia; Verny, Christophe; Bonneau, Dominique; Procaccio, Vincent; Reynier, Pascal

    2015-01-01

    Autosomal-dominant optic atrophy (ADOA) is the most common inherited optic neuropathy, due to mutations in the optic atrophy 1 gene (OPA1) in about 60%-80% of cases. At present, the clinical heterogeneity of patients carrying OPA1 variants renders genotype-phenotype correlations difficulty. Since 2005, when we published the first locus-specific database (LSDB) dedicated to OPA1, a large amount of new clinical and genetic knowledge has emerged, prompting us to update this database. We have used the Leiden Open-Source Variation Database to develop a clinico-biological database, aiming to add clinical phenotypes related to OPA1 variants. As a first step, we validated this new database by registering several patients previously reported in the literature, as well as new patients from our own institution. Contributors may now make online submissions of clinical and molecular descriptions of phenotypes due to OPA1 variants, including detailed ophthalmological and neurological data, with due respect to patient anonymity. The updated OPA1 LSDB (http://opa1.mitodyn.org/) should prove useful for molecular diagnoses, large-scale variant statistics, and genotype-phenotype correlations in ADOA studies.

  1. The Vertebrate Genome Annotation browser 10 years on

    PubMed Central

    Harrow, Jennifer L.; Steward, Charles A.; Frankish, Adam; Gilbert, James G.; Gonzalez, Jose M.; Loveland, Jane E.; Mudge, Jonathan; Sheppard, Dan; Thomas, Mark; Trevanion, Stephen; Wilming, Laurens G.

    2014-01-01

    The Vertebrate Genome Annotation (VEGA) database (http://vega.sanger.ac.uk), initially designed as a community resource for browsing manual annotation of the human genome project, now contains five reference genomes (human, mouse, zebrafish, pig and rat). Its introduction pages have been redesigned to enable the user to easily navigate between whole genomes and smaller multi-species haplotypic regions of interest such as the major histocompatibility complex. The VEGA browser is unique in that annotation is updated via the Human And Vertebrate Analysis aNd Annotation (HAVANA) update track every 2 weeks, allowing single gene updates to be made publicly available to the research community quickly. The user can now access different haplotypic subregions more easily, such as those from the non-obese diabetic mouse, and display them in a more intuitive way using the comparative tools. We also highlight how the user can browse manually annotated updated patches from the Genome Reference Consortium (GRC). PMID:24316575

  2. ORegAnno 3.0: a community-driven resource for curated regulatory annotation.

    PubMed

    Lesurf, Robert; Cotto, Kelsy C; Wang, Grace; Griffith, Malachi; Kasaian, Katayoon; Jones, Steven J M; Montgomery, Stephen B; Griffith, Obi L

    2016-01-01

    The Open Regulatory Annotation database (ORegAnno) is a resource for curated regulatory annotation. It contains information about regulatory regions, transcription factor binding sites, RNA binding sites, regulatory variants, haplotypes, and other regulatory elements. ORegAnno differentiates itself from other regulatory resources by facilitating crowd-sourced interpretation and annotation of regulatory observations from the literature and highly curated resources. It contains a comprehensive annotation scheme that aims to describe both the elements and outcomes of regulatory events. Moreover, ORegAnno assembles these disparate data sources and annotations into a single, high quality catalogue of curated regulatory information. The current release is an update of the database previously featured in the NAR Database Issue, and now contains 1 948 307 records, across 18 species, with a combined coverage of 334 215 080 bp. Complete records, annotation, and other associated data are available for browsing and download at http://www.oreganno.org/.

  3. Complementary use of the SciSearch database for improved biomedical information searching.

    PubMed Central

    Brown, C M

    1998-01-01

    The use of at least two complementary online biomedical databases is generally considered critical for biomedical scientists seeking to keep fully abreast of recent research developments as well as to retrieve the highest number of relevant citations possible. Although the National Library of Medicine's MEDLINE is usually the database of choice, this paper illustrates the benefits of using another database, the Institute for Scientific Information's SciSearch, when conducting a biomedical information search. When a simple query about red wine consumption and coronary artery disease was posed simultaneously in both MEDLINE and SciSearch, a greater number of relevant citations were retrieved through SciSearch. This paper also provides suggestions for carrying out a comprehensive biomedical literature search in a rapid and efficient manner by using SciSearch in conjunction with MEDLINE. PMID:9549014

  4. Improving HJ-1B IRS land surface temperature product using ASTER global emissivity database

    NASA Astrophysics Data System (ADS)

    Li, H.; Hu, T.; Meng, X.; Yongming, D.; Cao, B.; Liu, Q.

    2015-12-01

    Land surface temperature (LST) is a key parameter for hydrological, meteorological, climatological and environmental studies. Currently many operational LST products have been generated using European and American satellite data, i.e., the Advanced Very High Resolution Radiometer (AVHRR), Advanced Along-Track Scanning Radiometer (AATSR) and Moderate Resolution Imaging Spectroradiometer (MODIS). However, few LST product has been produced using Chinese satellite data. Thus, the objective of this study is to generate reliable LST product using Chinese HJ-1B satellite data. The HJ-1B satellite of China, were launched on September 6, 2008, which are used for disaster and environment monitoring. IRS (Infrared Scanner) is one of the key instruments onboard HJ-1B satellite, it can scan the earth every four days, has four spectral bands ranging from the near-infrared to thermal infrared bands (band 1 0.75 - 1.10μm, band 2 1.55-1.75μm, MIR band 3 3.50 - 3.90μm, band 4 10.5-12.5μm) with 720 km swath. It scans ±29° from nadir and the spatial resolution for band1-3 is 150m and 300m for band4. In this study, a single-channel parametric model (SC-PM) algorithm were used to produce 300m LST product from HJ-1B IRS data. The NCEP atmospheric profiles and a parametric model were used for atmospheric correction. In order to improve the accuracy of the land surface emissivity (LSE), the 1km ASTER Global Emissivity Database (GED) and self-developed 5-day 1km vegetation cover product were used for estimating the LSE based on the Vegetation Cover Method. Two years of HJ-1B IRS LST product in Heihe River basin (Gansu province, China) from June 2012 to June 2014 were generated. The LST products were evaluated against ground observations in an arid area of northwest China during the Heihe Watershed Allied Telemetry Experimental Research (HiWATER) experiment. Four barren surface sites and ten vegetated sites were chosen for the evaluation. The results show that the developed HJ-1B IRS

  5. DAS Writeback: A Collaborative Annotation System

    PubMed Central

    2011-01-01

    Background Centralised resources such as GenBank and UniProt are perfect examples of the major international efforts that have been made to integrate and share biological information. However, additional data that adds value to these resources needs a simple and rapid route to public access. The Distributed Annotation System (DAS) provides an adequate environment to integrate genomic and proteomic information from multiple sources, making this information accessible to the community. DAS offers a way to distribute and access information but it does not provide domain experts with the mechanisms to participate in the curation process of the available biological entities and their annotations. Results We designed and developed a Collaborative Annotation System for proteins called DAS Writeback. DAS writeback is a protocol extension of DAS to provide the functionalities of adding, editing and deleting annotations. We implemented this new specification as extensions of both a DAS server and a DAS client. The architecture was designed with the involvement of the DAS community and it was improved after performing usability experiments emulating a real annotation task. Conclusions We demonstrate that DAS Writeback is effective, usable and will provide the appropriate environment for the creation and evolution of community protein annotation. PMID:21569281

  6. The Coral Triangle Atlas: an integrated online spatial database system for improving coral reef management.

    PubMed

    Cros, Annick; Ahamad Fatan, Nurulhuda; White, Alan; Teoh, Shwu Jiau; Tan, Stanley; Handayani, Christian; Huang, Charles; Peterson, Nate; Venegas Li, Ruben; Siry, Hendra Yusran; Fitriana, Ria; Gove, Jamison; Acoba, Tomoko; Knight, Maurice; Acosta, Renerio; Andrew, Neil; Beare, Doug

    2014-01-01

    In this paper we describe the construction of an online GIS database system, hosted by WorldFish, which stores bio-physical, ecological and socio-economic data for the 'Coral Triangle Area' in South-east Asia and the Pacific. The database has been built in partnership with all six (Timor-Leste, Malaysia, Indonesia, The Philippines, Solomon Islands and Papua New Guinea) of the Coral Triangle countries, and represents a valuable source of information for natural resource managers at the regional scale. Its utility is demonstrated using biophysical data, data summarising marine habitats, and data describing the extent of marine protected areas in the region.

  7. The Coral Triangle Atlas: An Integrated Online Spatial Database System for Improving Coral Reef Management

    PubMed Central

    Cros, Annick; Ahamad Fatan, Nurulhuda; White, Alan; Teoh, Shwu Jiau; Tan, Stanley; Handayani, Christian; Huang, Charles; Peterson, Nate; Venegas Li, Ruben; Siry, Hendra Yusran; Fitriana, Ria; Gove, Jamison; Acoba, Tomoko; Knight, Maurice; Acosta, Renerio; Andrew, Neil; Beare, Doug

    2014-01-01

    In this paper we describe the construction of an online GIS database system, hosted by WorldFish, which stores bio-physical, ecological and socio-economic data for the ‘Coral Triangle Area’ in South-east Asia and the Pacific. The database has been built in partnership with all six (Timor-Leste, Malaysia, Indonesia, The Philippines, Solomon Islands and Papua New Guinea) of the Coral Triangle countries, and represents a valuable source of information for natural resource managers at the regional scale. Its utility is demonstrated using biophysical data, data summarising marine habitats, and data describing the extent of marine protected areas in the region. PMID:24941442

  8. Human Genome Annotation

    NASA Astrophysics Data System (ADS)

    Gerstein, Mark

    A central problem for 21st century science is annotating the human genome and making this annotation useful for the interpretation of personal genomes. My talk will focus on annotating the 99% of the genome that does not code for canonical genes, concentrating on intergenic features such as structural variants (SVs), pseudogenes (protein fossils), binding sites, and novel transcribed RNAs (ncRNAs). In particular, I will describe how we identify regulatory sites and variable blocks (SVs) based on processing next-generation sequencing experiments. I will further explain how we cluster together groups of sites to create larger annotations. Next, I will discuss a comprehensive pseudogene identification pipeline, which has enabled us to identify >10K pseudogenes in the genome and analyze their distribution with respect to age, protein family, and chromosomal location. Throughout, I will try to introduce some of the computational algorithms and approaches that are required for genome annotation. Much of this work has been carried out in the framework of the ENCODE, modENCODE, and 1000 genomes projects.

  9. IUPHAR-DB: updated database content and new features.

    PubMed

    Sharman, Joanna L; Benson, Helen E; Pawson, Adam J; Lukito, Veny; Mpamhanga, Chidochangu P; Bombail, Vincent; Davenport, Anthony P; Peters, John A; Spedding, Michael; Harmar, Anthony J

    2013-01-01

    The International Union of Basic and Clinical Pharmacology (IUPHAR) database, IUPHAR-DB (http://www.iuphar-db.org) is an open access, online database providing detailed, expert-driven annotation of the primary literature on human and rodent receptors and other drug targets, together with the substances that act on them. The present release includes information on the products of 646 genes from four major protein classes (G protein-coupled receptors, nuclear hormone receptors, voltage- and ligand-gated ion channels) and ∼3180 bioactive molecules (endogenous ligands, licensed drugs and key pharmacological tools) that interact with them. We have described previously the classification and curation of data for small molecule ligands in the database; in this update we have annotated 366 endogenous peptide ligands with their amino acid sequences, post-translational modifications, links to precursor genes, species differences and relationships with other molecules in the database (e.g. those derived from the same precursor). We have also matched targets with their endogenous ligands (peptides and small molecules), with particular attention paid to identifying bioactive peptide ligands generated by post-translational modification of precursor proteins. Other improvements to the database include enhanced information on the clinical relevance of targets and ligands in the database, more extensive links to other databases and a pilot project for the curation of enzymes as drug targets.

  10. IUPHAR-DB: updated database content and new features

    PubMed Central

    Sharman, Joanna L.; Benson, Helen E.; Pawson, Adam J.; Lukito, Veny; Mpamhanga, Chidochangu P.; Bombail, Vincent; Davenport, Anthony P.; Peters, John A.; Spedding, Michael; Harmar, Anthony J.; NC-IUPHAR

    2013-01-01

    The International Union of Basic and Clinical Pharmacology (IUPHAR) database, IUPHAR-DB (http://www.iuphar-db.org) is an open access, online database providing detailed, expert-driven annotation of the primary literature on human and rodent receptors and other drug targets, together with the substances that act on them. The present release includes information on the products of 646 genes from four major protein classes (G protein-coupled receptors, nuclear hormone receptors, voltage- and ligand-gated ion channels) and ∼3180 bioactive molecules (endogenous ligands, licensed drugs and key pharmacological tools) that interact with them. We have described previously the classification and curation of data for small molecule ligands in the database; in this update we have annotated 366 endogenous peptide ligands with their amino acid sequences, post-translational modifications, links to precursor genes, species differences and relationships with other molecules in the database (e.g. those derived from the same precursor). We have also matched targets with their endogenous ligands (peptides and small molecules), with particular attention paid to identifying bioactive peptide ligands generated by post-translational modification of precursor proteins. Other improvements to the database include enhanced information on the clinical relevance of targets and ligands in the database, more extensive links to other databases and a pilot project for the curation of enzymes as drug targets. PMID:23087376

  11. Gene ontology annotation by density and gravitation models.

    PubMed

    Hou, Wen-Juan; Lin, Kevin Hsin-Yih; Chen, Hsin-Hsi

    2006-01-01

    Gene Ontology (GO) is developed to provide standard vocabularies of gene products in different databases. The process of annotating GO terms to genes requires curators to read through lengthy articles. Methods for speeding up or automating the annotation process are thus of great importance. We propose a GO annotation approach using full-text biomedical documents for directing more relevant papers to curators. This system explores word density and gravitation relationships between genes and GO terms. Different density and gravitation models are built and several evaluation criteria are employed to assess the effects of the proposed methods. PMID:17503384

  12. An annotation system for 3D fluid flow visualization

    NASA Technical Reports Server (NTRS)

    Loughlin, Maria M.; Hughes, John F.

    1995-01-01

    Annotation is a key activity of data analysis. However, current systems for data analysis focus almost exclusively on visualization. We propose a system which integrates annotations into a visualization system. Annotations are embedded in 3D data space, using the Post-it metaphor. This embedding allows contextual-based information storage and retrieval, and facilitates information sharing in collaborative environments. We provide a traditional database filter and a Magic Lens filter to create specialized views of the data. The system has been customized for fluid flow applications, with features which allow users to store parameters of visualization tools and sketch 3D volumes.

  13. Gene ontology annotation by density and gravitation models.

    PubMed

    Hou, Wen-Juan; Lin, Kevin Hsin-Yih; Chen, Hsin-Hsi

    2006-01-01

    Gene Ontology (GO) is developed to provide standard vocabularies of gene products in different databases. The process of annotating GO terms to genes requires curators to read through lengthy articles. Methods for speeding up or automating the annotation process are thus of great importance. We propose a GO annotation approach using full-text biomedical documents for directing more relevant papers to curators. This system explores word density and gravitation relationships between genes and GO terms. Different density and gravitation models are built and several evaluation criteria are employed to assess the effects of the proposed methods.

  14. The UCSC Genome Browser database: 2016 update.

    PubMed

    Speir, Matthew L; Zweig, Ann S; Rosenbloom, Kate R; Raney, Brian J; Paten, Benedict; Nejad, Parisa; Lee, Brian T; Learned, Katrina; Karolchik, Donna; Hinrichs, Angie S; Heitner, Steve; Harte, Rachel A; Haeussler, Maximilian; Guruvadoo, Luvina; Fujita, Pauline A; Eisenhart, Christopher; Diekhans, Mark; Clawson, Hiram; Casper, Jonathan; Barber, Galt P; Haussler, David; Kuhn, Robert M; Kent, W James

    2016-01-01

    For the past 15 years, the UCSC Genome Browser (http://genome.ucsc.edu/) has served the international research community by offering an integrated platform for viewing and analyzing information from a large database of genome assemblies and their associated annotations. The UCSC Genome Browser has been under continuous development since its inception with new data sets and software features added frequently. Some release highlights of this year include new and updated genome browsers for various assemblies, including bonobo and zebrafish; new gene annotation sets; improvements to track and assembly hub support; and a new interactive tool, the "Data Integrator", for intersecting data from multiple tracks. We have greatly expanded the data sets available on the most recent human assembly, hg38/GRCh38, to include updated gene prediction sets from GENCODE, more phenotype- and disease-associated variants from ClinVar and ClinGen, more genomic regulatory data, and a new multiple genome alignment.

  15. The UCSC Genome Browser database: 2016 update.

    PubMed

    Speir, Matthew L; Zweig, Ann S; Rosenbloom, Kate R; Raney, Brian J; Paten, Benedict; Nejad, Parisa; Lee, Brian T; Learned, Katrina; Karolchik, Donna; Hinrichs, Angie S; Heitner, Steve; Harte, Rachel A; Haeussler, Maximilian; Guruvadoo, Luvina; Fujita, Pauline A; Eisenhart, Christopher; Diekhans, Mark; Clawson, Hiram; Casper, Jonathan; Barber, Galt P; Haussler, David; Kuhn, Robert M; Kent, W James

    2016-01-01

    For the past 15 years, the UCSC Genome Browser (http://genome.ucsc.edu/) has served the international research community by offering an integrated platform for viewing and analyzing information from a large database of genome assemblies and their associated annotations. The UCSC Genome Browser has been under continuous development since its inception with new data sets and software features added frequently. Some release highlights of this year include new and updated genome browsers for various assemblies, including bonobo and zebrafish; new gene annotation sets; improvements to track and assembly hub support; and a new interactive tool, the "Data Integrator", for intersecting data from multiple tracks. We have greatly expanded the data sets available on the most recent human assembly, hg38/GRCh38, to include updated gene prediction sets from GENCODE, more phenotype- and disease-associated variants from ClinVar and ClinGen, more genomic regulatory data, and a new multiple genome alignment. PMID:26590259

  16. The Genopolis Microarray Database

    PubMed Central

    Splendiani, Andrea; Brandizi, Marco; Even, Gael; Beretta, Ottavio; Pavelka, Norman; Pelizzola, Mattia; Mayhaus, Manuel; Foti, Maria; Mauri, Giancarlo; Ricciardi-Castagnoli, Paola

    2007-01-01

    Background Gene expression databases are key resources for microarray data management and analysis and the importance of a proper annotation of their content is well understood. Public repositories as well as microarray database systems that can be implemented by single laboratories exist. However, there is not yet a tool that can easily support a collaborative environment where different users with different rights of access to data can interact to define a common highly coherent content. The scope of the Genopolis database is to provide a resource that allows different groups performing microarray experiments related to a common subject to create a common coherent knowledge base and to analyse it. The Genopolis database has been implemented as a dedicated system for the scientific community studying dendritic and macrophage cells functions and host-parasite interactions. Results The Genopolis Database system allows the community to build an object based MIAME compliant annotation of their experiments and to store images, raw and processed data from the Affymetrix GeneChip® platform. It supports dynamical definition of controlled vocabularies and provides automated and supervised steps to control the coherence of data and annotations. It allows a precise control of the visibility of the database content to different sub groups in the community and facilitates exports of its content to public repositories. It provides an interactive users interface for data analysis: this allows users to visualize data matrices based on functional lists and sample characterization, and to navigate to other data matrices defined by similarity of expression values as well as functional characterizations of genes involved. A collaborative environment is also provided for the definition and sharing of functional annotation by users. Conclusion The Genopolis Database supports a community in building a common coherent knowledge base and analyse it. This fills a gap between a local

  17. The GATO gene annotation tool for research laboratories.

    PubMed

    Fujita, A; Massirer, K B; Durham, A M; Ferreira, C E; Sogayar, M C

    2005-11-01

    Large-scale genome projects have generated a rapidly increasing number of DNA sequences. Therefore, development of computational methods to rapidly analyze these sequences is essential for progress in genomic research. Here we present an automatic annotation system for preliminary analysis of DNA sequences. The gene annotation tool (GATO) is a Bioinformatics pipeline designed to facilitate routine functional annotation and easy access to annotated genes. It was designed in view of the frequent need of genomic researchers to access data pertaining to a common set of genes. In the GATO system, annotation is generated by querying some of the Web-accessible resources and the information is stored in a local database, which keeps a record of all previous annotation results. GATO may be accessed from everywhere through the internet or may be run locally if a large number of sequences are going to be annotated. It is implemented in PHP and Perl and may be run on any suitable Web server. Usually, installation and application of annotation systems require experience and are time consuming, but GATO is simple and practical, allowing anyone with basic skills in informatics to access it without any special training. GATO can be downloaded at [http://mariwork.iq.usp.br/gato/]. Minimum computer free space required is 2 MB. PMID:16258624

  18. Global Mapping of Traditional Chinese Medicine into Bioactivity Space and Pathways Annotation Improves Mechanistic Understanding and Discovers Relationships between Therapeutic Action (Sub)classes

    PubMed Central

    Mohamad Zobir, Siti Zuraidah; Mohd Fauzi, Fazlin; Liggi, Sonia; Drakakis, Georgios; Fu, Xianjun; Fan, Tai-Ping; Bender, Andreas

    2016-01-01

    Traditional Chinese medicine (TCM) still needs more scientific rationale to be proven for it to be accepted further in the West. We are now in the position to propose computational hypotheses for the mode-of-actions (MOAs) of 45 TCM therapeutic action (sub)classes from in silico target prediction algorithms, whose target was later annotated with Kyoto Encyclopedia of Genes and Genomes pathway, and to discover the relationship between them by generating a hierarchical clustering. The results of 10,749 TCM compounds showed 183 enriched targets and 99 enriched pathways from Estimation Score ≤ 0 and ≥ 5% of compounds/targets in a (sub)class. The MOA of a (sub)class was established from supporting literature. Overall, the most frequent top three enriched targets/pathways were immune-related targets such as tyrosine-protein phosphatase nonreceptor type 2 (PTPN2) and digestive system such as mineral absorption. We found two major protein families, G-protein coupled receptor (GPCR), and protein kinase family contributed to the diversity of the bioactivity space, while digestive system was consistently annotated pathway motif, which agreed with the important treatment principle of TCM, “the foundation of acquired constitution” that includes spleen and stomach. In short, the TCM (sub)classes, in many cases share similar targets/pathways despite having different indications. PMID:26989424

  19. Global Mapping of Traditional Chinese Medicine into Bioactivity Space and Pathways Annotation Improves Mechanistic Understanding and Discovers Relationships between Therapeutic Action (Sub)classes.

    PubMed

    Mohamad Zobir, Siti Zuraidah; Mohd Fauzi, Fazlin; Liggi, Sonia; Drakakis, Georgios; Fu, Xianjun; Fan, Tai-Ping; Bender, Andreas

    2016-01-01

    Traditional Chinese medicine (TCM) still needs more scientific rationale to be proven for it to be accepted further in the West. We are now in the position to propose computational hypotheses for the mode-of-actions (MOAs) of 45 TCM therapeutic action (sub)classes from in silico target prediction algorithms, whose target was later annotated with Kyoto Encyclopedia of Genes and Genomes pathway, and to discover the relationship between them by generating a hierarchical clustering. The results of 10,749 TCM compounds showed 183 enriched targets and 99 enriched pathways from Estimation Score ≤ 0 and ≥ 5% of compounds/targets in a (sub)class. The MOA of a (sub)class was established from supporting literature. Overall, the most frequent top three enriched targets/pathways were immune-related targets such as tyrosine-protein phosphatase nonreceptor type 2 (PTPN2) and digestive system such as mineral absorption. We found two major protein families, G-protein coupled receptor (GPCR), and protein kinase family contributed to the diversity of the bioactivity space, while digestive system was consistently annotated pathway motif, which agreed with the important treatment principle of TCM, "the foundation of acquired constitution" that includes spleen and stomach. In short, the TCM (sub)classes, in many cases share similar targets/pathways despite having different indications.

  20. ProbMetab: an R package for Bayesian probabilistic annotation of LC-MS-based metabolomics.

    PubMed

    Silva, Ricardo R; Jourdan, Fabien; Salvanha, Diego M; Letisse, Fabien; Jamin, Emilien L; Guidetti-Gonzalez, Simone; Labate, Carlos A; Vêncio, Ricardo Z N

    2014-05-01

    We present ProbMetab, an R package that promotes substantial improvement in automatic probabilistic liquid chromatography-mass spectrometry-based metabolome annotation. The inference engine core is based on a Bayesian model implemented to (i) allow diverse source of experimental data and metadata to be systematically incorporated into the model with alternative ways to calculate the likelihood function and (ii) allow sensitive selection of biologically meaningful biochemical reaction databases as Dirichlet-categorical prior distribution. Additionally, to ensure result interpretation by system biologists, we display the annotation in a network where observed mass peaks are connected if their candidate metabolites are substrate/product of known biochemical reactions. This graph can be overlaid with other graph-based analysis, such as partial correlation networks, in a visualization scheme exported to Cytoscape, with web and stand-alone versions. PMID:24443383

  1. Understanding the improved sensitivity of spectral library searching over sequence database searching in proteomics data analysis.

    PubMed

    Zhang, Xin; Li, Yunzi; Shao, Wenguang; Lam, Henry

    2011-03-01

    Spectral library searching has been recently proposed as an alternative to sequence database searching for peptide identification from MS/MS. We performed a systematic comparison between spectral library searching and sequence database searching using a wide variety of data to better demonstrate, and understand, the superior sensitivity of the former observed in preliminary studies. By decoupling the effect of search space, we demonstrated that the success of spectral library searching is primarily attributable to the use of real library spectra for matching, without which the sensitivity advantage largely disappears. We further determined the extent to which the use of real peak intensities and non-canonical fragments, both under-utilized information in sequence database searching, contributes to the sensitivity advantage. Lastly, we showed that spectral library searching is disproportionately more successful in identifying low-quality spectra, and complex spectra of higher- charged precursors, both important frontiers in peptide sequencing. Our results answered important outstanding questions about this promising yet unproven method using well-controlled computational experiments and sound statistical approaches.

  2. Annotation of Ehux ESTs

    SciTech Connect

    Kuo, Alan; Grigoriev, Igor

    2009-06-12

    22 percent ESTs do no align with scaffolds. EST Pipeleine assembles 17126 consensi from the noaligned ESTs. Annotation Pipeline predicts 8564 ORFS on the consensi. Domain analysis of ORFs reveals missing genes. Cluster analysis reveals missing genes. Expression analysis reveals potential strain specific genes.

  3. Annotation: The Savant Syndrome

    ERIC Educational Resources Information Center

    Heaton, Pamela; Wallace, Gregory L.

    2004-01-01

    Background: Whilst interest has focused on the origin and nature of the savant syndrome for over a century, it is only within the past two decades that empirical group studies have been carried out. Methods: The following annotation briefly reviews relevant research and also attempts to address outstanding issues in this research area.…

  4. Intellectuals in China: Annotations.

    ERIC Educational Resources Information Center

    Parker, Franklin

    This annotated bibliography of 72 books, journal articles, government reports, and newspaper feature stories focuses on the changing role of intellectuals in China, primarily since the 1949 Chinese Revolution. Particular attention is given to the Hundred Flowers Movement of 1957 and the Cultural Revolution. Most of the cited works are in English,…

  5. Collaborative Movie Annotation

    NASA Astrophysics Data System (ADS)

    Zad, Damon Daylamani; Agius, Harry

    In this paper, we focus on metadata for self-created movies like those found on YouTube and Google Video, the duration of which are increasing in line with falling upload restrictions. While simple tags may have been sufficient for most purposes for traditionally very short video footage that contains a relatively small amount of semantic content, this is not the case for movies of longer duration which embody more intricate semantics. Creating metadata is a time-consuming process that takes a great deal of individual effort; however, this effort can be greatly reduced by harnessing the power of Web 2.0 communities to create, update and maintain it. Consequently, we consider the annotation of movies within Web 2.0 environments, such that users create and share that metadata collaboratively and propose an architecture for collaborative movie annotation. This architecture arises from the results of an empirical experiment where metadata creation tools, YouTube and an MPEG-7 modelling tool, were used by users to create movie metadata. The next section discusses related work in the areas of collaborative retrieval and tagging. Then, we describe the experiments that were undertaken on a sample of 50 users. Next, the results are presented which provide some insight into how users interact with existing tools and systems for annotating movies. Based on these results, the paper then develops an architecture for collaborative movie annotation.

  6. Annotated Bibliography. First Edition.

    ERIC Educational Resources Information Center

    Haring, Norris G.

    An annotated bibliography which presents approximately 300 references from 1951 to 1973 on the education of severely/profoundly handicapped persons. Citations are grouped alphabetically by author's name within the following categories: characteristics and treatment, gross motor development, sensory and motor development, physical therapy for the…

  7. Ghostwriting: An Annotated Bibliography.

    ERIC Educational Resources Information Center

    Simmons, Donald B.

    Drawn from communication journals, historical and news magazines, business and industrial magazines, political science and world affairs journals, general interest periodicals, and literary and political review magazines, the approximately 90 entries in this annotated bibliography discuss ghostwriting as practiced through the ages and reveal the…

  8. Mouse genome database 2016.

    PubMed

    Bult, Carol J; Eppig, Janan T; Blake, Judith A; Kadin, James A; Richardson, Joel E

    2016-01-01

    The Mouse Genome Database (MGD; http://www.informatics.jax.org) is the primary community model organism database for the laboratory mouse and serves as the source for key biological reference data related to mouse genes, gene functions, phenotypes and disease models with a strong emphasis on the relationship of these data to human biology and disease. As the cost of genome-scale sequencing continues to decrease and new technologies for genome editing become widely adopted, the laboratory mouse is more important than ever as a model system for understanding the biological significance of human genetic variation and for advancing the basic research needed to support the emergence of genome-guided precision medicine. Recent enhancements to MGD include new graphical summaries of biological annotations for mouse genes, support for mobile access to the database, tools to support the annotation and analysis of sets of genes, and expanded support for comparative biology through the expansion of homology data.

  9. Mouse genome database 2016

    PubMed Central

    Bult, Carol J.; Eppig, Janan T.; Blake, Judith A.; Kadin, James A.; Richardson, Joel E.

    2016-01-01

    The Mouse Genome Database (MGD; http://www.informatics.jax.org) is the primary community model organism database for the laboratory mouse and serves as the source for key biological reference data related to mouse genes, gene functions, phenotypes and disease models with a strong emphasis on the relationship of these data to human biology and disease. As the cost of genome-scale sequencing continues to decrease and new technologies for genome editing become widely adopted, the laboratory mouse is more important than ever as a model system for understanding the biological significance of human genetic variation and for advancing the basic research needed to support the emergence of genome-guided precision medicine. Recent enhancements to MGD include new graphical summaries of biological annotations for mouse genes, support for mobile access to the database, tools to support the annotation and analysis of sets of genes, and expanded support for comparative biology through the expansion of homology data. PMID:26578600

  10. Mouse genome database 2016.

    PubMed

    Bult, Carol J; Eppig, Janan T; Blake, Judith A; Kadin, James A; Richardson, Joel E

    2016-01-01

    The Mouse Genome Database (MGD; http://www.informatics.jax.org) is the primary community model organism database for the laboratory mouse and serves as the source for key biological reference data related to mouse genes, gene functions, phenotypes and disease models with a strong emphasis on the relationship of these data to human biology and disease. As the cost of genome-scale sequencing continues to decrease and new technologies for genome editing become widely adopted, the laboratory mouse is more important than ever as a model system for understanding the biological significance of human genetic variation and for advancing the basic research needed to support the emergence of genome-guided precision medicine. Recent enhancements to MGD include new graphical summaries of biological annotations for mouse genes, support for mobile access to the database, tools to support the annotation and analysis of sets of genes, and expanded support for comparative biology through the expansion of homology data. PMID:26578600

  11. Effective function annotation through catalytic residue conservation.

    PubMed

    George, Richard A; Spriggs, Ruth V; Bartlett, Gail J; Gutteridge, Alex; MacArthur, Malcolm W; Porter, Craig T; Al-Lazikani, Bissan; Thornton, Janet M; Swindells, Mark B

    2005-08-30

    Because of the extreme impact of genome sequencing projects, protein sequences without accompanying experimental data now dominate public databases. Homology searches, by providing an opportunity to transfer functional information between related proteins, have become the de facto way to address this. Although a single, well annotated, close relationship will often facilitate sufficient annotation, this situation is not always the case, particularly if mutations are present in important functional residues. When only distant relationships are available, the transfer of function information is more tenuous, and the likelihood of encountering several well annotated proteins with different functions is increased. The consequence for a researcher is a range of candidate functions with little way of knowing which, if any, are correct. Here, we address the problem directly by introducing a computational approach to accurately identify and segregate related proteins into those with a functional similarity and those where function differs. This approach should find a wide range of applications, including the interpretation of genomics/proteomics data and the prioritization of targets for high-throughput structure determination. The method is generic, but here we concentrate on enzymes and apply high-quality catalytic site data. In addition to providing a series of comprehensive benchmarks to show the overall performance of our approach, we illustrate its utility with specific examples that include the correct identification of haptoglobin as a nonenzymatic relative of trypsin, discrimination of acid-d-amino acid ligases from a much larger ligase pool, and the successful annotation of BioH, a structural genomics target.

  12. Ontological Annotation with WordNet

    SciTech Connect

    Sanfilippo, Antonio P.; Tratz, Stephen C.; Gregory, Michelle L.; Chappell, Alan R.; Whitney, Paul D.; Posse, Christian; Paulson, Patrick R.; Baddeley, Bob; Hohimer, Ryan E.; White, Amanda M.

    2006-06-06

    Semantic Web applications require robust and accurate annotation tools that are capable of automating the assignment of ontological classes to words in naturally occurring text (ontological annotation). Most current ontologies do not include rich lexical databases and are therefore not easily integrated with word sense disambiguation algorithms that are needed to automate ontological annotation. WordNet provides a potentially ideal solution to this problem as it offers a highly structured lexical conceptual representation that has been extensively used to develop word sense disambiguation algorithms. However, WordNet has not been designed as an ontology, and while it can be easily turned into one, the result of doing this would present users with serious practical limitations due to the great number of concepts (synonym sets) it contains. Moreover, mapping WordNet to an existing ontology may be difficult and requires substantial labor. We propose to overcome these limitations by developing an analytical platform that (1) provides a WordNet-based ontology offering a manageable and yet comprehensive set of concept classes, (2) leverages the lexical richness of WordNet to give an extensive characterization of concept class in terms of lexical instances, and (3) integrates a class recognition algorithm that automates the assignment of concept classes to words in naturally occurring text. The ensuing framework makes available an ontological annotation platform that can be effectively integrated with intelligence analysis systems to facilitate evidence marshaling and sustain the creation and validation of inference models.

  13. Automating Ontological Annotation with WordNet

    SciTech Connect

    Sanfilippo, Antonio P.; Tratz, Stephen C.; Gregory, Michelle L.; Chappell, Alan R.; Whitney, Paul D.; Posse, Christian; Paulson, Patrick R.; Baddeley, Bob L.; Hohimer, Ryan E.; White, Amanda M.

    2006-01-22

    Semantic Web applications require robust and accurate annotation tools that are capable of automating the assignment of ontological classes to words in naturally occurring text (ontological annotation). Most current ontologies do not include rich lexical databases and are therefore not easily integrated with word sense disambiguation algorithms that are needed to automate ontological annotation. WordNet provides a potentially ideal solution to this problem as it offers a highly structured lexical conceptual representation that has been extensively used to develop word sense disambiguation algorithms. However, WordNet has not been designed as an ontology, and while it can be easily turned into one, the result of doing this would present users with serious practical limitations due to the great number of concepts (synonym sets) it contains. Moreover, mapping WordNet to an existing ontology may be difficult and requires substantial labor. We propose to overcome these limitations by developing an analytical platform that (1) provides a WordNet-based ontology offering a manageable and yet comprehensive set of concept classes, (2) leverages the lexical richness of WordNet to give an extensive characterization of concept class in terms of lexical instances, and (3) integrates a class recognition algorithm that automates the assignment of concept classes to words in naturally occurring text. The ensuing framework makes available an ontological annotation platform that can be effectively integrated with intelligence analysis systems to facilitate evidence marshaling and sustain the creation and validation of inference models.

  14. CART—a chemical annotation retrieval toolkit

    PubMed Central

    Deghou, Samy; Zeller, Georg; Iskar, Murat; Driessen, Marja; Castillo, Mercedes; van Noort, Vera; Bork, Peer

    2016-01-01

    Motivation: Data on bioactivities of drug-like chemicals are rapidly accumulating in public repositories, creating new opportunities for research in computational systems pharmacology. However, integrative analysis of these data sets is difficult due to prevailing ambiguity between chemical names and identifiers and a lack of cross-references between databases. Results: To address this challenge, we have developed CART, a Chemical Annotation Retrieval Toolkit. As a key functionality, it matches an input list of chemical names into a comprehensive reference space to assign unambiguous chemical identifiers. In this unified space, bioactivity annotations can be easily retrieved from databases covering a wide variety of chemical effects on biological systems. Subsequently, CART can determine annotations enriched in the input set of chemicals and display these in tabular format and interactive network visualizations, thereby facilitating integrative analysis of chemical bioactivity data. Availability and Implementation: CART is available as a Galaxy web service (cart.embl.de). Source code and an easy-to-install command line tool can also be obtained from the web site. Contact: bork@embl.de Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27256313

  15. On the Dynamic RSS Feedbacks of Indoor Fingerprinting Databases for Localization Reliability Improvement.

    PubMed

    Wen, Xiaoyang; Tao, Wenyuan; Own, Chung-Ming; Pan, Zhenjiang

    2016-08-15

    Location data is one of the most widely used context data types in context-aware and ubiquitous computing applications. To support locating applications in indoor environments, numerous systems with different deployment costs and positioning accuracies have been developed over the past decade. One useful method, based on received signal strength (RSS), provides a set of signal transmission access points. However, compiling a remeasurement RSS database involves a high cost, which is impractical in dynamically changing environments, particularly in highly crowded areas. In this study, we propose a dynamic estimation resampling method for certain locations chosen from a set of remeasurement fingerprinting databases. Our proposed method adaptively applies different, newly updated and offline fingerprinting points according to the temporal and spatial strength of the location. To achieve accuracy within a simulated area, the proposed method requires approximately 3% of the feedback to attain a double correctness probability comparable to similar methods; in a real environment, our proposed method can obtain excellent 1 m accuracy errors in the positioning system.

  16. On the Dynamic RSS Feedbacks of Indoor Fingerprinting Databases for Localization Reliability Improvement

    PubMed Central

    Wen, Xiaoyang; Tao, Wenyuan; Own, Chung-Ming; Pan, Zhenjiang

    2016-01-01

    Location data is one of the most widely used context data types in context-aware and ubiquitous computing applications. To support locating applications in indoor environments, numerous systems with different deployment costs and positioning accuracies have been developed over the past decade. One useful method, based on received signal strength (RSS), provides a set of signal transmission access points. However, compiling a remeasurement RSS database involves a high cost, which is impractical in dynamically changing environments, particularly in highly crowded areas. In this study, we propose a dynamic estimation resampling method for certain locations chosen from a set of remeasurement fingerprinting databases. Our proposed method adaptively applies different, newly updated and offline fingerprinting points according to the temporal and spatial strength of the location. To achieve accuracy within a simulated area, the proposed method requires approximately 3% of the feedback to attain a double correctness probability comparable to similar methods; in a real environment, our proposed method can obtain excellent 1 m accuracy errors in the positioning system. PMID:27537879

  17. On the Dynamic RSS Feedbacks of Indoor Fingerprinting Databases for Localization Reliability Improvement.

    PubMed

    Wen, Xiaoyang; Tao, Wenyuan; Own, Chung-Ming; Pan, Zhenjiang

    2016-01-01

    Location data is one of the most widely used context data types in context-aware and ubiquitous computing applications. To support locating applications in indoor environments, numerous systems with different deployment costs and positioning accuracies have been developed over the past decade. One useful method, based on received signal strength (RSS), provides a set of signal transmission access points. However, compiling a remeasurement RSS database involves a high cost, which is impractical in dynamically changing environments, particularly in highly crowded areas. In this study, we propose a dynamic estimation resampling method for certain locations chosen from a set of remeasurement fingerprinting databases. Our proposed method adaptively applies different, newly updated and offline fingerprinting points according to the temporal and spatial strength of the location. To achieve accuracy within a simulated area, the proposed method requires approximately 3% of the feedback to attain a double correctness probability comparable to similar methods; in a real environment, our proposed method can obtain excellent 1 m accuracy errors in the positioning system. PMID:27537879

  18. Automated analysis and annotation of basketball video

    NASA Astrophysics Data System (ADS)

    Saur, Drew D.; Tan, Yap-Peng; Kulkarni, Sanjeev R.; Ramadge, Peter J.

    1997-01-01

    Automated analysis and annotation of video sequences are important for digital video libraries, content-based video browsing and data mining projects. A successful video annotation system should provide users with useful video content summary in a reasonable processing time. Given the wide variety of video genres available today, automatically extracting meaningful video content for annotation still remains hard by using current available techniques. However, a wide range video has inherent structure such that some prior knowledge about the video content can be exploited to improve our understanding of the high-level video semantic content. In this paper, we develop tools and techniques for analyzing structured video by using the low-level information available directly from MPEG compressed video. Being able to work directly in the video compressed domain can greatly reduce the processing time and enhance storage efficiency. As a testbed, we have developed a basketball annotation system which combines the low-level information extracted from MPEG stream with the prior knowledge of basketball video structure to provide high level content analysis, annotation and browsing for events such as wide- angle and close-up views, fast breaks, steals, potential shots, number of possessions and possession times. We expect our approach can also be extended to structured video in other domains.

  19. Nutrition & Adolescent Pregnancy: A Selected Annotated Bibliography.

    ERIC Educational Resources Information Center

    National Agricultural Library (USDA), Washington, DC.

    This annotated bibliography on nutrition and adolescent pregnancy is intended to be a source of technical assistance for nurses, nutritionists, physicians, educators, social workers, and other personnel concerned with improving the health of teenage mothers and their babies. It is divided into two major sections. The first section lists selected…

  20. The MagIC Online Database: Improving the Archive Quality via a New Review System

    NASA Astrophysics Data System (ADS)

    Constable, C.; Minnett, R.; Koppers, A. A.; Tauxe, L.; Jarboe, N. A.

    2011-12-01

    The Magnetics Information Consortium (MagIC) is committed to providing the paleomagnetic, rock magnetic, and affiliated scientific communities on-line access to peer-reviewed, published, and raw data, and interpretations, along with online analytics and visualization tools. The MagIC Database (http://earthref.org/MAGIC/) is growing rapidly with new rock and paleomagnetic datasets being uploaded daily. Users can upload contributions for private viewing in the context of published data in the MagIC Database and can elect to share an unpublished dataset with a small group of users (e.g. collaborators, journal reviewers, editors, etc.). Once the data are published, the contribution can be associated with a citable reference and made visible to the general public. Rock and paleomagnetic studies vary considerably in complexity and types of results. To accommodate these variable datasets, the MagIC Data Model has evolved into a large collection of tables with hundreds of fields available. Many of these are recommended for use, but not required, providing great flexibility to accommodate minimal information available from legacy datasets at the same time as detailed modern studies. These published and contributed results are priceless to the scientific community, but are not easily accessible for further use without appropriate metadata describing the methods employed in the study. MagIC has developed an internal review system to rapidly assess the accuracy and completeness of the metadata used and to ensure appropriate placement and descriptions of data in the contributions. Experts in the field have volunteered as MagIC editors and reviewers: they comment on the technicalities of archiving the data, (not their scientific merit which remains a task for the journal peer-review system), and provide feedback to the contributor. Successfully reviewed contributions are free of data entry errors and misunderstandings about the data model, and fully document the methods in the

  1. Database decomposition of a knowledge-based CAD system in mammography: an ensemble approach to improve detection

    NASA Astrophysics Data System (ADS)

    Mazurowski, Maciej A.; Zurada, Jacek M.; Tourassi, Georgia D.

    2008-03-01

    Although ensemble techniques have been investigated in supervised machine learning, their potential with knowledge-based systems is unexplored. The purpose of this study is to investigate the ensemble approach with a knowledge-based (KB) CAD system for the detection of masses in screening mammograms. The system is designed to determine the presence of a mass in a query mammographic region of interest (ROI) based on its similarity with previously acquired examples of mass and normal cases. Similarity between images is assessed using normalized mutual information. Two different approaches of knowledge database decomposition were investigated to create the ensemble. The first approach was random division of the knowledge database into a pre-specified number of equal size, separate groups. The second approach was based on k-means clustering of the knowledge cases according to common texture features extracted from the ROIs. The ensemble components were fused using a linear classifier. Based on a database of 1820 ROIs (901 masses and 919 and the leave-one-out crossvalidation scheme, the ensemble techniques improved the performance of the original KB-CAD system (A z = 0.86+/-0.01). Specifically, random division resulted in ROC area index of A z = 0.90 +/- 0.01 while k-means clustering provided further improvement (A z = 0.91 +/- 0.01). Although marginally better, the improvement was statistically significant. The superiority of the k-means clustering scheme was robust regardless of the number of clusters. This study supports the idea of incorporation of ensemble techniques with knowledge-based systems in mammography.

  2. The OMA orthology database in 2015: function predictions, better plant support, synteny view and other improvements.

    PubMed

    Altenhoff, Adrian M; Škunca, Nives; Glover, Natasha; Train, Clément-Marie; Sueki, Anna; Piližota, Ivana; Gori, Kevin; Tomiczek, Bartlomiej; Müller, Steven; Redestig, Henning; Gonnet, Gaston H; Dessimoz, Christophe

    2015-01-01

    The Orthologous Matrix (OMA) project is a method and associated database inferring evolutionary relationships amongst currently 1706 complete proteomes (i.e. the protein sequence associated for every protein-coding gene in all genomes). In this update article, we present six major new developments in OMA: (i) a new web interface; (ii) Gene Ontology function predictions as part of the OMA pipeline; (iii) better support for plant genomes and in particular homeologs in the wheat genome; (iv) a new synteny viewer providing the genomic context of orthologs; (v) statically computed hierarchical orthologous groups subsets downloadable in OrthoXML format; and (vi) possibility to export parts of the all-against-all computations and to combine them with custom data for 'client-side' orthology prediction. OMA can be accessed through the OMA Browser and various programmatic interfaces at http://omabrowser.org.

  3. The OMA orthology database in 2015: function predictions, better plant support, synteny view and other improvements.

    PubMed

    Altenhoff, Adrian M; Škunca, Nives; Glover, Natasha; Train, Clément-Marie; Sueki, Anna; Piližota, Ivana; Gori, Kevin; Tomiczek, Bartlomiej; Müller, Steven; Redestig, Henning; Gonnet, Gaston H; Dessimoz, Christophe

    2015-01-01

    The Orthologous Matrix (OMA) project is a method and associated database inferring evolutionary relationships amongst currently 1706 complete proteomes (i.e. the protein sequence associated for every protein-coding gene in all genomes). In this update article, we present six major new developments in OMA: (i) a new web interface; (ii) Gene Ontology function predictions as part of the OMA pipeline; (iii) better support for plant genomes and in particular homeologs in the wheat genome; (iv) a new synteny viewer providing the genomic context of orthologs; (v) statically computed hierarchical orthologous groups subsets downloadable in OrthoXML format; and (vi) possibility to export parts of the all-against-all computations and to combine them with custom data for 'client-side' orthology prediction. OMA can be accessed through the OMA Browser and various programmatic interfaces at http://omabrowser.org. PMID:25399418

  4. Improving the Analysis, Storage and Sharing of Neuroimaging Data using Relational Databases and Distributed Computing

    PubMed Central

    Hasson, Uri; Skipper, Jeremy I.; Wilde, Michael J.; Nusbaum, Howard C.; Small, Steven L.

    2007-01-01

    The increasingly complex research questions addressed by neuroimaging research impose substantial demands on computational infrastructures. These infrastructures need to support management of massive amounts of data in a way that affords rapid and precise data analysis, to allow collaborative research, and to achieve these aims securely and with minimum management overhead. Here we present an approach that overcomes many current limitations in data analysis and data sharing. This approach is based on open source database management systems that support complex data queries as an integral part of data analysis, flexible data sharing, and parallel and distributed data processing using cluster computing and Grid computing resources. We assess the strengths of these approaches as compared to current frameworks based on storage of binary or text files. We then describe in detail the implementation of such a system and provide a concrete description of how it was used to enable a complex analysis of fMRI time series data. PMID:17964812

  5. Annotations of Mexican bullfighting videos for semantic index

    NASA Astrophysics Data System (ADS)

    Montoya Obeso, Abraham; Oropesa Morales, Lester Arturo; Fernando Vázquez, Luis; Cocolán Almeda, Sara Ivonne; Stoian, Andrei; García Vázquez, Mireya Saraí; Zamudio Fuentes, Luis Miguel; Montiel Perez, Jesús Yalja; de la O Torres, Saul; Ramírez Acosta, Alejandro Alvaro

    2015-09-01

    The video annotation is important for web indexing and browsing systems. Indeed, in order to evaluate the performance of video query and mining techniques, databases with concept annotations are required. Therefore, it is necessary generate a database with a semantic indexing that represents the digital content of the Mexican bullfighting atmosphere. This paper proposes a scheme to make complex annotations in a video in the frame of multimedia search engine project. Each video is partitioned using our segmentation algorithm that creates shots of different length and different number of frames. In order to make complex annotations about the video, we use ELAN software. The annotations are done in two steps: First, we take note about the whole content in each shot. Second, we describe the actions as parameters of the camera like direction, position and deepness. As a consequence, we obtain a more complete descriptor of every action. In both cases we use the concepts of the TRECVid 2014 dataset. We also propose new concepts. This methodology allows to generate a database with the necessary information to create descriptors and algorithms capable to detect actions to automatically index and classify new bullfighting multimedia content.

  6. Analysis and Annotation of Nucleic Acid Sequence

    SciTech Connect

    States, David J.

    2004-07-28

    The aims of this project were to develop improved methods for computational genome annotation and to apply these methods to improve the annotation of genomic sequence data with a specific focus on human genome sequencing. The project resulted in a substantial body of published work. Notable contributions of this project were the identification of basecalling and lane tracking as error processes in genome sequencing and contributions to improved methods for these steps in genome sequencing. This technology improved the accuracy and throughput of genome sequence analysis. Probabilistic methods for physical map construction were developed. Improved methods for sequence alignment, alternative splicing analysis, promoter identification and NF kappa B response gene prediction were also developed.

  7. MIPS: analysis and annotation of proteins from whole genomes.

    PubMed

    Mewes, H W; Amid, C; Arnold, R; Frishman, D; Güldener, U; Mannhaupt, G; Münsterkötter, M; Pagel, P; Strack, N; Stümpflen, V; Warfsmann, J; Ruepp, A

    2004-01-01

    The Munich Information Center for Protein Sequences (MIPS-GSF), Neuherberg, Germany, provides protein sequence-related information based on whole-genome analysis. The main focus of the work is directed toward the systematic organization of sequence-related attributes as gathered by a variety of algorithms, primary information from experimental data together with information compiled from the scientific literature. MIPS maintains automatically generated and manually annotated genome-specific databases, develops systematic classification schemes for the functional annotation of protein sequences and provides tools for the comprehensive analysis of protein sequences. This report updates the information on the yeast genome (CYGD), the Neurospora crassa genome (MNCDB), the database of complete cDNAs (German Human Genome Project, NGFN), the database of mammalian protein-protein interactions (MPPI), the database of FASTA homologies (SIMAP), and the interface for the fast retrieval of protein-associated information (QUIPOS). The Arabidopsis thaliana database, the rice database, the plant EST databases (MATDB, MOsDB, SPUTNIK), as well as the databases for the comprehensive set of genomes (PEDANT genomes) are described elsewhere in the 2003 and 2004 NAR database issues, respectively. All databases described, and the detailed descriptions of our projects can be accessed through the MIPS web server (http://mips.gsf.de). PMID:14681354

  8. NOAA's Integrated Tsunami Database: Data for improved forecasts, warnings, research, and risk assessments

    NASA Astrophysics Data System (ADS)

    Stroker, Kelly; Dunbar, Paula; Mungov, George; Sweeney, Aaron; McCullough, Heather; Carignan, Kelly

    2015-04-01

    The National Oceanic and Atmospheric Administration (NOAA) has primary responsibility in the United States for tsunami forecast, warning, research, and supports community resiliency. NOAA's National Geophysical Data Center (NGDC) and co-located World Data Service for Geophysics provide a unique collection of data enabling communities to ensure preparedness and resilience to tsunami hazards. Immediately following a damaging or fatal tsunami event there is a need for authoritative data and information. The NGDC Global Historical Tsunami Database (http://www.ngdc.noaa.gov/hazard/) includes all tsunami events, regardless of intensity, as well as earthquakes and volcanic eruptions that caused fatalities, moderate damage, or generated a tsunami. The long-term data from these events, including photographs of damage, provide clues to what might happen in the future. NGDC catalogs the information on global historical tsunamis and uses these data to produce qualitative tsunami hazard assessments at regional levels. In addition to the socioeconomic effects of a tsunami, NGDC also obtains water level data from the coasts and the deep-ocean at stations operated by the NOAA/NOS Center for Operational Oceanographic Products and Services, the NOAA Tsunami Warning Centers, and the National Data Buoy Center (NDBC) and produces research-quality data to isolate seismic waves (in the case of the deep-ocean sites) and the tsunami signal. These water-level data provide evidence of sea-level fluctuation and possible inundation events. NGDC is also building high-resolution digital elevation models (DEMs) to support real-time forecasts, implemented at 75 US coastal communities. After a damaging or fatal event NGDC begins to collect and integrate data and information from many organizations into the hazards databases. Sources of data include our NOAA partners, the U.S. Geological Survey, the UNESCO Intergovernmental Oceanographic Commission (IOC) and International Tsunami Information Center

  9. IMPROVING EMISSIONS ESTIMATES WITH COMPUTATIONAL INTELLIGENCE, DATABASE EXPANSION, AND COMPREHENSIVE VALIDATION

    EPA Science Inventory

    The report discusses an EPA investigation of techniques to improve methods for estimating volatile organic compound (VOC) emissions from area sources. Using the automobile refinishing industry for a detailed area source case study, an emission estimation method is being developed...

  10. Improving the Discoverability and Availability of Sample Data and Imagery in NASA's Astromaterials Curation Digital Repository Using a New Common Architecture for Sample Databases

    NASA Astrophysics Data System (ADS)

    Todd, N. S.; Evans, C.

    2015-06-01

    NASA’s Astromaterials Curation Office is leading an initiative to create a common framework for its databases to improve discoverability and access to data and imagery from NASA-curated extraterrestrial samples for planetary science researchers.

  11. Effects of Annotations and Homework on Learning Achievement: An Empirical Study of Scratch Programming Pedagogy

    ERIC Educational Resources Information Center

    Su, Addison Y. S.; Huang, Chester S. J.; Yang, Stephen J. H.; Ding, T. J.; Hsieh, Y. Z.

    2015-01-01

    In Taiwan elementary schools, Scratch programming has been taught for more than four years. Previous studies have shown that personal annotations is a useful learning method that improve learning performance. An annotation-based Scratch programming (ASP) system provides for the creation, share, and review of annotations and homework solutions in…

  12. Similarity landscapes: An improved method for scientific visualization of information from protein and DNA database searches

    SciTech Connect

    Dogget, N.; Myers, G.; Wills, C.J.

    1998-12-01

    This is the final report of a three-year, Laboratory Directed Research and Development (LDRD) project at the Los Alamos National Laboratory (LANL). The authors have used computer simulations and examination of a variety of databases to answer questions about a wide range of evolutionary questions. The authors have found that there is a clear distinction in the evolution of HIV-1 and HIV-2, with the former and more virulent virus evolving more rapidly at a functional level. The authors have discovered highly non-random patterns in the evolution of HIV-1 that can be attributed to a variety of selective pressures. In the course of examination of microsatellite DNA (short repeat regions) in microorganisms, the authors have found clear differences between prokaryotes and eukaryotes in their distribution, differences that can be tied to different selective pressures. They have developed a new method (topiary pruning) for enhancing the phylogenetic information contained in DNA sequences. Most recently, the authors have discovered effects in complex rainforest ecosystems that indicate strong frequency-dependent interactions between host species and their parasites, leading to the maintenance of ecosystem variability.

  13. CHIANTI-AN ATOMIC DATABASE FOR EMISSION LINES. XIII. SOFT X-RAY IMPROVEMENTS AND OTHER CHANGES

    SciTech Connect

    Landi, E.; Young, P. R.; Dere, K. P.; Del Zanna, G.; Mason, H. E.

    2013-02-15

    The CHIANTI spectral code consists of two parts: an atomic database and a suite of computer programs in Python and IDL. Together, they allow the calculation of the optically thin spectrum of astrophysical objects and provide spectroscopic plasma diagnostics for the analysis of astrophysical spectra. The database includes atomic energy levels, wavelengths, radiative transition probabilities, collision excitation rate coefficients, ionization, and recombination rate coefficients, as well as data to calculate free-free, free-bound, and two-photon continuum emission. Version 7.1 has been released, which includes improved data for several ions, recombination rates, and element abundances. In particular, it provides a large expansion of the CHIANTI models for key Fe ions from Fe VIII to Fe XIV to improve the predicted emission in the 50-170 A wavelength range. All data and programs are freely available at http://www.chiantidatabase.org and in SolarSoft, while the Python interface to CHIANTI can be found at http://chiantipy.sourceforge.net.

  14. Annotating images by mining image search results.

    PubMed

    Wang, Xin-Jing; Zhang, Lei; Li, Xirong; Ma, Wei-Ying

    2008-11-01

    Although it has been studied for years by the computer vision and machine learning communities, image annotation is still far from practical. In this paper, we propose a novel attempt at model-free image annotation, which is a data-driven approach that annotates images by mining their search results. Some 2.4 million images with their surrounding text are collected from a few photo forums to support this approach. The entire process is formulated in a divide-and-conquer framework where a query keyword is provided along with the uncaptioned image to improve both the effectiveness and efficiency. This is helpful when the collected data set is not dense everywhere. In this sense, our approach contains three steps: 1) the search process to discover visually and semantically similar search results, 2) the mining process to identify salient terms from textual descriptions of the search results, and 3) the annotation rejection process to filter out noisy terms yielded by Step 2. To ensure real-time annotation, two key techniques are leveraged-one is to map the high-dimensional image visual features into hash codes, the other is to implement it as a distributed system, of which the search and mining processes are provided as Web services. As a typical result, the entire process finishes in less than 1 second. Since no training data set is required, our approach enables annotating with unlimited vocabulary and is highly scalable and robust to outliers. Experimental results on both real Web images and a benchmark image data set show the effectiveness and efficiency of the proposed algorithm. It is also worth noting that, although the entire approach is illustrated within the divide-and conquer framework, a query keyword is not crucial to our current implementation. We provide experimental results to prove this.

  15. Improving the Mapping of Smith-Waterman Sequence Database Searches onto CUDA-Enabled GPUs.

    PubMed

    Huang, Liang-Tsung; Wu, Chao-Chin; Lai, Lien-Fu; Li, Yun-Ju

    2015-01-01

    Sequence alignment lies at heart of the bioinformatics. The Smith-Waterman algorithm is one of the key sequence search algorithms and has gained popularity due to improved implementations and rapidly increasing compute power. Recently, the Smith-Waterman algorithm has been successfully mapped onto the emerging general-purpose graphics processing units (GPUs). In this paper, we focused on how to improve the mapping, especially for short query sequences, by better usage of shared memory. We performed and evaluated the proposed method on two different platforms (Tesla C1060 and Tesla K20) and compared it with two classic methods in CUDASW++. Further, the performance on different numbers of threads and blocks has been analyzed. The results showed that the proposed method significantly improves Smith-Waterman algorithm on CUDA-enabled GPUs in proper allocation of block and thread numbers.

  16. 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

  17. 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

  18. The apoptosis database.

    PubMed

    Doctor, K S; Reed, J C; Godzik, A; Bourne, P E

    2003-06-01

    The apoptosis database is a public resource for researchers and students interested in the molecular biology of apoptosis. The resource provides functional annotation, literature references, diagrams/images, and alternative nomenclatures on a set of proteins having 'apoptotic domains'. These are the distinctive domains that are often, if not exclusively, found in proteins involved in apoptosis. The initial choice of proteins to be included is defined by apoptosis experts and bioinformatics tools. Users can browse through the web accessible lists of domains, proteins containing these domains and their associated homologs. The database can also be searched by sequence homology using basic local alignment search tool, text word matches of the annotation, and identifiers for specific records. The resource is available at http://www.apoptosis-db.org and is updated on a regular basis.

  19. The Male Sex Role: A Selected and Annotated Bibliography.

    ERIC Educational Resources Information Center

    Grady, Kathleen E.; And Others

    This bibliography, containing more than 250 entries, presents research and theoretical perspectives into the male sex role. Articles were chosen for their usefulness to researchers, with emphasis on scientific and data-based research literature. All the annotations use a standard format including subjects, method, findings and comments. Articles…

  20. The Dfam database of repetitive DNA families

    PubMed Central

    Hubley, Robert; Finn, Robert D.; Clements, Jody; Eddy, Sean R.; Jones, Thomas A.; Bao, Weidong; Smit, Arian F.A.; Wheeler, Travis J.

    2016-01-01

    Repetitive DNA, especially that due to transposable elements (TEs), makes up a large fraction of many genomes. Dfam is an open access database of families of repetitive DNA elements, in which each family is represented by a multiple sequence alignment and a profile hidden Markov model (HMM). The initial release of Dfam, featured in the 2013 NAR Database Issue, contained 1143 families of repetitive elements found in humans, and was used to produce more than 100 Mb of additional annotation of TE-derived regions in the human genome, with improved speed. Here, we describe recent advances, most notably expansion to 4150 total families including a comprehensive set of known repeat families from four new organisms (mouse, zebrafish, fly and nematode). We describe improvements to coverage, and to our methods for identifying and reducing false annotation. We also describe updates to the website interface. The Dfam website has moved to http://dfam.org. Seed alignments, profile HMMs, hit lists and other underlying data are available for download. PMID:26612867

  1. The Dfam database of repetitive DNA families.

    PubMed

    Hubley, Robert; Finn, Robert D; Clements, Jody; Eddy, Sean R; Jones, Thomas A; Bao, Weidong; Smit, Arian F A; Wheeler, Travis J

    2016-01-01

    Repetitive DNA, especially that due to transposable elements (TEs), makes up a large fraction of many genomes. Dfam is an open access database of families of repetitive DNA elements, in which each family is represented by a multiple sequence alignment and a profile hidden Markov model (HMM). The initial release of Dfam, featured in the 2013 NAR Database Issue, contained 1143 families of repetitive elements found in humans, and was used to produce more than 100 Mb of additional annotation of TE-derived regions in the human genome, with improved speed. Here, we describe recent advances, most notably expansion to 4150 total families including a comprehensive set of known repeat families from four new organisms (mouse, zebrafish, fly and nematode). We describe improvements to coverage, and to our methods for identifying and reducing false annotation. We also describe updates to the website interface. The Dfam website has moved to http://dfam.org. Seed alignments, profile HMMs, hit lists and other underlying data are available for download.

  2. The Dfam database of repetitive DNA families.

    PubMed

    Hubley, Robert; Finn, Robert D; Clements, Jody; Eddy, Sean R; Jones, Thomas A; Bao, Weidong; Smit, Arian F A; Wheeler, Travis J

    2016-01-01

    Repetitive DNA, especially that due to transposable elements (TEs), makes up a large fraction of many genomes. Dfam is an open access database of families of repetitive DNA elements, in which each family is represented by a multiple sequence alignment and a profile hidden Markov model (HMM). The initial release of Dfam, featured in the 2013 NAR Database Issue, contained 1143 families of repetitive elements found in humans, and was used to produce more than 100 Mb of additional annotation of TE-derived regions in the human genome, with improved speed. Here, we describe recent advances, most notably expansion to 4150 total families including a comprehensive set of known repeat families from four new organisms (mouse, zebrafish, fly and nematode). We describe improvements to coverage, and to our methods for identifying and reducing false annotation. We also describe updates to the website interface. The Dfam website has moved to http://dfam.org. Seed alignments, profile HMMs, hit lists and other underlying data are available for download. PMID:26612867

  3. Rfam 12.0: updates to the RNA families database

    PubMed Central

    Nawrocki, Eric P.; Burge, Sarah W.; Bateman, Alex; Daub, Jennifer; Eberhardt, Ruth Y.; Eddy, Sean R.; Floden, Evan W.; Gardner, Paul P.; Jones, Thomas A.; Tate, John; Finn, Robert D.

    2015-01-01

    The Rfam database (available at http://rfam.xfam.org) is a collection of non-coding RNA families represented by manually curated sequence alignments, consensus secondary structures and annotation gathered from corresponding Wikipedia, taxonomy and ontology resources. In this article, we detail updates and improvements to the Rfam data and website for the Rfam 12.0 release. We describe the upgrade of our search pipeline to use Infernal 1.1 and demonstrate its improved homology detection ability by comparison with the previous version. The new pipeline is easier for users to apply to their own data sets, and we illustrate its ability to annotate RNAs in genomic and metagenomic data sets of various sizes. Rfam has been expanded to include 260 new families, including the well-studied large subunit ribosomal RNA family, and for the first time includes information on short sequence- and structure-based RNA motifs present within families. PMID:25392425

  4. a Radiocarbon Database for Improved Understanding of Global Soil Carbon Dynamics: Part II

    NASA Astrophysics Data System (ADS)

    Trumbore, S.; Torn, M. S.; Sierra, C. A.; Smith, L. J.; Nave, L. E.; Workshop Paritipants, R.

    2011-12-01

    We report results of a workshop to initiate a global database of radiocarbon measurements in soil and other ecosystem compartments. Radiocarbon provides critical information for understanding the rate of exchange of soil carbon with the atmosphere and hydrosphere. For example, radiocarbon has been used to demonstrate the importance of short range order minerals in stabilizing organic carbon on millennial timescales in some soils. On decadal to centennial timescales, the infiltration of 'bomb' radiocarbon provides a measure of the amount and nature of soil carbon that responds on the timescale of most human impacts. The radiocarbon sigature of chemically or physically fractionated soil, or even in specific organic compounds, can yield clues as to controls on organic matter cycling on a range of timescales. Radiocarbon in microbial biomass or respiration can be a sensitive indicator of shifts in substrate use with vegetation, nutrient availability or temperature change. Taken toghether, such measurements can provide critical tests for models of soil carbon dynamics, while patterns in soil C dynamics with edaphic factors can be used to help parameterize models at spatial scales ranging from profile to landscape to global. The advent and proliferation of accelerator mass spectrometry since the early 1990s has vastly increased the number of radiocarbon analyses carried out in soils. However, these studies have usually been carried out by individual investigators within specific sites or regions, and to date the results have not been assembled, interpreted or compared at larger spatial scales. Given the expense of radiocarbon measurements, and the need for global synthesis products to evaluate and/or develop models of soil carbon response to climate and land use changes across a range of spatial scales, our goals are to: (1) bring together in one place existing radiocarbon measurements and provide a continuing common repository for new analyses; (2) supply ancillary

  5. Reflective Database Access Control

    ERIC Educational Resources Information Center

    Olson, Lars E.

    2009-01-01

    "Reflective Database Access Control" (RDBAC) is a model in which a database privilege is expressed as a database query itself, rather than as a static privilege contained in an access control list. RDBAC aids the management of database access controls by improving the expressiveness of policies. However, such policies introduce new interactions…

  6. AGeS: A Software System for Microbial Genome Sequence Annotation

    PubMed Central

    Kumar, Kamal; Desai, Valmik; Cheng, Li; Khitrov, Maxim; Grover, Deepak; Satya, Ravi Vijaya; Yu, Chenggang; Zavaljevski, Nela; Reifman, Jaques

    2011-01-01

    Background The annotation of genomes from next-generation sequencing platforms needs to be rapid, high-throughput, and fully integrated and automated. Although a few Web-based annotation services have recently become available, they may not be the best solution for researchers that need to annotate a large number of genomes, possibly including proprietary data, and store them locally for further analysis. To address this need, we developed a standalone software application, the Annotation of microbial Genome Sequences (AGeS) system, which incorporates publicly available and in-house-developed bioinformatics tools and databases, many of which are parallelized for high-throughput performance. Methodology The AGeS system supports three main capabilities. The first is the storage of input contig sequences and the resulting annotation data in a central, customized database. The second is the annotation of microbial genomes using an integrated software pipeline, which first analyzes contigs from high-throughput sequencing by locating genomic regions that code for proteins, RNA, and other genomic elements through the Do-It-Yourself Annotation (DIYA) framework. The identified protein-coding regions are then functionally annotated using the in-house-developed Pipeline for Protein Annotation (PIPA). The third capability is the visualization of annotated sequences using GBrowse. To date, we have implemented these capabilities for bacterial genomes. AGeS was evaluated by comparing its genome annotations with those provided by three other methods. Our results indicate that the software tools integrated into AGeS provide annotations that are in general agreement with those provided by the compared methods. This is demonstrated by a >94% overlap in the number of identified genes, a significant number of identical annotated features, and a >90% agreement in enzyme function predictions. PMID:21408217

  7. A Factor Graph Approach to Automated GO Annotation.

    PubMed

    Spetale, Flavio E; Tapia, Elizabeth; Krsticevic, Flavia; Roda, Fernando; Bulacio, Pilar

    2016-01-01

    As volume of genomic data grows, computational methods become essential for providing a first glimpse onto gene annotations. Automated Gene Ontology (GO) annotation methods based on hierarchical ensemble classification techniques are particularly interesting when interpretability of annotation results is a main concern. In these methods, raw GO-term predictions computed by base binary classifiers are leveraged by checking the consistency of predefined GO relationships. Both formal leveraging strategies, with main focus on annotation precision, and heuristic alternatives, with main focus on scalability issues, have been described in literature. In this contribution, a factor graph approach to the hierarchical ensemble formulation of the automated GO annotation problem is presented. In this formal framework, a core factor graph is first built based on the GO structure and then enriched to take into account the noisy nature of GO-term predictions. Hence, starting from raw GO-term predictions, an iterative message passing algorithm between nodes of the factor graph is used to compute marginal probabilities of target GO-terms. Evaluations on Saccharomyces cerevisiae, Arabidopsis thaliana and Drosophila melanogaster protein sequences from the GO Molecular Function domain showed significant improvements over competing approaches, even when protein sequences were naively characterized by their physicochemical and secondary structure properties or when loose noisy annotation datasets were considered. Based on these promising results and using Arabidopsis thaliana annotation data, we extend our approach to the identification of most promising molecular function annotations for a set of proteins of unknown function in Solanum lycopersicum. PMID:26771463

  8. A Factor Graph Approach to Automated GO Annotation

    PubMed Central

    Spetale, Flavio E.; Tapia, Elizabeth; Krsticevic, Flavia; Roda, Fernando; Bulacio, Pilar

    2016-01-01

    As volume of genomic data grows, computational methods become essential for providing a first glimpse onto gene annotations. Automated Gene Ontology (GO) annotation methods based on hierarchical ensemble classification techniques are particularly interesting when interpretability of annotation results is a main concern. In these methods, raw GO-term predictions computed by base binary classifiers are leveraged by checking the consistency of predefined GO relationships. Both formal leveraging strategies, with main focus on annotation precision, and heuristic alternatives, with main focus on scalability issues, have been described in literature. In this contribution, a factor graph approach to the hierarchical ensemble formulation of the automated GO annotation problem is presented. In this formal framework, a core factor graph is first built based on the GO structure and then enriched to take into account the noisy nature of GO-term predictions. Hence, starting from raw GO-term predictions, an iterative message passing algorithm between nodes of the factor graph is used to compute marginal probabilities of target GO-terms. Evaluations on Saccharomyces cerevisiae, Arabidopsis thaliana and Drosophila melanogaster protein sequences from the GO Molecular Function domain showed significant improvements over competing approaches, even when protein sequences were naively characterized by their physicochemical and secondary structure properties or when loose noisy annotation datasets were considered. Based on these promising results and using Arabidopsis thaliana annotation data, we extend our approach to the identification of most promising molecular function annotations for a set of proteins of unknown function in Solanum lycopersicum. PMID:26771463

  9. A Factor Graph Approach to Automated GO Annotation.

    PubMed

    Spetale, Flavio E; Tapia, Elizabeth; Krsticevic, Flavia; Roda, Fernando; Bulacio, Pilar

    2016-01-01

    As volume of genomic data grows, computational methods become essential for providing a first glimpse onto gene annotations. Automated Gene Ontology (GO) annotation methods based on hierarchical ensemble classification techniques are particularly interesting when interpretability of annotation results is a main concern. In these methods, raw GO-term predictions computed by base binary classifiers are leveraged by checking the consistency of predefined GO relationships. Both formal leveraging strategies, with main focus on annotation precision, and heuristic alternatives, with main focus on scalability issues, have been described in literature. In this contribution, a factor graph approach to the hierarchical ensemble formulation of the automated GO annotation problem is presented. In this formal framework, a core factor graph is first built based on the GO structure and then enriched to take into account the noisy nature of GO-term predictions. Hence, starting from raw GO-term predictions, an iterative message passing algorithm between nodes of the factor graph is used to compute marginal probabilities of target GO-terms. Evaluations on Saccharomyces cerevisiae, Arabidopsis thaliana and Drosophila melanogaster protein sequences from the GO Molecular Function domain showed significant improvements over competing approaches, even when protein sequences were naively characterized by their physicochemical and secondary structure properties or when loose noisy annotation datasets were considered. Based on these promising results and using Arabidopsis thaliana annotation data, we extend our approach to the identification of most promising molecular function annotations for a set of proteins of unknown function in Solanum lycopersicum.

  10. MEPD: medaka expression pattern database, genes and more

    PubMed Central

    Alonso-Barba, Juan I.; Rahman, Raza-Ur; Wittbrodt, Joachim; Mateo, Juan L.

    2016-01-01

    The Medaka Expression Pattern Database (MEPD; http://mepd.cos.uni-heidelberg.de/) is designed as a repository of medaka expression data for the scientific community. In this update we present two main improvements. First, we have changed the previous clone-centric view for in situ data to a gene-centric view. This is possible because now we have linked all the data present in MEPD to the medaka gene annotation in ENSEMBL. In addition, we have also connected the medaka genes in MEPD to their corresponding orthologous gene in zebrafish, again using the ENSEMBL database. Based on this, we provide a link to the Zebrafish Model Organism Database (ZFIN) to allow researches to compare expression data between these two fish model organisms. As a second major improvement, we have modified the design of the database to enable it to host regulatory elements, promoters or enhancers, expression patterns in addition to gene expression. The combination of gene expression, by traditional in situ, and regulatory element expression, typically by fluorescence reporter gene, within the same platform assures consistency in terms of annotation. In our opinion, this will allow researchers to uncover new insights between the expression domain of genes and their regulatory landscape. PMID:26450962

  11. MEPD: medaka expression pattern database, genes and more.

    PubMed

    Alonso-Barba, Juan I; Rahman, Raza-Ur; Wittbrodt, Joachim; Mateo, Juan L

    2016-01-01

    The Medaka Expression Pattern Database (MEPD; http://mepd.cos.uni-heidelberg.de/) is designed as a repository of medaka expression data for the scientific community. In this update we present two main improvements. First, we have changed the previous clone-centric view for in situ data to a gene-centric view. This is possible because now we have linked all the data present in MEPD to the medaka gene annotation in ENSEMBL. In addition, we have also connected the medaka genes in MEPD to their corresponding orthologous gene in zebrafish, again using the ENSEMBL database. Based on this, we provide a link to the Zebrafish Model Organism Database (ZFIN) to allow researches to compare expression data between these two fish model organisms. As a second major improvement, we have modified the design of the database to enable it to host regulatory elements, promoters or enhancers, expression patterns in addition to gene expression. The combination of gene expression, by traditional in situ, and regulatory element expression, typically by fluorescence reporter gene, within the same platform assures consistency in terms of annotation. In our opinion, this will allow researchers to uncover new insights between the expression domain of genes and their regulatory landscape. PMID:26450962

  12. The IMPROVE_A temperature protocol for thermal/optical carbon analysis: maintaining consistency with a long-term database.

    PubMed

    Chow, Judith C; Watson, John G; Chen, L W Antony; Chang, M C Oliver; Robinson, Norman F; Trimble, Dana; Kohl, Steven

    2007-09-01

    Thermally derived carbon fractions including organic carbon (OC) and elemental carbon (EC) have been reported for the U.S. Interagency Monitoring of PROtected Visual Environments (IMPROVE) network since 1987 and have been found useful in source apportionment studies and to evaluate quartz-fiber filter adsorption of organic vapors. The IMPROVE_A temperature protocol defines temperature plateaus for thermally derived carbon fractions of 140 degrees C for OC1, 280 degrees C for OC2, 480 degrees C for OC3, and 580 degrees C for OC4 in a helium (He) carrier gas and 580 degrees C for EC1, 740 degrees C for EC2, and 840 degrees C for EC3 in a 98% He/2% oxygen (O2) carrier gas. These temperatures differ from those used previously because new hardware used for the IMPROVE thermal/optical reflectance (IMPROVE_TOR) protocol better represents the sample temperature than did the old hardware. A newly developed temperature calibration method demonstrates that these temperatures better represent sample temperatures in the older units used to quantify IMPROVE carbon fractions from 1987 through 2004. Only the thermal fractions are affected by changes in temperature. The OC and EC by TOR are insensitive to the change in temperature protocol, and therefore the long-term consistency of the IMPROVE database is conserved. A method to detect small quantities of O2 in the pure He carrier gas shows that O2 levels above 100 ppmv also affect the comparability of thermal carbon fractions but have little effect on the IMPROVE_TOR split between OC and EC.

  13. iPathCons and iPathDB: an improved insect pathway construction tool and the database.

    PubMed

    Zhang, Zan; Yin, Chuanlin; Liu, Ying; Jie, Wencai; Lei, Wenjie; Li, Fei

    2014-01-01

    Insects are one of the most successful animal groups on earth. Some insects, such as the silkworm and honeybee, are beneficial to humans, whereas others are notorious pests of crops. At present, the genomes of 38 insects have been sequenced and made publically available. In addition, the transcriptomes of dozens of insects have been sequenced. As gene data rapidly accumulate, constructing the pathway of molecular interactions becomes increasingly important for entomological research. Here, we developed an improved tool, iPathCons, for knowledge-based construction of pathways from the transcriptomes or the official gene sets of genomes. Considering the high evolution diversity in insects, iPathCons uses a voting system for Kyoto Encyclopedia of Genes and Genomes Orthology assignment. Both stand-alone software and a web server of iPathCons are provided. Using iPathCons, we constructed the pathways of molecular interactions of 52 insects, including 37 genome-sequenced and 15 transcriptome-sequenced ones. These pathways are available in the iPathDB, which provides searches, web server, data downloads, etc. This database will be highly useful for the insect research community. Database URL: http://ento.njau.edu.cn/ipath/

  14. Databases save time and improve the quality of the design, management and processing of ecopathological surveys.

    PubMed

    Sulpice, P; Bugnard, F; Calavas, D

    1994-01-01

    The example of an ecopathological survey on nursing ewe mastitis shows that data bases have 4 complementary functions: assistance during the conception of surveys; follow-up of surveys; management and quality control of data; and data organization for statistical analysis. This is made possible by the simultaneous conception of both the data base and the survey, and by the integration of computer science into the work of the task group that conducts the survey. This methodology helps save time and improve the quality of data in ecopathological surveys.

  15. An improved tropospheric ozone database retrieved from SCIAMACHY Limb-Nadir-Matching method

    NASA Astrophysics Data System (ADS)

    Jia, Jia; Rozanov, Alexei; Ladstätter-Weißenmayer, Annette; Ebojie, Felix; Rahpoe, Nabiz; Bötel, Stefan; Burrows, John

    2015-04-01

    Tropospheric ozone is one of the most important green-house gases and the main component of photochemical smog. It is either transported from the stratosphere or photochemically produced during pollution events in the troposphere that threaten the respiratory system. To investigate sources, transport mechanisms of tropospheric ozone in a global view, limb nadir matching (LNM) technique applied with SCIAMACHY instrument is used to retrieve tropospheric ozone. With the fact that 90% ozone is located in the stratosphere and only about 10% can be observed in the troposphere, the usage of satellite data requires highly qualified nadir and limb data. In this study we show an improvement of SCIAMACHY limb data as well as its influence on tropospheric ozone results. The limb nadir matching technique is also refined to increase the quality of the tropospheric ozone. The results are validated with ozone sonde measurements.

  16. EST-PAC a web package for EST annotation and protein sequence prediction

    PubMed Central

    Strahm, Yvan; Powell, David; Lefèvre, Christophe

    2006-01-01

    With the decreasing cost of DNA sequencing technology and the vast diversity of biological resources, researchers increasingly face the basic challenge of annotating a larger number of expressed sequences tags (EST) from a variety of species. This typically consists of a series of repetitive tasks, which should be automated and easy to use. The results of these annotation tasks need to be stored and organized in a consistent way. All these operations should be self-installing, platform independent, easy to customize and amenable to using distributed bioinformatics resources available on the Internet. In order to address these issues, we present EST-PAC a web oriented multi-platform software package for expressed sequences tag (EST) annotation. EST-PAC provides a solution for the administration of EST and protein sequence annotations accessible through a web interface. Three aspects of EST annotation are automated: 1) searching local or remote biological databases for sequence similarities using Blast services, 2) predicting protein coding sequence from EST data and, 3) annotating predicted protein sequences with functional domain predictions. In practice, EST-PAC integrates the BLASTALL suite, EST-Scan2 and HMMER in a relational database system accessible through a simple web interface. EST-PAC also takes advantage of the relational database to allow consistent storage, powerful queries of results and, management of the annotation process. The system allows users to customize annotation strategies and provides an open-source data-management environment for research and education in bioinformatics. PMID:17147782

  17. The SEED and the Rapid Annotation of microbial genomes using Subsystems Technology (RAST)

    PubMed Central

    Overbeek, Ross; Olson, Robert; Pusch, Gordon D.; Olsen, Gary J.; Davis, James J.; Disz, Terry; Edwards, Robert A.; Gerdes, Svetlana; Parrello, Bruce; Shukla, Maulik; Vonstein, Veronika; Wattam, Alice R.; Xia, Fangfang; Stevens, Rick

    2014-01-01

    In 2004, the SEED (http://pubseed.theseed.org/) was created to provide consistent and accurate genome annotations across thousands of genomes and as a platform for discovering and developing de novo annotations. The SEED is a constantly updated integration of genomic data with a genome database, web front end, API and server scripts. It is used by many scientists for predicting gene functions and discovering new pathways. In addition to being a powerful database for bioinformatics research, the SEED also houses subsystems (collections of functionally related protein families) and their derived FIGfams (protein families), which represent the core of the RAST annotation engine (http://rast.nmpdr.org/). When a new genome is submitted to RAST, genes are called and their annotations are made by comparison to the FIGfam collection. If the genome is made public, it is then housed within the SEED and its proteins populate the FIGfam collection. This annotation cycle has proven to be a robust and scalable solution to the problem of annotating the exponentially increasing number of genomes. To date, >12 000 users worldwide have annotated >60 000 distinct genomes using RAST. Here we describe the interconnectedness of the SEED database and RAST, the RAST annotation pipeline and updates to both resources. PMID:24293654

  18. Human object annotation for surveillance video forensics

    NASA Astrophysics Data System (ADS)

    Fraz, Muhammad; Zafar, Iffat; Tzanidou, Giounona; Edirisinghe, Eran A.; Sarfraz, Muhammad Saquib

    2013-10-01

    A system that can automatically annotate surveillance video in a manner useful for locating a person with a given description of clothing is presented. Each human is annotated based on two appearance features: primary colors of clothes and the presence of text/logos on clothes. The annotation occurs after a robust foreground extraction stage employing a modified Gaussian mixture model-based approach. The proposed pipeline consists of a preprocessing stage where color appearance of an image is improved using a color constancy algorithm. In order to annotate color information for human clothes, we use the color histogram feature in HSV space and find local maxima to extract dominant colors for different parts of a segmented human object. To detect text/logos on clothes, we begin with the extraction of connected components of enhanced horizontal, vertical, and diagonal edges in the frames. These candidate regions are classified as text or nontext on the basis of their local energy-based shape histogram features. Further, to detect humans, a novel technique has been proposed that uses contourlet transform-based local binary pattern (CLBP) features. In the proposed method, we extract the uniform direction invariant LBP feature descriptor for contourlet transformed high-pass subimages from vertical and diagonal directional bands. In the final stage, extracted CLBP descriptors are classified by a trained support vector machine. Experimental results illustrate the superiority of our method on large-scale surveillance video data.

  19. Update for Users of the Methanol Database: Recent Improvements, Remaining Problems, and More Complicated Regions

    NASA Astrophysics Data System (ADS)

    Xu, Li-Hong; Pearson, J. C.; Drouin, B. J.; Hougen, J. T.

    2009-06-01

    Last year, we published a new global fit for normal methanol covering the first three torsional states (v_t = 0, 1 and 2) for J values up to 30^{[a]}. The global fit of approximately 5600 frequency measurements and 19 000 Fourier transform far infrared (FTFIR) wavenumber measurements to 119 parameters reached the estimated experimental measurement accuracy for the FTFIR transitions, and about twice the estimated experimental measurement accuracy for the microwave, submillimeter-wave and terahertz transitions. Due to a number of complications in that data set, we designated the work as a "living document" and encouraged measurement laboratories represented in the data set to assess carefully how their data were treated, and to partition (if appropriate) their measurements into an optimum set (for which they specify their highest measurement precision) and a less good set (for which they specify a reduced measurement precision). Using the new JPL spectrometer and additional improved measurements, we have recently revisited a large number of transitions. Poor line shapes due either to power saturation or blending were carefully treated with a multi-line peakfinding procedure and assessed with more realistic uncertainties. Assignments were also extended to higher K and J. Several perturbed systems have been identified with complicated networks of interactions. The current data set now contains nearly 9500 frequency measured transitions. While we believe that this represents a substantial improvement on the quantum number coverage of our previous paper^{[a]}, we are also aware of continuing problems in our data fitting. Above all, we are facing challenges moving into a more complicated region with networks of interactions coupling different torsional states. Li-Hong Xu, J. Fisher, R.M. Lees, H.Y. Shi, J.T. Hougen, J.C. Pearson, B.J. Drouin, G.A. Blake, R. Braakman, 2008, J. Mol. Spectrosc., 251, 305-313.

  20. Hawaii bibliographic database

    USGS Publications Warehouse

    Wright, T.L.; Takahashi, T.J.

    1998-01-01

    The Hawaii bibliographic database has been created to contain all of the literature, from 1779 to the present, pertinent to the volcanological history of the Hawaiian-Emperor volcanic chain. References are entered in a PC- and Macintosh-compatible EndNote Plus bibliographic database with keywords and abstracts or (if no abstract) with annotations as to content. Keywords emphasize location, discipline, process, identification of new chemical data or age determinations, and type of publication. The database is updated approximately three times a year and is available to upload from an ftp site. The bibliography contained 8460 references at the time this paper was submitted for publication. Use of the database greatly enhances the power and completeness of library searches for anyone interested in Hawaiian volcanism.

  1. GFam: a platform for automatic annotation of gene families

    PubMed Central

    Sasidharan, Rajkumar; Nepusz, Tamás; Swarbreck, David; Huala, Eva; Paccanaro, Alberto

    2012-01-01

    We have developed GFam, a platform for automatic annotation of gene/protein families. GFam provides a framework for genome initiatives and model organism resources to build domain-based families, derive meaningful functional labels and offers a seamless approach to propagate functional annotation across periodic genome updates. GFam is a hybrid approach that uses a greedy algorithm to chain component domains from InterPro annotation provided by its 12 member resources followed by a sequence-based connected component analysis of un-annotated sequence regions to derive consensus domain architecture for each sequence and subsequently generate families based on common architectures. Our integrated approach increases sequence coverage by 7.2 percentage points and residue coverage by 14.6 percentage points higher than the coverage relative to the best single-constituent database within InterPro for the proteome of Arabidopsis. The true power of GFam lies in maximizing annotation provided by the different InterPro data sources that offer resource-specific coverage for different regions of a sequence. GFam’s capability to capture higher sequence and residue coverage can be useful for genome annotation, comparative genomics and functional studies. GFam is a general-purpose software and can be used for any collection of protein sequences. The software is open source and can be obtained from http://www.paccanarolab.org/software/gfam/. PMID:22790981

  2. MetaStorm: A Public Resource for Customizable Metagenomics Annotation.

    PubMed

    Arango-Argoty, Gustavo; Singh, Gargi; Heath, Lenwood S; Pruden, Amy; Xiao, Weidong; Zhang, Liqing

    2016-01-01

    Metagenomics is a trending research area, calling for the need to analyze large quantities of data generated from next generation DNA sequencing technologies. The need to store, retrieve, analyze, share, and visualize such data challenges current online computational systems. Interpretation and annotation of specific information is especially a challenge for metagenomic data sets derived from environmental samples, because current annotation systems only offer broad classification of microbial diversity and function. Moreover, existing resources are not configured to readily address common questions relevant to environmental systems. Here we developed a new online user-friendly metagenomic analysis server called MetaStorm (http://bench.cs.vt.edu/MetaStorm/), which facilitates customization of computational analysis for metagenomic data sets. Users can upload their own reference databases to tailor the metagenomics annotation to focus on various taxonomic and functional gene markers of interest. MetaStorm offers two major analysis pipelines: an assembly-based annotation pipeline and the standard read annotation pipeline used by existing web servers. These pipelines can be selected individually or together. Overall, MetaStorm provides enhanced interactive visualization to allow researchers to explore and manipulate taxonomy and functional annotation at various levels of resolution. PMID:27632579

  3. MetaStorm: A Public Resource for Customizable Metagenomics Annotation

    PubMed Central

    Arango-Argoty, Gustavo; Singh, Gargi; Heath, Lenwood S.; Pruden, Amy; Xiao, Weidong; Zhang, Liqing

    2016-01-01

    Metagenomics is a trending research area, calling for the need to analyze large quantities of data generated from next generation DNA sequencing technologies. The need to store, retrieve, analyze, share, and visualize such data challenges current online computational systems. Interpretation and annotation of specific information is especially a challenge for metagenomic data sets derived from environmental samples, because current annotation systems only offer broad classification of microbial diversity and function. Moreover, existing resources are not configured to readily address common questions relevant to environmental systems. Here we developed a new online user-friendly metagenomic analysis server called MetaStorm (http://bench.cs.vt.edu/MetaStorm/), which facilitates customization of computational analysis for metagenomic data sets. Users can upload their own reference databases to tailor the metagenomics annotation to focus on various taxonomic and functional gene markers of interest. MetaStorm offers two major analysis pipelines: an assembly-based annotation pipeline and the standard read annotation pipeline used by existing web servers. These pipelines can be selected individually or together. Overall, MetaStorm provides enhanced interactive visualization to allow researchers to explore and manipulate taxonomy and functional annotation at various levels of resolution. PMID:27632579

  4. Fire-induced water-repellent soils, an annotated bibliography

    USGS Publications Warehouse

    Kalendovsky, M.A.; Cannon, S.H.

    1997-01-01

    The development and nature of water-repellent, or hydrophobic, soils are important issues in evaluating hillslope response to fire. The following annotated bibliography was compiled to consolidate existing published research on the topic. Emphasis was placed on the types, causes, effects and measurement techniques of water repellency, particularly with respect to wildfires and prescribed burns. Each annotation includes a general summary of the respective publication, as well as highlights of interest to this focus. Although some references on the development of water repellency without fires, the chemistry of hydrophobic substances, and remediation of water-repellent conditions are included, coverage of these topics is not intended to be comprehensive. To develop this database, the GeoRef, Agricola, and Water Resources Abstracts databases were searched for appropriate references, and the bibliographies of each reference were then reviewed for additional entries. Additional references will be added to this bibliography as they become available. The annotated bibliography can be accessed on the Web at http://geohazards.cr.usgs.gov/html_files/landslides/ofr97-720/biblio.html. A database consisting of the references and keywords is available through a link at the above address. This database was compiled using EndNote2 plus software by Niles and Associates, and is necessary to search the database.

  5. Automated update, revision, and quality control of the maize genome annotations using MAKER-P improves the B73 RefGen_v3 gene models and identifies new genes

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The large size and relative complexity of many plant genomes make creation, quality control, and dissemination of high-quality gene structure annotations challenging. In response, we have developed MAKER-P, a fast and easy-to-use genome annotation engine for plants. Here, we report the use of MAKER-...

  6. Drug Education: An Annotated Bibliography.

    ERIC Educational Resources Information Center

    Mathieson, Moira B.

    This bibliography consists of a total of 215 entries dealing with drug education, including curriculum guides, and drawn from documents in the ERIC system. There are two sections, the first containing 130 annotated citations of documents and journal articles, and the second containing 85 citations of journal articles without annotations, but with…

  7. Adult Basic Education Annotated Bibliography.

    ERIC Educational Resources Information Center

    Carter, Nancy B.

    This annotated bibliography contains sections divided according to area of study, and within each category materials are listed alphabetically by publisher. Publishers and mailing addresses are listed at the end of the bibliography. Throughout the annotations, whenever specific grade level divisions are not named, the regular Adult Basic Education…

  8. Morphosyntactic Annotation of CHILDES Transcripts

    ERIC Educational Resources Information Center

    Sagae, Kenji; Davis, Eric; Lavie, Alon; MacWhinney, Brian; Wintner, Shuly

    2010-01-01

    Corpora of child language are essential for research in child language acquisition and psycholinguistics. Linguistic annotation of the corpora provides researchers with better means for exploring the development of grammatical constructions and their usage. We describe a project whose goal is to annotate the English section of the CHILDES database…

  9. The PRoteomics IDEntification (PRIDE) Converter 2 framework: an improved suite of tools to facilitate data submission to the PRIDE database and the ProteomeXchange consortium.

    PubMed

    Côté, Richard G; Griss, Johannes; Dianes, José A; Wang, Rui; Wright, James C; van den Toorn, Henk W P; van Breukelen, Bas; Heck, Albert J R; Hulstaert, Niels; Martens, Lennart; Reisinger, Florian; Csordas, Attila; Ovelleiro, David; Perez-Rivevol, Yasset; Barsnes, Harald; Hermjakob, Henning; Vizcaíno, Juan Antonio

    2012-12-01

    The original PRIDE Converter tool greatly simplified the process of submitting mass spectrometry (MS)-based proteomics data to the PRIDE database. However, after much user feedback, it was noted that the tool had some limitations and could not handle several user requirements that were now becoming commonplace. This prompted us to design and implement a whole new suite of tools that would build on the successes of the original PRIDE Converter and allow users to generate submission-ready, well-annotated PRIDE XML files. The PRIDE Converter 2 tool suite allows users to convert search result files into PRIDE XML (the format needed for performing submissions to the PRIDE database), generate mzTab skeleton files that can be used as a basis to submit quantitative and gel-based MS data, and post-process PRIDE XML files by filtering out contaminants and empty spectra, or by merging several PRIDE XML files together. All the tools have both a graphical user interface that provides a dialog-based, user-friendly way to convert and prepare files for submission, as well as a command-line interface that can be used to integrate the tools into existing or novel pipelines, for batch processing and power users. The PRIDE Converter 2 tool suite will thus become a cornerstone in the submission process to PRIDE and, by extension, to the ProteomeXchange consortium of MS-proteomics data repositories.

  10. Automatic annotation of protein function based on family identification.

    PubMed

    Abascal, Federico; Valencia, Alfonso

    2003-11-15

    Although genomes are being sequenced at an impressive rate, the information generated tells us little about protein function, which is slow to characterize by traditional methods. Automatic protein function annotation based on computational methods has alleviated this imbalance. The most powerful current approach for inferring the function of new proteins is by studying the annotations of their homologues, since their common origin is assumed to be reflected in their structure and function. Unfortunately, as proteins evolve they acquire new functions, so annotation based on homology must be carried out in the context of orthologues or subfamilies. Evolution adds new complications through domain shuffling: homology (or orthology) frequently corresponds to domains rather than complete proteins. Moreover, the function of a protein may be seen as the result of combining the functions of its domains. Additionally, automatic annotation has to deal with problems related to the annotations in the databases: errors (which are likely to be propagated), inconsistencies, or different degrees of function specification. We describe a method that addresses these difficulties for the annotation of protein function. Sequence relationships are detected and measured to obtain a map of the sequence space, which is searched for differentiated groups of proteins (similar to islands on the map), which are expected to have a common function and correspond to groups of orthologues or subfamilies. This mapmaking is done by applying a clustering algorithm based on Normalized cuts in graphs. The domain problem is addressed in a simple way: pairwise local alignments are analyzed to determine the extent to which they cover the entire sequence lengths of the two proteins. This analysis determines both what homologues are preferred for functional inheritance and the level of confidence of the annotation. To alleviate the problems associated with database annotations, the information on all the

  11. Cognition inspired framework for indoor scene annotation

    NASA Astrophysics Data System (ADS)

    Ye, Zhipeng; Liu, Peng; Zhao, Wei; Tang, Xianglong

    2015-09-01

    We present a simple yet effective scene annotation framework based on a combination of bag-of-visual words (BoVW), three-dimensional scene structure estimation, scene context, and cognitive theory. From a macroperspective, the proposed cognition-based hybrid motivation framework divides the annotation problem into empirical inference and real-time classification. Inspired by the inference ability of human beings, common objects of indoor scenes are defined for experience-based inference, while in the real-time classification stage, an improved BoVW-based multilayer abstract semantics labeling method is proposed by introducing abstract semantic hierarchies to narrow the semantic gap and improve the performance of object categorization. The proposed framework was evaluated on a variety of common data sets and experimental results proved its effectiveness.

  12. The Proteomics Identifications database: 2010 update.

    PubMed

    Vizcaíno, Juan Antonio; Côté, Richard; Reisinger, Florian; Barsnes, Harald; Foster, Joseph M; Rameseder, Jonathan; Hermjakob, Henning; Martens, Lennart

    2010-01-01

    The Proteomics Identifications database (PRIDE, http://www.ebi.ac.uk/pride) at the European Bioinformatics Institute has become one of the main repositories of mass spectrometry-derived proteomics data. For the last 2 years, PRIDE data holdings have grown substantially, comprising 60 different species, more than 2.5 million protein identifications, 11.5 million peptides and over 50 million spectra by September 2009. We here describe several new and improved features in PRIDE, including the revised submission process, which now includes direct submission of fragment ion annotations. Correspondingly, it is now possible to visualize spectrum fragmentation annotations on tandem mass spectra, a key feature for compliance with journal data submission requirements. We also describe recent developments in the PRIDE BioMart interface, which now allows integrative queries that can join PRIDE data to a growing number of biological resources such as Reactome, Ensembl, InterPro and UniProt. This ability to perform extremely powerful across-domain queries will certainly be a cornerstone of future bioinformatics analyses. Finally, we highlight the importance of data sharing in the proteomics field, and the corresponding integration of PRIDE with other databases in the ProteomExchange consortium.

  13. Functional Annotation Analytics of Rhodopseudomonas palustris Genomes

    PubMed Central

    Simmons, Shaneka S.; Isokpehi, Raphael D.; Brown, Shyretha D.; McAllister, Donee L.; Hall, Charnia C.; McDuffy, Wanaki M.; Medley, Tamara L.; Udensi, Udensi K.; Rajnarayanan, Rajendram V.; Ayensu, Wellington K.; Cohly, Hari H.P.

    2011-01-01

    Rhodopseudomonas palustris, a nonsulphur purple photosynthetic bacteria, has been extensively investigated for its metabolic versatility including ability to produce hydrogen gas from sunlight and biomass. The availability of the finished genome sequences of six R. palustris strains (BisA53, BisB18, BisB5, CGA009, HaA2 and TIE-1) combined with online bioinformatics software for integrated analysis presents new opportunities to determine the genomic basis of metabolic versatility and ecological lifestyles of the bacteria species. The purpose of this investigation was to compare the functional annotations available for multiple R. palustris genomes to identify annotations that can be further investigated for strain-specific or uniquely shared phenotypic characteristics. A total of 2,355 protein family Pfam domain annotations were clustered based on presence or absence in the six genomes. The clustering process identified groups of functional annotations including those that could be verified as strain-specific or uniquely shared phenotypes. For example, genes encoding water/glycerol transport were present in the genome sequences of strains CGA009 and BisB5, but absent in strains BisA53, BisB18, HaA2 and TIE-1. Protein structural homology modeling predicted that the two orthologous 240 aa R. palustris aquaporins have water-specific transport function. Based on observations in other microbes, the presence of aquaporin in R. palustris strains may improve freeze tolerance in natural conditions of rapid freezing such as nitrogen fixation at low temperatures where access to liquid water is a limiting factor for nitrogenase activation. In the case of adaptive loss of aquaporin genes, strains may be better adapted to survive in conditions of high-sugar content such as fermentation of biomass for biohydrogen production. Finally, web-based resources were developed to allow for interactive, user-defined selection of the relationship between protein family annotations and the R

  14. A guide to best practices for Gene Ontology (GO) manual annotation.

    PubMed

    Balakrishnan, Rama; Harris, Midori A; Huntley, Rachael; Van Auken, Kimberly; Cherry, J Michael

    2013-01-01

    The Gene Ontology Consortium (GOC) is a community-based bioinformatics project that classifies gene product function through the use of structured controlled vocabularies. A fundamental application of the Gene Ontology (GO) is in the creation of gene product annotations, evidence-based associations between GO definitions and experimental or sequence-based analysis. Currently, the GOC disseminates 126 million annotations covering >374,000 species including all the kingdoms of life. This number includes two classes of GO annotations: those created manually by experienced biocurators reviewing the literature or by examination of biological data (1.1 million annotations covering 2226 species) and those generated computationally via automated methods. As manual annotations are often used to propagate functional predictions between related proteins within and between genomes, it is critical to provide accurate consistent manual annotations. Toward this goal, we present here the conventions defined by the GOC for the creation of manual annotation. This guide represents the best practices for manual annotation as established by the GOC project over the past 12 years. We hope this guide will encourage research communities to annotate gene products of their interest to enhance the corpus of GO annotations available to all. DATABASE URL: http://www.geneontology.org.

  15. Sma3s: a three-step modular annotator for large sequence datasets.

    PubMed

    Muñoz-Mérida, Antonio; Viguera, Enrique; Claros, M Gonzalo; Trelles, Oswaldo; Pérez-Pulido, Antonio J

    2014-08-01

    Automatic sequence annotation is an essential component of modern 'omics' studies, which aim to extract information from large collections of sequence data. Most existing tools use sequence homology to establish evolutionary relationships and assign putative functions to sequences. However, it can be difficult to define a similarity threshold that achieves sufficient coverage without sacrificing annotation quality. Defining the correct configuration is critical and can be challenging for non-specialist users. Thus, the development of robust automatic annotation techniques that generate high-quality annotations without needing expert knowledge would be very valuable for the research community. We present Sma3s, a tool for automatically annotating very large collections of biological sequences from any kind of gene library or genome. Sma3s is composed of three modules that progressively annotate query sequences using either: (i) very similar homologues, (ii) orthologous sequences or (iii) terms enriched in groups of homologous sequences. We trained the system using several random sets of known sequences, demonstrating average sensitivity and specificity values of ~85%. In conclusion, Sma3s is a versatile tool for high-throughput annotation of a wide variety of sequence datasets that outperforms the accuracy of other well-established annotation algorithms, and it can enrich existing database annotations and uncover previously hidden features. Importantly, Sma3s has already been used in the functional annotation of two published transcriptomes. PMID:24501397

  16. Reliability Of A Surgeon-Reported Morbidity And Mortality Database: A Comparison Of Short-Term Morbidity Between The Scoliosis Research Society And National Surgical Quality Improvement Program Databases

    PubMed Central

    Martin, Christopher T.; Pugely, Andrew J.; Gao, Yubo; Skovrlj, Branko; Lee, Nathan J.; Cho, Samuel K.; Mendoza-Lattes, Sergio

    2016-01-01

    Background There exists a lack of comparison between large national healthcare databases reporting surgical morbidity and mortality. Prior authors have expressed concern that the Scoliosis Research Society (SRS) membership may have underreported complications in spinal surgery. Thus, the purpose of the present study was to compare the incidence of morbidity between the SRS and National Surgical Quality Improvement Program (NSQIP) databases. Methods We reviewed patients enrolled between 2012 and 2013, with a total of 96,875 patients identified in the SRS dataset and 15,909 in the combined adult and pediatric NSQIP dataset. Patients were matched based on diagnostic category,and a univariate analysis was used to compare reported complication rates in the categories of perioperative infection, neurologic injury, and mortality. The SRS database only requires detailed demographic data reporting on patients that have had a complication event. We compared the demographics and comorbidities of this subgroup, and used this as a surrogate to assess the potential magnitude of confounders. Results Small differences existed between the SRS and NSQIP databases in terms of mortality (0.1% v. 0.2%), infection (1.2% v. 2%), and neurologic injury (0.8% v. 0.1%) (p<0.001 for each comparison). Infection rates were consistently lower across multiple diagnostic sub-categories in the SRS database, whereas neurologic injury rates were consistently lower in the NSQIP database. These differences reached statistical significance across several diagnostic subcategories, but the clinical magnitude of the differences was small. Amongst the patients with a complication, modest differences in comorbidities existed between the two cohorts. Conclusion Overall, the incidence of short-term morbidity and mortality was similar between the two databases. There were modest differences in comorbidities, which may explain the small differences observed in morbidity. Concerns regarding possible under

  17. Metabolic pathfinding using RPAIR annotation.

    PubMed

    Faust, Karoline; Croes, Didier; van Helden, Jacques

    2009-05-01

    Metabolic databases contain information about thousands of small molecules and reactions, which can be represented as networks. In the context of metabolic reconstruction, pathways can be inferred by searching optimal paths in such networks. A recurrent problem is the presence of pool metabolites (e.g., water, energy carriers, and cofactors), which are connected to hundreds of reactions, thus establishing irrelevant shortcuts between nodes of the network. One solution to this problem relies on weighted networks to penalize highly connected compounds. A more refined solution takes the chemical structure of reactants into account in order to differentiate between side and main compounds of a reaction. Thanks to an intensive annotation effort at KEGG, decompositions of reactions into reactant pairs (RPAIR) categorized by their role (main, trans, cofac, ligase, and leave) are now available. The goal of this article is to evaluate the impact of RPAIR data on pathfinding in metabolic networks. To this end, we measure the impact of different parameters concerning the construction of the metabolic network: mapping of reactions and reactant pairs onto a graph, use of selected categories of reactant pairs, weighting schemes for compounds and reactions, removal of highly connected metabolites, and reaction directionality. In total, we tested 104 combinations of parameters and identified their optimal values for pathfinding on the basis of 55 reference pathways from three organisms. The best-performing metabolic network combines the biochemical knowledge encoded by KEGG RPAIR with a weighting scheme penalizing highly connected compounds. With this network, we could recover reference pathways from Escherichia coli with an average accuracy of 93% (32 pathways), from Saccharomyces cerevisiae with an average accuracy of 66% (11 pathways), and from humans with an average accuracy of 70% (12 pathways). Our pathfinding approach is available as part of the Network Analysis Tools.

  18. Introspection into institutional database allows for focused quality improvement plan in cardiac surgery: example for a new global healthcare system.

    PubMed

    Lancaster, Elizabeth; Postel, Mackenzie; Satou, Nancy; Shemin, Richard; Benharash, Peyman

    2013-10-01

    Reducing readmission rates is vital to improving quality of care and reducing healthcare costs. In accordance with the Patient Protection and Affordable Care Act, Medicare will cut payments to hospitals with high 30-day readmission rates. We retrospectively reviewed an institutional database to identify risk factors predisposing adult cardiac surgery patients to rehospitalization within 30 days of discharge. Of 2302 adult cardiac surgery patients within the study period from 2008 to 2011, a total of 218 patients (9.5%) were readmitted within 30 days. Factors found to be significant predictors of readmission were nonwhite race (P = 0.003), government health insurance (P = 0.02), ejection fraction less than 40 per cent (P = 0.001), chronic lung disease (P < 0.001), and hospital length of stay greater than 7 days (P = 0.02). Patients undergoing aortic and mitral valve operations had an increased risk of readmission compared with other cardiac operations (P < 0.001). The most common reasons for rehospitalization were pneumonia and other respiratory complications (n = 27 [12.4%]). Recognition of risk factors is crucial to reducing readmissions and improving patient care. Our data suggest that optimizing cardiopulmonary status in patients with comorbidities such as heart failure and chronic obstructive pulmonary disease, increasing directed pneumonia prophylaxis, patient education tailored to specific patient social needs, earlier patient follow-up, and better communication between inpatient and outpatient physicians may reduce readmission rates. PMID:24160795

  19. The Mouse Genome Database: integration of and access to knowledge about the laboratory mouse.

    PubMed

    Blake, Judith A; Bult, Carol J; Eppig, Janan T; Kadin, James A; Richardson, Joel E

    2014-01-01

    The Mouse Genome Database (MGD) (http://www.informatics.jax.org) is the community model organism database resource for the laboratory mouse, a premier animal model for the study of genetic and genomic systems relevant to human biology and disease. MGD maintains a comprehensive catalog of genes, functional RNAs and other genome features as well as heritable phenotypes and quantitative trait loci. The genome feature catalog is generated by the integration of computational and manual genome annotations generated by NCBI, Ensembl and Vega/HAVANA. MGD curates and maintains the comprehensive listing of functional annotations for mouse genes using the Gene Ontology, and MGD curates and integrates comprehensive phenotype annotations including associations of mouse models with human diseases. Recent improvements include integration of the latest mouse genome build (GRCm38), improved access to comparative and functional annotations for mouse genes with expanded representation of comparative vertebrate genomes and new loads of phenotype data from high-throughput phenotyping projects. All MGD resources are freely available to the research community.

  20. Genome Wide Re-Annotation of Caldicellulosiruptor saccharolyticus with New Insights into Genes Involved in Biomass Degradation and Hydrogen Production

    PubMed Central

    Chowdhary, Nupoor; Selvaraj, Ashok; KrishnaKumaar, Lakshmi; Kumar, Gopal Ramesh

    2015-01-01

    Caldicellulosiruptor saccharolyticus has proven itself to be an excellent candidate for biological hydrogen (H2) production, but still it has major drawbacks like sensitivity to high osmotic pressure and low volumetric H2 productivity, which should be considered before it can be used industrially. A whole genome re-annotation work has been carried out as an attempt to update the incomplete genome information that causes gap in the knowledge especially in the area of metabolic engineering, to improve the H2 producing capabilities of C. saccharolyticus. Whole genome re-annotation was performed through manual means for 2,682 Coding Sequences (CDSs). Bioinformatics tools based on sequence similarity, motif search, phylogenetic analysis and fold recognition were employed for re-annotation. Our methodology could successfully add functions for 409 hypothetical proteins (HPs), 46 proteins previously annotated as putative and assigned more accurate functions for the known protein sequences. Homology based gene annotation has been used as a standard method for assigning function to novel proteins, but over the past few years many non-homology based methods such as genomic context approaches for protein function prediction have been developed. Using non-homology based functional prediction methods, we were able to assign cellular processes or physical complexes for 249 hypothetical sequences. Our re-annotation pipeline highlights the addition of 231 new CDSs generated from MicroScope Platform, to the original genome with functional prediction for 49 of them. The re-annotation of HPs and new CDSs is stored in the relational database that is available on the MicroScope web-based platform. In parallel, a comparative genome analyses were performed among the members of genus Caldicellulosiruptor to understand the function and evolutionary processes. Further, with results from integrated re-annotation studies (homology and genomic context approach), we strongly suggest that Csac

  1. Genome Wide Re-Annotation of Caldicellulosiruptor saccharolyticus with New Insights into Genes Involved in Biomass Degradation and Hydrogen Production.

    PubMed

    Chowdhary, Nupoor; Selvaraj, Ashok; KrishnaKumaar, Lakshmi; Kumar, Gopal Ramesh

    2015-01-01

    Caldicellulosiruptor saccharolyticus has proven itself to be an excellent candidate for biological hydrogen (H2) production, but still it has major drawbacks like sensitivity to high osmotic pressure and low volumetric H2 productivity, which should be considered before it can be used industrially. A whole genome re-annotation work has been carried out as an attempt to update the incomplete genome information that causes gap in the knowledge especially in the area of metabolic engineering, to improve the H2 producing capabilities of C. saccharolyticus. Whole genome re-annotation was performed through manual means for 2,682 Coding Sequences (CDSs). Bioinformatics tools based on sequence similarity, motif search, phylogenetic analysis and fold recognition were employed for re-annotation. Our methodology could successfully add functions for 409 hypothetical proteins (HPs), 46 proteins previously annotated as putative and assigned more accurate functions for the known protein sequences. Homology based gene annotation has been used as a standard method for assigning function to novel proteins, but over the past few years many non-homology based methods such as genomic context approaches for protein function prediction have been developed. Using non-homology based functional prediction methods, we were able to assign cellular processes or physical complexes for 249 hypothetical sequences. Our re-annotation pipeline highlights the addition of 231 new CDSs generated from MicroScope Platform, to the original genome with functional prediction for 49 of them. The re-annotation of HPs and new CDSs is stored in the relational database that is available on the MicroScope web-based platform. In parallel, a comparative genome analyses were performed among the members of genus Caldicellulosiruptor to understand the function and evolutionary processes. Further, with results from integrated re-annotation studies (homology and genomic context approach), we strongly suggest that Csac

  2. Unlimited Thirst for Genome Sequencing, Data Interpretation, and Database Usage in Genomic Era: The Road towards Fast-Track Crop Plant Improvement

    PubMed Central

    Govindaraj, Mahalingam

    2015-01-01

    The number of sequenced crop genomes and associated genomic resources is growing rapidly with the advent of inexpensive next generation sequencing methods. Databases have become an integral part of all aspects of science research, including basic and applied plant and animal sciences. The importance of databases keeps increasing as the volume of datasets from direct and indirect genomics, as well as other omics approaches, keeps expanding in recent years. The databases and associated web portals provide at a minimum a uniform set of tools and automated analysis across a wide range of crop plant genomes. This paper reviews some basic terms and considerations in dealing with crop plant databases utilization in advancing genomic era. The utilization of databases for variation analysis with other comparative genomics tools, and data interpretation platforms are well described. The major focus of this review is to provide knowledge on platforms and databases for genome-based investigations of agriculturally important crop plants. The utilization of these databases in applied crop improvement program is still being achieved widely; otherwise, the end for sequencing is not far away. PMID:25874133

  3. Functional annotation of hypothetical proteins – A review

    PubMed Central

    Sivashankari, Selvarajan; Shanmughavel, Piramanayagam

    2006-01-01

    The complete human genome sequences in the public database provide ways to understand the blue print of life. As of June 29, 2006, 27 archaeal, 326 bacterial and 21 eukaryotes is complete genomes are available and the sequencing for 316 bacterial, 24 archaeal, 126 eukaryotic genomes are in progress. The traditional biochemical/molecular experiments can assign accurate functions for genes in these genomes. However, the process is time-consuming and costly. Despite several efforts, only 50-60 % of genes have been annotated in most completely sequenced genomes. Automated genome sequence analysis and annotation may provide ways to understand genomes. Thus, determination of protein function is one of the challenging problems of the post-genome era. This demands bioinformatics to predict functions of un-annotated protein sequences by developing efficient tools. Here, we discuss some of the recent and popular approaches developed in Bioinformatics to predict functions for hypothetical proteins. PMID:17597916

  4. Semantic annotation for live and posterity logging of video documents

    NASA Astrophysics Data System (ADS)

    Bertini, Marco; Del Bimbo, Alberto; Nunziati, W.

    2003-06-01

    Broadcasters usually envision two basic applications for video databases: Live Logging and Posterity Logging. The former aims at providing effective annotation of video in quasi-real time and supports extraction of meaningful clips from the live stream; it is usually performed by assistant producers working at the same location of the event. The latter provides annotation for later reuse of video material and is the prerequisite for retrieval by content from video digital libraries; it is performed by trained librarians. Both require that annotation is performed, at a great extent, automatically. Video information structure must encompass both low-intermediate level video organization and event relationships that define specific highlights and situations. Analysis of the visual data of the video stream permits to extract hints, identify events and detect highlights. All of this must be supported by a-priori knowledge of the video domain and effective reasoning engines capable to capture the inherent semantics of the visual events.

  5. Scripps Genome ADVISER: Annotation and Distributed Variant Interpretation SERver

    PubMed Central

    Pham, Phillip H.; Shipman, William J.; Erikson, Galina A.; Schork, Nicholas J.; Torkamani, Ali

    2015-01-01

    Interpretation of human genomes is a major challenge. We present the Scripps Genome ADVISER (SG-ADVISER) suite, which aims to fill the gap between data generation and genome interpretation by performing holistic, in-depth, annotations and functional predictions on all variant types and effects. The SG-ADVISER suite includes a de-identification tool, a variant annotation web-server, and a user interface for inheritance and annotation-based filtration. SG-ADVISER allows users with no bioinformatics expertise to manipulate large volumes of variant data with ease – without the need to download large reference databases, install software, or use a command line interface. SG-ADVISER is freely available at genomics.scripps.edu/ADVISER. PMID:25706643

  6. Processing sequence annotation data using the Lua programming language.

    PubMed

    Ueno, Yutaka; Arita, Masanori; Kumagai, Toshitaka; Asai, Kiyoshi

    2003-01-01

    The data processing language in a graphical software tool that manages sequence annotation data from genome databases should provide flexible functions for the tasks in molecular biology research. Among currently available languages we adopted the Lua programming language. It fulfills our requirements to perform computational tasks for sequence map layouts, i.e. the handling of data containers, symbolic reference to data, and a simple programming syntax. Upon importing a foreign file, the original data are first decomposed in the Lua language while maintaining the original data schema. The converted data are parsed by the Lua interpreter and the contents are stored in our data warehouse. Then, portions of annotations are selected and arranged into our catalog format to be depicted on the sequence map. Our sequence visualization program was successfully implemented, embedding the Lua language for processing of annotation data and layout script. The program is available at http://staff.aist.go.jp/yutaka.ueno/guppy/.

  7. Rapid identification of microorganisms by mass spectrometry: improved performance by incorporation of in-house spectral data into a commercial database.

    PubMed

    Sogawa, Kazuyuki; Watanabe, Masaharu; Sato, Kenichi; Segawa, Syunsuke; Miyabe, Akiko; Murata, Syota; Saito, Tomoko; Nomura, Fumio

    2012-06-01

    Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) is increasingly used as a microbial diagnostic method for species identification of pathogens. However, MALDI-TOF identification of bacteria at the species level remains unsatisfactory, with the major problem being an incomplete database that still needs refinement and expansion. Augmentation of the original MALDI BioTyper 2.0 (Bruker) database by incorporating mass spectra obtained in-house from clinical isolates may increase the identification rate at the species level. We conducted a prospective study to assess whether the augmented database can improve the performance of MALDI-TOF MS for routine identification of species. Cluster analyses revealed distinct differences in MS spectral profiles of clinical isolates obtained in our hospital and those of ATCC strains in the Bruker database. In the first part of the study, which was performed over 3 weeks, 259 bacterial isolates were subjected to analysis by MALDI-TOF MS, and MS spectra of 229 successfully identified isolates (49 species) were incorporated into the original database to give the augmented Bruker-Chiba database. In a second separate analysis, the concordance of identification of 498 clinical isolates of the 49 species with conventional methods was 87.1% (434/498) with the commercial Bruker database and 98.0% (488/498) using the Bruker-Chiba database. These results indicate that refinement of a commercial database can be achieved relatively easy and effectively by incorporating MS spectra of clinical isolates obtained in a clinical laboratory.

  8. MaGe: a microbial genome annotation system supported by synteny results.

    PubMed

    Vallenet, David; Labarre, Laurent; Rouy, Zoé; Barbe, Valérie; Bocs, Stéphanie; Cruveiller, Stéphane; Lajus, Aurélie; Pascal, Géraldine; Scarpelli, Claude; Médigue, Claudine

    2006-01-01

    Magnifying Genomes (MaGe) is a microbial genome annotation system based on a relational database containing information on bacterial genomes, as well as a web interface to achieve genome annotation projects. Our system allows one to initiate the annotation of a genome at the early stage of the finishing phase. MaGe's main features are (i) integration of annotation data from bacterial genomes enhanced by a gene coding re-annotation process using accurate gene models, (ii) integration of results obtained with a wide range of bioinformatics methods, among which exploration of gene context by searching for conserved synteny and reconstruction of metabolic pathways, (iii) an advanced web interface allowing multiple users to refine the automatic assignment of gene product functions. MaGe is also linked to numerous well-known biological databases and systems. Our system has been thoroughly tested during the annotation of complete bacterial genomes (Acinetobacter baylyi ADP1, Pseudoalteromonas haloplanktis, Frankia alni) and is currently used in the context of several new microbial genome annotation projects. In addition, MaGe allows for annotation curation and exploration of already published genomes from various genera (e.g. Yersinia, Bacillus and Neisseria). MaGe can be accessed at http://www.genoscope.cns.fr/agc/mage. PMID:16407324

  9. Caliper Context Annotation Library

    SciTech Connect

    2015-09-30

    To understand the performance of parallel programs, developers need to be able to relate performance measurement data with context information, such as the call path / line numbers or iteration numbers where measurements were taken. Caliper provides a generic way to specify and collect multi-dimensional context information across the software stack, and provide ti to third-party measurement tools or write it into a file or database in the form of context streams.

  10. GenColors: annotation and comparative genomics of prokaryotes made easy.

    PubMed

    Romualdi, Alessandro; Felder, Marius; Rose, Dominic; Gausmann, Ulrike; Schilhabel, Markus; Glöckner, Gernot; Platzer, Matthias; Sühnel, Jürgen

    2007-01-01

    GenColors (gencolors.fli-leibniz.de) is a new web-based software/database system aimed at an improved and accelerated annotation of prokaryotic genomes considering information on related genomes and making extensive use of genome comparison. It offers a seamless integration of data from ongoing sequencing projects and annotated genomic sequences obtained from GenBank. A variety of export/import filters manages an effective data flow from sequence assembly and manipulation programs (e.g., GAP4) to GenColors and back as well as to standard GenBank file(s). The genome comparison tools include best bidirectional hits, gene conservation, syntenies, and gene core sets. Precomputed UniProt matches allow annotation and analysis in an effective manner. In addition to these analysis options, base-specific quality data (coverage and confidence) can also be handled if available. The GenColors system can be used both for annotation purposes in ongoing genome projects and as an analysis tool for finished genomes. GenColors comes in two types, as dedicated genome browsers and as the Jena Prokaryotic Genome Viewer (JPGV). Dedicated genome browsers contain genomic information on a set of related genomes and offer a large number of options for genome comparison. The system has been efficiently used in the genomic sequencing of Borrelia garinii and is currently applied to various ongoing genome projects on Borrelia, Legionella, Escherichia, and Pseudomonas genomes. One of these dedicated browsers, the Spirochetes Genome Browser (sgb.fli-leibniz.de) with Borrelia, Leptospira, and Treponema genomes, is freely accessible. The others will be released after finalization of the corresponding genome projects. JPGV (jpgv.fli-leibniz.de) offers information on almost all finished bacterial genomes, as compared to the dedicated browsers with reduced genome comparison functionality, however. As of January 2006, this viewer includes 632 genomic elements (e.g., chromosomes and plasmids) of 293

  11. Expressed Peptide Tags: An additional layer of data for genome annotation

    SciTech Connect

    Savidor, Alon; Donahoo, Ryan S; Hurtado-Gonzales, Oscar; Verberkmoes, Nathan C; Shah, Manesh B; Lamour, Kurt H; McDonald, W Hayes

    2006-01-01

    While genome sequencing is becoming ever more routine, genome annotation remains a challenging process. Identification of the coding sequences within the genomic milieu presents a tremendous challenge, especially for eukaryotes with their complex gene architectures. Here we present a method to assist the annotation process through the use of proteomic data and bioinformatics. Mass spectra of digested protein preparations of the organism of interest were acquired and searched against a protein database created by a six frame translation of the genome. The identified peptides were mapped back to the genome, compared to the current annotation, and then categorized as supporting or extending the current genome annotation. We named the classified peptides Expressed Peptide Tags (EPTs). The well annotated bacterium Rhodopseudomonas palustris was used as a control for the method and showed high degree of correlation between EPT mapping and the current annotation, with 86% of the EPTs confirming existing gene calls and less than 1% of the EPTs expanding on the current annotation. The eukaryotic plant pathogens Phytophthora ramorum and Phytophthora sojae, whose genomes have been recently sequenced and are much less well annotated, were also subjected to this method. A series of algorithmic steps were taken to increase the confidence of EPT identification for these organisms, including generation of smaller sub-databases to be searched against, and definition of EPT criteria that accommodates the more complex eukaryotic gene architecture. As expected, the analysis of the Phytophthora species showed less correlation between EPT mapping and their current annotation. While ~77% of Phytophthora EPTs supported the current annotation, a portion of them (7.2% and 12.6% for P. ramorum and P. sojae, respectively) suggested modification to current gene calls or identified novel genes that were missed by the current genome annotation of these organisms.

  12. Annotated Bibliography on Religious Development.

    ERIC Educational Resources Information Center

    Bucher, Anton A.; Reich, K. Helmut

    1991-01-01

    Presents an annotated bibliography on religious development that covers the areas of psychology and religion, measurement of religiousness, religious development during the life cycle, religious experiences, conversion, religion and morality, and images of God. (Author/BB)

  13. Patient Education: An Annotated Bibliography.

    ERIC Educational Resources Information Center

    Simmons, Jeannette

    Topics included in this annotated bibliography on patient education are (1) background on development of patient education programs, (2) patient education interventions, (3) references for health professionals, and (4) research and evaluation in patient education. (TA)

  14. The Disease and Gene Annotations (DGA): an annotation resource for human disease.

    PubMed

    Peng, Kai; Xu, Wei; Zheng, Jianyong; Huang, Kegui; Wang, Huisong; Tong, Jiansong; Lin, Zhifeng; Liu, Jun; Cheng, Wenqing; Fu, Dong; Du, Pan; Kibbe, Warren A; Lin, Simon M; Xia, Tian

    2013-01-01

    Disease and Gene Annotations database (DGA, http://dga.nubic.northwestern.edu) is a collaborative effort aiming to provide a comprehensive and integrative annotation of the human genes in disease network context by integrating computable controlled vocabulary of the Disease Ontology (DO version 3 revision 2510, which has 8043 inherited, developmental and acquired human diseases), NCBI Gene Reference Into Function (GeneRIF) and molecular interaction network (MIN). DGA integrates these resources together using semantic mappings to build an integrative set of disease-to-gene and gene-to-gene relationships with excellent coverage based on current knowledge. DGA is kept current by periodically reparsing DO, GeneRIF, and MINs. DGA provides a user-friendly and interactive web interface system enabling users to efficiently query, download and visualize the DO tree structure and annotations as a tree, a network graph or a tabular list. To facilitate integrative analysis, DGA provides a web service Application Programming Interface for integration with external analytic tools.

  15. The Society of Thoracic Surgeons Adult Cardiac Surgery Database: The Driving Force for Improvement in Cardiac Surgery.

    PubMed

    Winkley Shroyer, Annie Laurie; Bakaeen, Faisal; Shahian, David M; Carr, Brendan M; Prager, Richard L; Jacobs, Jeffrey P; Ferraris, Victor; Edwards, Fred; Grover, Frederick L

    2015-01-01

    Initiated in 1989, the Society of Thoracic Surgeons (STS) Adult Cardiac Surgery Database (ACSD) includes more than 1085 participating centers, representing 90%-95% of current US-based adult cardiac surgery hospitals. Since its inception, the primary goal of the STS ACSD has been to use clinical data to track and improve cardiac surgical outcomes. Patients' preoperative risk characteristics, procedure-related processes of care, and clinical outcomes data have been captured and analyzed, with timely risk-adjusted feedback reports to participating providers. In 2006, STS initiated an external audit process to evaluate STS ACSD completeness and accuracy. Given the extremely high inter-rater reliability and completeness rates of STS ACSD, it is widely regarded as the "gold standard" for benchmarking cardiac surgery risk-adjusted outcomes. Over time, STS ACSD has expanded its quality horizons beyond the traditional focus on isolated, risk-adjusted short-term outcomes such as perioperative morbidity and mortality. New quality indicators have evolved including composite measures of key processes of care and outcomes (risk-adjusted morbidity and risk-adjusted mortality), longer-term outcomes, and readmissions. Resource use and patient-reported outcomes would be added in the future. These additional metrics provide a more comprehensive perspective on quality as well as additional end points. Widespread acceptance and use of STS ACSD has led to a cultural transformation within cardiac surgery by providing nationally benchmarked data for internal quality assessment, aiding data-driven quality improvement activities, serving as the basis for a voluntary public reporting program, advancing cardiac surgery care through STS ACSD-based research, and facilitating data-driven informed consent dialogues and alternative treatment-related discussions.

  16. SelenoDB 2.0: annotation of selenoprotein genes in animals and their genetic diversity in humans

    PubMed Central

    Romagné, Frédéric; Santesmasses, Didac; White, Louise; Sarangi, Gaurab K.; Mariotti, Marco; Hübler, Ron; Weihmann, Antje; Parra, Genís; Gladyshev, Vadim N.; Guigó, Roderic; Castellano, Sergi

    2014-01-01

    SelenoDB (http://www.selenodb.org) aims to provide high-quality annotations of selenoprotein genes, proteins and SECIS elements. Selenoproteins are proteins that contain the amino acid selenocysteine (Sec) and the first release of the database included annotations for eight species. Since the release of SelenoDB 1.0 many new animal genomes have been sequenced. The annotations of selenoproteins in new genomes usually contain many errors in major databases. For this reason, we have now fully annotated selenoprotein genes in 58 animal genomes. We provide manually curated annotations for human selenoproteins, whereas we use an automatic annotation pipeline to annotate selenoprotein genes in other animal genomes. In addition, we annotate the homologous genes containing cysteine (Cys) instead of Sec. Finally, we have surveyed genetic variation in the annotated genes in humans. We use exon capture and resequencing approaches to identify single-nucleotide polymorphisms in more than 50 human populations around the world. We thus present a detailed view of the genetic divergence of Sec- and Cys-containing genes in animals and their diversity in humans. The addition of these datasets into the second release of the database provides a valuable resource for addressing medical and evolutionary questions in selenium biology. PMID:24194593

  17. SelenoDB 2.0: annotation of selenoprotein genes in animals and their genetic diversity in humans.

    PubMed

    Romagné, Frédéric; Santesmasses, Didac; White, Louise; Sarangi, Gaurab K; Mariotti, Marco; Hübler, Ron; Weihmann, Antje; Parra, Genís; Gladyshev, Vadim N; Guigó, Roderic; Castellano, Sergi

    2014-01-01

    SelenoDB (http://www.selenodb.org) aims to provide high-quality annotations of selenoprotein genes, proteins and SECIS elements. Selenoproteins are proteins that contain the amino acid selenocysteine (Sec) and the first release of the database included annotations for eight species. Since the release of SelenoDB 1.0 many new animal genomes have been sequenced. The annotations of selenoproteins in new genomes usually contain many errors in major databases. For this reason, we have now fully annotated selenoprotein genes in 58 animal genomes. We provide manually curated annotations for human selenoproteins, whereas we use an automatic annotation pipeline to annotate selenoprotein genes in other animal genomes. In addition, we annotate the homologous genes containing cysteine (Cys) instead of Sec. Finally, we have surveyed genetic variation in the annotated genes in humans. We use exon capture and resequencing approaches to identify single-nucleotide polymorphisms in more than 50 human populations around the world. We thus present a detailed view of the genetic divergence of Sec- and Cys-containing genes in animals and their diversity in humans. The addition of these datasets into the second release of the database provides a valuable resource for addressing medical and evolutionary questions in selenium biology.

  18. Automated semantic annotation of rare disease cases: a case study

    PubMed Central

    Taboada, Maria; Rodríguez, Hadriana; Martínez, Diego; Pardo, María; Sobrido, María Jesús

    2014-01-01

    Motivation: As the number of clinical reports in the peer-reviewed medical literature keeps growing, there is an increasing need for online search tools to find and analyze publications on patients with similar clinical characteristics. This problem is especially critical and challenging for rare diseases, where publications of large series are scarce. Through an applied example, we illustrate how to automatically identify new relevant cases and semantically annotate the relevant literature about patient case reports to capture the phenotype of a rare disease named cerebrotendinous xanthomatosis. Results: Our results confirm that it is possible to automatically identify new relevant case reports with a high precision and to annotate them with a satisfactory quality (74% F-measure). Automated annotation with an emphasis to entirely describe all phenotypic abnormalities found in a disease may facilitate curation efforts by supplying phenotype retrieval and assessment of their frequency. Availability and Supplementary information: http://www.usc.es/keam/Phenotype Annotation/. Database URL: http://www.usc.es/keam/PhenotypeAnnotation/ PMID:24903515

  19. Variation Ontology for annotation of variation effects and mechanisms

    PubMed Central

    Vihinen, Mauno

    2014-01-01

    Ontology organizes and formally conceptualizes information in a knowledge domain with a controlled vocabulary having defined terms and relationships between them. Several ontologies have been used to annotate numerous databases in biology and medicine. Due to their unambiguous nature, ontological annotations facilitate systematic description and data organization, data integration and mining, and pattern recognition and statistics, as well as development of analysis and prediction tools. The Variation Ontology (VariO) was developed to allow the annotation of effects, consequences, and mechanisms of DNA, RNA, and protein variations. Variation types are systematically organized, and a detailed description of effects and mechanisms is possible. VariO is for annotating the variant, not the normal-state features or properties, and requires a reference (e.g., reference sequence, reference-state property, activity, etc.) compared to which the changes are indicated. VariO is versatile and can be used for variations ranging from genomic multiplications to single nucleotide or amino acid changes, whether of genetic or nongenetic origin. VariO annotations are position-specific and can be used for variations in any organism. PMID:24162187

  20. Mouse genome annotation by the RefSeq project.

    PubMed

    McGarvey, Kelly M; Goldfarb, Tamara; Cox, Eric; Farrell, Catherine M; Gupta, Tripti; Joardar, Vinita S; Kodali, Vamsi K; Murphy, Michael R; O'Leary, Nuala A; Pujar, Shashikant; Rajput, Bhanu; Rangwala, Sanjida H; Riddick, Lillian D; Webb, David; Wright, Mathew W; Murphy, Terence D; Pruitt, Kim D

    2015-10-01

    Complete and accurate annotation of the mouse genome is critical to the advancement of research conducted on this important model organism. The National Center for Biotechnology Information (NCBI) develops and maintains many useful resources to assist the mouse research community. In particular, the reference sequence (RefSeq) database provides high-quality annotation of multiple mouse genome assemblies using a combinatorial approach that leverages computation, manual curation, and collaboration. Implementation of this conservative and rigorous approach, which focuses on representation of only full-length and non-redundant data, produces high-quality annotation products. RefSeq records explicitly link sequences to current knowledge in a timely manner, updating public records regularly and rapidly in response to nomenclature updates, addition of new relevant publications, collaborator discussion, and user feedback. Whole genome re-annotation is also conducted at least every 12-18 months, and often more frequently in response to assembly updates or availability of informative data. This article highlights key features and advantages of RefSeq genome annotation products and presents an overview of NCBI processes to generate these data. Further discussion of NCBI's resources highlights useful features and the best methods for accessing our data.

  1. Enhanced Acylcarnitine Annotation in High-Resolution Mass Spectrometry Data: Fragmentation Analysis for the Classification and Annotation of Acylcarnitines

    PubMed Central

    van der Hooft, Justin J. J.; Ridder, Lars; Barrett, Michael P.; Burgess, Karl E. V.

    2015-01-01

    Metabolite annotation and identification are primary challenges in untargeted metabolomics experiments. Rigorous workflows for reliable annotation of mass features with chemical structures or compound classes are needed to enhance the power of untargeted mass spectrometry. High-resolution mass spectrometry considerably improves the confidence in assigning elemental formulas to mass features in comparison to nominal mass spectrometry, and embedding of fragmentation methods enables more reliable metabolite annotations and facilitates metabolite classification. However, the analysis of mass fragmentation spectra can be a time-consuming step and requires expert knowledge. This study demonstrates how characteristic fragmentations, specific to compound classes, can be used to systematically analyze their presence in complex biological extracts like urine that have undergone untargeted mass spectrometry combined with data dependent or targeted fragmentation. Human urine extracts were analyzed using normal phase liquid chromatography (hydrophilic interaction chromatography) coupled to an Ion Trap-Orbitrap hybrid instrument. Subsequently, mass chromatograms and collision-induced dissociation and higher-energy collisional dissociation (HCD) fragments were annotated using the freely available MAGMa software1. Acylcarnitines play a central role in energy metabolism by transporting fatty acids into the mitochondrial matrix. By filtering on a combination of a mass fragment and neutral loss designed based on the MAGMa fragment annotations, we were able to classify and annotate 50 acylcarnitines in human urine extracts, based on high-resolution mass spectrometry HCD fragmentation spectra at different energies for all of them. Of these annotated acylcarnitines, 31 are not described in HMDB yet and for only 4 annotated acylcarnitines the fragmentation spectra could be matched to reference spectra. Therefore, we conclude that the use of mass fragmentation filters within the context

  2. NCBI prokaryotic genome annotation pipeline.

    PubMed

    Tatusova, Tatiana; DiCuccio, Michael; Badretdin, Azat; Chetvernin, Vyacheslav; Nawrocki, Eric P; Zaslavsky, Leonid; Lomsadze, Alexandre; Pruitt, Kim D; Borodovsky, Mark; Ostell, James

    2016-08-19

    Recent technological advances have opened unprecedented opportunities for large-scale sequencing and analysis of populations of pathogenic species in disease outbreaks, as well as for large-scale diversity studies aimed at expanding our knowledge across the whole domain of prokaryotes. To meet the challenge of timely interpretation of structure, function and meaning of this vast genetic information, a comprehensive approach to automatic genome annotation is critically needed. In collaboration with Georgia Tech, NCBI has developed a new approach to genome annotation that combines alignment based methods with methods of predicting protein-coding and RNA genes and other functional elements directly from sequence. A new gene finding tool, GeneMarkS+, uses the combined evidence of protein and RNA placement by homology as an initial map of annotation to generate and modify ab initio gene predictions across the whole genome. Thus, the new NCBI's Prokaryotic Genome Annotation Pipeline (PGAP) relies more on sequence similarity when confident comparative data are available, while it relies more on statistical predictions in the absence of external evidence. The pipeline provides a framework for generation and analysis of annotation on the full breadth of prokaryotic taxonomy. For additional information on PGAP see https://www.ncbi.nlm.nih.gov/genome/annotation_prok/ and the NCBI Handbook, https://www.ncbi.nlm.nih.gov/books/NBK174280/. PMID:27342282

  3. NCBI prokaryotic genome annotation pipeline.

    PubMed

    Tatusova, Tatiana; DiCuccio, Michael; Badretdin, Azat; Chetvernin, Vyacheslav; Nawrocki, Eric P; Zaslavsky, Leonid; Lomsadze, Alexandre; Pruitt, Kim D; Borodovsky, Mark; Ostell, James

    2016-08-19

    Recent technological advances have opened unprecedented opportunities for large-scale sequencing and analysis of populations of pathogenic species in disease outbreaks, as well as for large-scale diversity studies aimed at expanding our knowledge across the whole domain of prokaryotes. To meet the challenge of timely interpretation of structure, function and meaning of this vast genetic information, a comprehensive approach to automatic genome annotation is critically needed. In collaboration with Georgia Tech, NCBI has developed a new approach to genome annotation that combines alignment based methods with methods of predicting protein-coding and RNA genes and other functional elements directly from sequence. A new gene finding tool, GeneMarkS+, uses the combined evidence of protein and RNA placement by homology as an initial map of annotation to generate and modify ab initio gene predictions across the whole genome. Thus, the new NCBI's Prokaryotic Genome Annotation Pipeline (PGAP) relies more on sequence similarity when confident comparative data are available, while it relies more on statistical predictions in the absence of external evidence. The pipeline provides a framework for generation and analysis of annotation on the full breadth of prokaryotic taxonomy. For additional information on PGAP see https://www.ncbi.nlm.nih.gov/genome/annotation_prok/ and the NCBI Handbook, https://www.ncbi.nlm.nih.gov/books/NBK174280/.

  4. Comparative Omics-Driven Genome Annotation Refinement: Application across Yersiniae

    SciTech Connect

    Rutledge, Alexandra C.; Jones, Marcus B.; Chauhan, Sadhana; Purvine, Samuel O.; Sanford, James; Monroe, Matthew E.; Brewer, Heather M.; Payne, Samuel H.; Ansong, Charles; Frank, Bryan C.; Smith, Richard D.; Peterson, Scott; Motin, Vladimir L.; Adkins, Joshua N.

    2012-03-27

    Genome sequencing continues to be a rapidly evolving technology, yet most downstream aspects of genome annotation pipelines remain relatively stable or are even being abandoned. To date, the perceived value of manual curation for genome annotations is not offset by the real cost and time associated with the process. In order to balance the large number of sequences generated, the annotation process is now performed almost exclusively in an automated fashion for most genome sequencing projects. One possible way to reduce errors inherent to automated computational annotations is to apply data from 'omics' measurements (i.e. transcriptional and proteomic) to the un-annotated genome with a proteogenomic-based approach. This approach does require additional experimental and bioinformatics methods to include omics technologies; however, the approach is readily automatable and can benefit from rapid developments occurring in those research domains as well. The annotation process can be improved by experimental validation of transcription and translation and aid in the discovery of annotation errors. Here the concept of annotation refinement has been extended to include a comparative assessment of genomes across closely related species, as is becoming common in sequencing efforts. Transcriptomic and proteomic data derived from three highly similar pathogenic Yersiniae (Y. pestis CO92, Y. pestis pestoides F, and Y. pseudotuberculosis PB1/+) was used to demonstrate a comprehensive comparative omic-based annotation methodology. Peptide and oligo measurements experimentally validated the expression of nearly 40% of each strain's predicted proteome and revealed the identification of 28 novel and 68 previously incorrect protein-coding sequences (e.g., observed frameshifts, extended start sites, and translated pseudogenes) within the three current Yersinia genome annotations. Gene loss is presumed to play a major role in Y. pestis acquiring its niche as a virulent pathogen, thus

  5. Developing a biocuration workflow for AgBase, a non-model organism database

    PubMed Central

    Pillai, Lakshmi; Chouvarine, Philippe; Tudor, Catalina O.; Schmidt, Carl J.; Vijay-Shanker, K.; McCarthy, Fiona M.

    2012-01-01

    AgBase provides annotation for agricultural gene products using the Gene Ontology (GO) and Plant Ontology, as appropriate. Unlike model organism species, agricultural species have a body of literature that does not just focus on gene function; to improve efficiency, we use text mining to identify literature for curation. The first component of our annotation interface is the gene prioritization interface that ranks gene products for annotation. Biocurators select the top-ranked gene and mark annotation for these genes as ‘in progress’ or ‘completed’; links enable biocurators to move directly to our biocuration interface (BI). Our BI includes all current GO annotation for gene products and is the main interface to add/modify AgBase curation data. The BI also displays Extracting Genic Information from Text (eGIFT) results for each gene product. eGIFT is a web-based, text-mining tool that associates ranked, informative terms (iTerms) and the articles and sentences containing them, with genes. Moreover, iTerms are linked to GO terms, where they match either a GO term name or a synonym. This enables AgBase biocurators to rapidly identify literature for further curation based on possible GO terms. Because most agricultural species do not have standardized literature, eGIFT searches all gene names and synonyms to associate articles with genes. As many of the gene names can be ambiguous, eGIFT applies a disambiguation step to remove matches that do not correspond to this gene, and filtering is applied to remove abstracts that mention a gene in passing. The BI is linked to our Journal Database (JDB) where corresponding journal citations are stored. Just as importantly, biocurators also add to the JDB citations that have no GO annotation. The AgBase BI also supports bulk annotation upload to facilitate our Inferred from electronic annotation of agricultural gene products. All annotations must pass standard GO Consortium quality checking before release in Ag

  6. DbMap: improving database interoperability issues in medical software using a simple, Java-Xml based solution.

    PubMed Central

    Karadimas, H.; Hemery, F.; Roland, P.; Lepage, E.

    2000-01-01

    In medical software development, the use of databases plays a central role. However, most of the databases have heterogeneous encoding and data models. To deal with these variations in the application code directly is error-prone and reduces the potential reuse of the produced software. Several approaches to overcome these limitations have been proposed in the medical database literature, which will be presented. We present a simple solution, based on a Java library, and a central Metadata description file in XML. This development approach presents several benefits in software design and development cycles, the main one being the simplicity in maintenance. PMID:11079915

  7. Enzyme reaction annotation using cloud techniques.

    PubMed

    Huang, Chuan-Ching; Lin, Chun-Yuan; Chang, Cheng-Wen; Tang, Chuan Yi

    2013-01-01

    An understanding of the activities of enzymes could help to elucidate the metabolic pathways of thousands of chemical reactions that are catalyzed by enzymes in living systems. Sophisticated applications such as drug design and metabolic reconstruction could be developed using accurate enzyme reaction annotation. Because accurate enzyme reaction annotation methods create potential for enhanced production capacity in these applications, they have received greater attention in the global market. We propose the enzyme reaction prediction (ERP) method as a novel tool to deduce enzyme reactions from domain architecture. We used several frequency relationships between architectures and reactions to enhance the annotation rates for single and multiple catalyzed reactions. The deluge of information which arose from high-throughput techniques in the postgenomic era has improved our understanding of biological data, although it presents obstacles in the data-processing stage. The high computational capacity provided by cloud computing has resulted in an exponential growth in the volume of incoming data. Cloud services also relieve the requirement for large-scale memory space required by this approach to analyze enzyme kinetic data. Our tool is designed as a single execution file; thus, it could be applied to any cloud platform in which multiple queries are supported.

  8. Objective-guided image annotation.

    PubMed

    Mao, Qi; Tsang, Ivor Wai-Hung; Gao, Shenghua

    2013-04-01

    Automatic image annotation, which is usually formulated as a multi-label classification problem, is one of the major tools used to enhance the semantic understanding of web images. Many multimedia applications (e.g., tag-based image retrieval) can greatly benefit from image annotation. However, the insufficient performance of image annotation methods prevents these applications from being practical. On the other hand, specific measures are usually designed to evaluate how well one annotation method performs for a specific objective or application, but most image annotation methods do not consider optimization of these measures, so that they are inevitably trapped into suboptimal performance of these objective-specific measures. To address this issue, we first summarize a variety of objective-guided performance measures under a unified representation. Our analysis reveals that macro-averaging measures are very sensitive to infrequent keywords, and hamming measure is easily affected by skewed distributions. We then propose a unified multi-label learning framework, which directly optimizes a variety of objective-specific measures of multi-label learning tasks. Specifically, we first present a multilayer hierarchical structure of learning hypotheses for multi-label problems based on which a variety of loss functions with respect to objective-guided measures are defined. And then, we formulate these loss functions as relaxed surrogate functions and optimize them by structural SVMs. According to the analysis of various measures and the high time complexity of optimizing micro-averaging measures, in this paper, we focus on example-based measures that are tailor-made for image annotation tasks but are seldom explored in the literature. Experiments show consistency with the formal analysis on two widely used multi-label datasets, and demonstrate the superior performance of our proposed method over state-of-the-art baseline methods in terms of example-based measures on four

  9. Uncertainty modeling for ontology-based mammography annotation with intelligent BI-RADS scoring.

    PubMed

    Bulu, Hakan; Alpkocak, Adil; Balci, Pinar

    2013-05-01

    This paper presents an ontology-based annotation system and BI-RADS (Breast Imaging Reporting and Data System) score reasoning with Semantic Web technologies in mammography. The annotation system is based on the Mammography Annotation Ontology (MAO) where the BI-RADS score reasoning works. However, ontologies are based on crisp logic and they cannot handle uncertainty. Consequently, we propose a Bayesian-based approach to model uncertainty in mammography ontology and make reasoning possible using BI-RADS scores with SQWRL (Semantic Query-enhanced Web Rule Language). First, we give general information about our system and present details of mammography annotation ontology, its main concepts and relationships. Then, we express uncertainty in mammography and present approaches to handle uncertainty issues. System is evaluated with a manually annotated dataset DEMS (Dokuz Eylul University Mammography Set) and DDSM (Digital Database for Screening Mammography). We give the result of experimentations in terms of accuracy, sensitivity, precision and uncertainty level measures.

  10. MaizeGDB, the maize model organism database

    Technology Transfer Automated Retrieval System (TEKTRAN)

    MaizeGDB is the maize research community's database for maize genetic and genomic information. In this seminar I will outline our current endeavors including a full website redesign, the status of maize genome assembly and annotation projects, and work toward genome functional annotation. Mechanis...

  11. Gene3D: comprehensive structural and functional annotation of genomes.

    PubMed

    Yeats, Corin; Lees, Jonathan; Reid, Adam; Kellam, Paul; Martin, Nigel; Liu, Xinhui; Orengo, Christine

    2008-01-01

    Gene3D provides comprehensive structural and functional annotation of most available protein sequences, including the UniProt, RefSeq and Integr8 resources. The main structural annotation is generated through scanning these sequences against the CATH structural domain database profile-HMM library. CATH is a database of manually derived PDB-based structural domains, placed within a hierarchy reflecting topology, homology and conservation and is able to infer more ancient and divergent homology relationships than sequence-based approaches. This data is supplemented with Pfam-A, other non-domain structural predictions (i.e. coiled coils) and experimental data from UniProt. In order to enhance the investigations possible with this data, we have also incorporated a variety of protein annotation resources, including protein-protein interaction data, GO functional assignments, KEGG pathways, FUNCAT functional descriptions and links to microarray expression data. All of this data can be accessed through a newly re-designed website that has a focus on flexibility and clarity, with searches that can be restricted to a single genome or across the entire sequence database. Currently Gene3D contains over 3.5 million domain assignments for nearly 5 million proteins including 527 completed genomes. This is available at: http://gene3d.biochem.ucl.ac.uk/ PMID:18032434

  12. Collective dynamics of social annotation.

    PubMed

    Cattuto, Ciro; Barrat, Alain; Baldassarri, Andrea; Schehr, Gregory; Loreto, Vittorio

    2009-06-30

    The enormous increase of popularity and use of the worldwide web has led in the recent years to important changes in the ways people communicate. An interesting example of this fact is provided by the now very popular social annotation systems, through which users annotate resources (such as web pages or digital photographs) with keywords known as "tags." Understanding the rich emergent structures resulting from the uncoordinated actions of users calls for an interdisciplinary effort. In particular concepts borrowed from statistical physics, such as random walks (RWs), and complex networks theory, can effectively contribute to the mathematical modeling of social annotation systems. Here, we show that the process of social annotation can be seen as a collective but uncoordinated exploration of an underlying semantic space, pictured as a graph, through a series of RWs. This modeling framework reproduces several aspects, thus far unexplained, of social annotation, among which are the peculiar growth of the size of the vocabulary used by the community and its complex network structure that represents an externalization of semantic structures grounded in cognition and that are typically hard to access. PMID:19506244

  13. PAZAR: a framework for collection and dissemination of cis-regulatory sequence annotation

    PubMed Central

    Portales-Casamar, Elodie; Kirov, Stefan; Lim, Jonathan; Lithwick, Stuart; Swanson, Magdalena I; Ticoll, Amy; Snoddy, Jay; Wasserman, Wyeth W

    2007-01-01

    PAZAR is an open-access and open-source database of transcription factor and regulatory sequence annotation with associated web interface and programming tools for data submission and extraction. Curated boutique data collections can be maintained and disseminated through the unified schema of the mall-like PAZAR repository. The Pleiades Promoter Project collection of brain-linked regulatory sequences is introduced to demonstrate the depth of annotation possible within PAZAR. PAZAR, located at , is open for business. PMID:17916232

  14. An Annotated Guide and Interactive Database for Solo Horn Repertoire

    ERIC Educational Resources Information Center

    Schouten, Sarah

    2012-01-01

    Given the horn's lengthy history, it is not surprising that many scholars have examined the evolution of the instrument from the natural horn to the modern horn and its expansive repertoire. Numerous dissertations, theses, and treatises illuminate specific elements of the horn's solo repertoire; however, no scholar has produced a…

  15. Modelling of the reactive transport for rock salt-brine in geological repository systems based on improved thermodynamic database (Invited)

    NASA Astrophysics Data System (ADS)

    Müller, W.; Alkan, H.; Xie, M.; Moog, H.; Sonnenthal, E. L.

    2009-12-01

    The release and migration of toxic contaminants from the disposed wastes is one of the main issues in long-term safety assessment of geological repositories. In the engineered and geological barriers around the nuclear waste emplacements chemical interactions between the components of the system may affect the isolation properties considerably. As the chemical issues change the transport properties in the near and far field of a nuclear repository, modelling of the transport should also take the chemistry into account. The reactive transport modelling consists of two main components: a code that combines the possible chemical reactions with thermo-hydrogeological processes interactively and a thermodynamic databank supporting the required parameters for the calculation of the chemical reactions. In the last decade many thermo-hydrogeological codes were upgraded to include the modelling of the chemical processes. TOUGHREACT is one of these codes. This is an extension of the well known simulator TOUGH2 for modelling geoprocesses. The code is developed by LBNL (Lawrence Berkeley National Laboratory, Univ. of California) for the simulation of the multi-phase transport of gas and liquid in porous media including heat transfer. After the release of its first version in 1998, this code has been applied and improved many times in conjunction with considerations for nuclear waste emplacement. A recent version has been extended to calculate ion activities in concentrated salt solutions applying the Pitzer model. In TOUGHREACT, the incorporated equation of state module ECO2N is applied as the EOS module for non-isothermal multiphase flow in a fluid system of H2O-NaCl-CO2. The partitioning of H2O and CO2 between liquid and gas phases is modelled as a function of temperature, pressure, and salinity. This module is applicable for waste repositories being expected to generate or having originally CO2 in the fluid system. The enhanced TOUGHREACT uses an EQ3/6-formatted database

  16. The Aerospace Database data element dictionary with issues and recommendations from the meetings of July 24-25, August 13-14, and September 24-25, 1991

    NASA Technical Reports Server (NTRS)

    1991-01-01

    The present volume contains descriptions of the individual fields (data elements) which comprise the bibliographic records of the Aerospace Database. Indexes by field name and field mnemonic are provided. In addition, the issues and recommendations defined by the NASA STI Database Upgrade Working Group are included as annotations to the individual field descriptions and are listed at the end of the volume. The activities of the Working Group were initiated by the NASA STI Program Coordinating Council as part of an effort to improve overall database quality.

  17. VitisExpDB: A Database Resource for Grape Functional Genomics

    Technology Transfer Automated Retrieval System (TEKTRAN)

    VitisExpDB is an online MySQL-PHP driven relational database that houses annotated EST and gene expression data for Vitis vinifera and non-vinifera grape varieties. Currently, the database stores ~320,000 EST sequences derived from 8 species/hybrids, their annotation details and gene ontology based...

  18. Determining similarity of scientific entities in annotation datasets

    PubMed Central

    Palma, Guillermo; Vidal, Maria-Esther; Haag, Eric; Raschid, Louiqa; Thor, Andreas

    2015-01-01

    Linked Open Data initiatives have made available a diversity of scientific collections where scientists have annotated entities in the datasets with controlled vocabulary terms from ontologies. Annotations encode scientific knowledge, which is captured in annotation datasets. Determining relatedness between annotated entities becomes a building block for pattern mining, e.g. identifying drug–drug relationships may depend on the similarity of the targets that interact with each drug. A diversity of similarity measures has been proposed in the literature to compute relatedness between a pair of entities. Each measure exploits some knowledge including the name, function, relationships with other entities, taxonomic neighborhood and semantic knowledge. We propose a novel general-purpose annotation similarity measure called ‘AnnSim’ that measures the relatedness between two entities based on the similarity of their annotations. We model AnnSim as a 1–1 maximum weight bipartite match and exploit properties of existing solvers to provide an efficient solution. We empirically study the performance of AnnSim on real-world datasets of drugs and disease associations from clinical trials and relationships between drugs and (genomic) targets. Using baselines that include a variety of measures, we identify where AnnSim can provide a deeper understanding of the semantics underlying the relatedness of a pair of entities or where it could lead to predicting new links or identifying potential novel patterns. Although AnnSim does not exploit knowledge or properties of a particular domain, its performance compares well with a variety of state-of-the-art domain-specific measures. Database URL: http://www.yeastgenome.org/ PMID:25725057

  19. Determining similarity of scientific entities in annotation datasets.

    PubMed

    Palma, Guillermo; Vidal, Maria-Esther; Haag, Eric; Raschid, Louiqa; Thor, Andreas

    2015-01-01

    Linked Open Data initiatives have made available a diversity of scientific collections where scientists have annotated entities in the datasets with controlled vocabulary terms from ontologies. Annotations encode scientific knowledge, which is captured in annotation datasets. Determining relatedness between annotated entities becomes a building block for pattern mining, e.g. identifying drug-drug relationships may depend on the similarity of the targets that interact with each drug. A diversity of similarity measures has been proposed in the literature to compute relatedness between a pair of entities. Each measure exploits some knowledge including the name, function, relationships with other entities, taxonomic neighborhood and semantic knowledge. We propose a novel general-purpose annotation similarity measure called 'AnnSim' that measures the relatedness between two entities based on the similarity of their annotations. We model AnnSim as a 1-1 maximum weight bipartite match and exploit properties of existing solvers to provide an efficient solution. We empirically study the performance of AnnSim on real-world datasets of drugs and disease associations from clinical trials and relationships between drugs and (genomic) targets. Using baselines that include a variety of measures, we identify where AnnSim can provide a deeper understanding of the semantics underlying the relatedness of a pair of entities or where it could lead to predicting new links or identifying potential novel patterns. Although AnnSim does not exploit knowledge or properties of a particular domain, its performance compares well with a variety of state-of-the-art domain-specific measures. Database URL: http://www.yeastgenome.org/ PMID:25725057

  20. HPIDB 2.0: a curated database for host-pathogen interactions.

    PubMed

    Ammari, Mais G; Gresham, Cathy R; McCarthy, Fiona M; Nanduri, Bindu

    2016-01-01

    Identification and analysis of host-pathogen interactions (HPI) is essential to study infectious diseases. However, HPI data are sparse in existing molecular interaction databases, especially for agricultural host-pathogen systems. Therefore, resources that annotate, predict and display the HPI that underpin infectious diseases are critical for developing novel intervention strategies. HPIDB 2.0 (http://www.agbase.msstate.edu/hpi/main.html) is a resource for HPI data, and contains 45, 238 manually curated entries in the current release. Since the first description of the database in 2010, multiple enhancements to HPIDB data and interface services were made that are described here. Notably, HPIDB 2.0 now provides targeted biocuration of molecular interaction data. As a member of the International Molecular Exchange consortium, annotations provided by HPIDB 2.0 curators meet community standards to provide detailed contextual experimental information and facilitate data sharing. Moreover, HPIDB 2.0 provides access to rapidly available community annotations that capture minimum molecular interaction information to address immediate researcher needs for HPI network analysis. In addition to curation, HPIDB 2.0 integrates HPI from existing external sources and contains tools to infer additional HPI where annotated data are scarce. Compared to other interaction databases, our data collection approach ensures HPIDB 2.0 users access the most comprehensive HPI data from a wide range of pathogens and their hosts (594 pathogen and 70 host species, as of February 2016). Improvements also include enhanced search capacity, addition of Gene Ontology functional information, and implementation of network visualization. The changes made to HPIDB 2.0 content and interface ensure that users, especially agricultural researchers, are able to easily access and analyse high quality, comprehensive HPI data. All HPIDB 2.0 data are updated regularly, are publically available for direct

  1. HPIDB 2.0: a curated database for host–pathogen interactions

    PubMed Central

    Ammari, Mais G.; Gresham, Cathy R.; McCarthy, Fiona M.; Nanduri, Bindu

    2016-01-01

    Identification and analysis of host–pathogen interactions (HPI) is essential to study infectious diseases. However, HPI data are sparse in existing molecular interaction databases, especially for agricultural host–pathogen systems. Therefore, resources that annotate, predict and display the HPI that underpin infectious diseases are critical for developing novel intervention strategies. HPIDB 2.0 (http://www.agbase.msstate.edu/hpi/main.html) is a resource for HPI data, and contains 45, 238 manually curated entries in the current release. Since the first description of the database in 2010, multiple enhancements to HPIDB data and interface services were made that are described here. Notably, HPIDB 2.0 now provides targeted biocuration of molecular interaction data. As a member of the International Molecular Exchange consortium, annotations provided by HPIDB 2.0 curators meet community standards to provide detailed contextual experimental information and facilitate data sharing. Moreover, HPIDB 2.0 provides access to rapidly available community annotations that capture minimum molecular interaction information to address immediate researcher needs for HPI network analysis. In addition to curation, HPIDB 2.0 integrates HPI from existing external sources and contains tools to infer additional HPI where annotated data are scarce. Compared to other interaction databases, our data collection approach ensures HPIDB 2.0 users access the most comprehensive HPI data from a wide range of pathogens and their hosts (594 pathogen and 70 host species, as of February 2016). Improvements also include enhanced search capacity, addition of Gene Ontology functional information, and implementation of network visualization. The changes made to HPIDB 2.0 content and interface ensure that users, especially agricultural researchers, are able to easily access and analyse high quality, comprehensive HPI data. All HPIDB 2.0 data are updated regularly, are publically available for direct

  2. Compensating for literature annotation bias when predicting novel drug-disease relationships through Medical Subject Heading Over-representation Profile (MeSHOP) similarity

    PubMed Central

    2013-01-01

    Background Using annotations to the articles in MEDLINE®/PubMed®, over six thousand chemical compounds with pharmacological actions have been tracked since 1996. Medical Subject Heading Over-representation Profiles (MeSHOPs) quantitatively leverage the literature associated with biological entities such as diseases or drugs, providing the opportunity to reposition known compounds towards novel disease applications. Methods A MeSHOP is constructed by counting the number of times each medical subject term is assigned to an entity-related research publication in the MEDLINE database and calculating the significance of the count by comparing against the count of the term in a background set of publications. Based on the expectation that drugs suitable for treatment of a disease (or disease symptom) will have similar annotation properties to the disease, we successfully predict drug-disease associations by comparing MeSHOPs of diseases and drugs. Results The MeSHOP comparison approach delivers an 11% improvement over bibliometric baselines. However, novel drug-disease associations are observed to be biased towards drugs and diseases with more publications. To account for the annotation biases, a correction procedure is introduced and evaluated. Conclusions By explicitly accounting for the annotation bias, unexpectedly similar drug-disease pairs are highlighted as candidates for drug repositioning research. MeSHOPs are shown to provide a literature-supported perspective for discovery of new links between drugs and diseases based on pre-existing knowledge. PMID:23819887

  3. VariOtator, a Software Tool for Variation Annotation with the Variation Ontology.

    PubMed

    Schaafsma, Gerard C P; Vihinen, Mauno

    2016-04-01

    The Variation Ontology (VariO) is used for describing and annotating types, effects, consequences, and mechanisms of variations. To facilitate easy and consistent annotations, the online application VariOtator was developed. For variation type annotations, VariOtator is fully automated, accepting variant descriptions in Human Genome Variation Society (HGVS) format, and generating VariO terms, either with or without full lineage, that is, all parent terms. When a coding DNA variant description with a reference sequence is provided, VariOtator checks the description first with Mutalyzer and then generates the predicted RNA and protein descriptions with their respective VariO annotations. For the other sublevels, function, structure, and property, annotations cannot be automated, and VariOtator generates annotation based on provided details. For VariO terms relating to structure and property, one can use attribute terms as modifiers and evidence code terms for annotating experimental evidence. There is an online batch version, and stand-alone batch versions to be used with a Leiden Open Variation Database (LOVD) download file. A SOAP Web service allows client programs to access VariOtator programmatically. Thus, systematic variation effect and type annotations can be efficiently generated to allow easy use and integration of variations and their consequences. PMID:26773573

  4. Preserving sequence annotations across reference sequences

    PubMed Central

    2014-01-01

    Background Matching and comparing sequence annotations of different reference sequences is vital to genomics research, yet many annotation formats do not specify the reference sequence types or versions used. This makes the integration of annotations from different sources difficult and error prone. Results As part of our effort to create linked data for interoperable sequence annotations, we present an RDF data model for sequence annotation using the ontological framework established by the OBO Foundry ontologies and the Basic Formal Ontology (BFO). We defined reference sequences as the common domain of integration for sequence annotations, and identified three semantic relationships between sequence annotations. In doing so, we created the Reference Sequence Annotation to compensate for gaps in the SO and in its mapping to BFO, particularly for annotations that refer to versions of consensus reference sequences. Moreover, we present three integration models for sequence annotations using different reference assemblies. Conclusions We demonstrated a working example of a sequence annotation instance, and how this instance can be linked to other annotations on different reference sequences. Sequence annotations in this format are semantically rich and can be integrated easily with different assemblies. We also identify other challenges of modeling reference sequences with the BFO. PMID:25093075

  5. Improvement of the Cramer classification for oral exposure using the database TTC RepDose - A strategy description

    EPA Science Inventory

    The present report describes a strategy to refine the current Cramer classification of the TTC concept using a broad database (DB) termed TTC RepDose. Cramer classes 1-3 overlap to some extent, indicating a need for a better separation of structural classes likely to be toxic, mo...

  6. Nutrient database improvement project: Separable components and proximate composition of retail cuts from the beef loin and round

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Beef nutrition research has become increasingly important domestically and internationally for the beef industry and its consumers. The objective of this study was to analyze the nutrient composition of ten beef loin and round cuts to update the nutrient data in the USDA National Nutrient Database f...

  7. CTDB: An Integrated Chickpea Transcriptome Database for Functional and Applied Genomics.

    PubMed

    Verma, Mohit; Kumar, Vinay; Patel, Ravi K; Garg, Rohini; Jain, Mukesh

    2015-01-01

    Chickpea is an important grain legume used as a rich source of protein in human diet. The narrow genetic diversity and limited availability of genomic resources are the major constraints in implementing breeding strategies and biotechnological interventions for genetic enhancement of chickpea. We developed an integrated Chickpea Transcriptome Database (CTDB), which provides the comprehensive web interface for visualization and easy retrieval of transcriptome data in chickpea. The database features many tools for similarity search, functional annotation (putative function, PFAM domain and gene ontology) search and comparative gene expression analysis. The current release of CTDB (v2.0) hosts transcriptome datasets with high quality functional annotation from cultivated (desi and kabuli types) and wild chickpea. A catalog of transcription factor families and their expression profiles in chickpea are available in the database. The gene expression data have been integrated to study the expression profiles of chickpea transcripts in major tissues/organs and various stages of flower development. The utilities, such as similarity search, ortholog identification and comparative gene expression have also been implemented in the database to facilitate comparative genomic studies among different legumes and Arabidopsis. Furthermore, the CTDB represents a resource for the discovery of functional molecular markers (microsatellites and single nucleotide polymorphisms) between different chickpea types. We anticipate that integrated information content of this database will accelerate the functional and applied genomic research for improvement of chickpea. The CTDB web service is freely available at http://nipgr.res.in/ctdb.html. PMID:26322998

  8. CTDB: An Integrated Chickpea Transcriptome Database for Functional and Applied Genomics.

    PubMed

    Verma, Mohit; Kumar, Vinay; Patel, Ravi K; Garg, Rohini; Jain, Mukesh

    2015-01-01

    Chickpea is an important grain legume used as a rich source of protein in human diet. The narrow genetic diversity and limited availability of genomic resources are the major constraints in implementing breeding strategies and biotechnological interventions for genetic enhancement of chickpea. We developed an integrated Chickpea Transcriptome Database (CTDB), which provides the comprehensive web interface for visualization and easy retrieval of transcriptome data in chickpea. The database features many tools for similarity search, functional annotation (putative function, PFAM domain and gene ontology) search and comparative gene expression analysis. The current release of CTDB (v2.0) hosts transcriptome datasets with high quality functional annotation from cultivated (desi and kabuli types) and wild chickpea. A catalog of transcription factor families and their expression profiles in chickpea are available in the database. The gene expression data have been integrated to study the expression profiles of chickpea transcripts in major tissues/organs and various stages of flower development. The utilities, such as similarity search, ortholog identification and comparative gene expression have also been implemented in the database to facilitate comparative genomic studies among different legumes and Arabidopsis. Furthermore, the CTDB represents a resource for the discovery of functional molecular markers (microsatellites and single nucleotide polymorphisms) between different chickpea types. We anticipate that integrated information content of this database will accelerate the functional and applied genomic research for improvement of chickpea. The CTDB web service is freely available at http://nipgr.res.in/ctdb.html.

  9. Infant Feeding: An Annotated Bibliography.

    ERIC Educational Resources Information Center

    Crowhurst, Christine Marie, Comp.; Kumer, Bonnie Lee, Comp.

    Intended for parents, health professionals and allied health workers, and others involved in caring for infants and young children, this annotated bibliography brings together in one selective listing a review of over 700 current publications related to infant feeding. Reflecting current knowledge in infant feeding, the bibliography has as its…

  10. English Language Learners: Annotated Bibliography

    ERIC Educational Resources Information Center

    Hector-Mason, Anestine; Bardack, Sarah

    2010-01-01

    This annotated bibliography represents a first step toward compiling a comprehensive overview of current research on issues related to English language learners (ELLs). It is intended to be a resource for researchers, policymakers, administrators, and educators who are engaged in efforts to bridge the divide between research, policy, and practice…

  11. Appalachian Women. An Annotated Bibliography.

    ERIC Educational Resources Information Center

    Hamm, Mary Margo

    This bibliography compiles annotations of 178 books, journal articles, ERIC documents, and dissertations on Appalachian women and their social, cultural, and economic environment. Entries were published 1966-93 and are listed in the following categories: (1) authors and literary criticism; (2) bibliographies and resource guides; (3) economics,…

  12. Radiocarbon Dating: An Annotated Bibliography.

    ERIC Educational Resources Information Center

    Fortine, Suellen

    This selective annotated bibliography covers various sources of information on the radiocarbon dating method, including journal articles, conference proceedings, and reports, reflecting the most important and useful sources of the last 25 years. The bibliography is divided into five parts--general background on radiocarbon, radiocarbon dating,…

  13. Hispanic Heritage. An Annotated Bibliography.

    ERIC Educational Resources Information Center

    Denver Univ., CO. School of Education.

    This annotated bibliography of a wide range of materials for the social studies teacher is concerned with the Hispano heritage. The sections are introduced by a brief description. The sections are: 1) general materials, 2) the land and the people, 3) the European background, 4) Spain's colonial system, 5) the Spanish borderlands, 6) the Anglo…

  14. Rural Education: An Annotated Bibliography.

    ERIC Educational Resources Information Center

    Massey, Sara

    The 120-item annotated bibliography was compiled to facilitate the development of a recently approved course entitled "Topics in Rural Education" at the University of Maine at Machias. Although the dates range from 1964 to 1982, most of the materials were prepared in the 1970s and 1980s. The interrelatedness of the issues makes categorization…

  15. Workforce Reductions. An Annotated Bibliography.

    ERIC Educational Resources Information Center

    Hickok, Thomas A.; Hickok, Thomas A.

    This report, which is based on a review of practitioner-oriented sources and scholarly journals, uses a three-part framework to organize annotated bibliographies that, together, list a total of 104 sources that provide the following three perspectives on work force reduction issues: organizational, organizational-individual relationship, and…

  16. Vietnamese Amerasians: An Annotated Bibliography.

    ERIC Educational Resources Information Center

    Johnson, Mark C.; And Others

    This annotated bibliography on Vietnamese Amerasians includes primary and secondary sources as well as reviews of three documentary films. Sources were selected in order to provide an overview of the historical and political context of Amerasian resettlement and a review of the scant available research on coping and adaptation with this…

  17. Instructional Materials Centers; Annotated Bibliography.

    ERIC Educational Resources Information Center

    Poli, Rosario, Comp.

    An annotated bibliography lists 74 articles and reports on instructional materials centers (IMC) which appeared from 1967-70. The articles deal with such topics as the purposes of an IMC, guidelines for setting up an IMC, and the relationship of an IMC to technology. Most articles deal with use of an IMC on an elementary or secondary level, but…

  18. Nikos Kazantzakis: An Annotated Bibliography.

    ERIC Educational Resources Information Center

    Qiu, Kui

    This research paper consists of an annotated bibliography about Nikos Kazantzakis, one of the major modern Greek writers and author of "The Last Temptation of Christ,""Zorba the Greek," and many other works. Because of Kazantzakis' position in world literature there are many critical works about him; however, bibliographical control of these works…

  19. An Annotated Bibliography for Art.

    ERIC Educational Resources Information Center

    Minnesota State Dept. of Education, St. Paul. Div. of Instruction.

    The annotated bibliography presents approximately 450 references about art for elementary, secondary, and professional levels. It is presented in three sections. Section one identifies 19 resources about art from a professional or teaching perspective. Included are books explaining how to teach various techniques to students of beginning or…

  20. Annotated Bibliography on Humanistic Education

    ERIC Educational Resources Information Center

    Ganung, Cynthia

    1975-01-01

    Part I of this annotated bibliography deals with books and articles on such topics as achievement motivation, process education, transactional analysis, discipline without punishment, role-playing, interpersonal skills, self-acceptance, moral education, self-awareness, values clarification, and non-verbal communication. Part II focuses on…

  1. MSDAC Resource Library Annotated Bibliography.

    ERIC Educational Resources Information Center

    Watson, Cristel; And Others

    This annotated bibliography lists books, films, filmstrips, recordings, and booklets on sex equity. Entries are arranged according to the following topics: career resources, curriculum resources, management, sex equity, sex roles, women's studies, student activities, and sex-fair fiction. Included in each entry are name of author, editor or…

  2. Multicultural Education. An Annotated Bibliography.

    ERIC Educational Resources Information Center

    Narang, H. L.

    This annotated bibliography contains references to books, journal articles, ERIC documents, doctoral dissertations, and audio-visual materials on the subject of multicultural education. Topics include integrating multiculturalism in school subjects, prejudice and discrimination, intercultural communication, ethnic identity and ethnic bias.…

  3. Extension to distributed annotation system: Summary and summaryplot commands.

    PubMed

    Chrysostomou, Charalambos; Brookes, Anthony J

    2015-08-01

    In recent years, the development of high-throughput sequencing technologies provided an effective way to generate data from entire genomes and test variants from thousands of individuals. The information acquired from analysing the data generated from high-throughput sequencing technologies provided useful insights into applications like whole-exome sequencing and targeted sequencing to discover the genetic cause of complex diseases and drug responses. The Distributed Annotation System (DAS) is one of the proposed solution developed to share and unify biological data from multiple local and remote DAS annotation servers. The researchers can use DAS to request data from federated or centralised databases and integrate them into a unified view. Furthermore, with the use of Reference DAS servers, structural and sequence data can be used to accompany annotation data, for the pursue of new knowledge for a particular feature or region. In this paper, two additional commands, summary and summary-plot commands, to the existing DAS protocol are proposed and implemented. The proposed commands were created in order to give the users the capabilities to request a summary of features for a particular region of interest. The summary command was created in order to extend the capabilities of the current DAS protocol, while the summaryplot command was created to provide a more user-friendly alternative to standard XML DAS responses. Finally, three examples are presented based on the GENCODE annotation data. PMID:26738065

  4. Supervised learning of semantic classes for image annotation and retrieval.

    PubMed

    Carneiro, Gustavo; Chan, Antoni B; Moreno, Pedro J; Vasconcelos, Nuno

    2007-03-01

    A probabilistic formulation for semantic image annotation and retrieval is proposed. Annotation and retrieval are posed as classification problems where each class is defined as the group of database images labeled with a common semantic label. It is shown that, by establishing this one-to-one correspondence between semantic labels and semantic classes, a minimum probability of error annotation and retrieval are feasible with algorithms that are 1) conceptually simple, 2) computationally efficient, and 3) do not require prior semantic segmentation of training images. In particular, images are represented as bags of localized feature vectors, a mixture density estimated for each image, and the mixtures associated with all images annotated with a common semantic label pooled into a density estimate for the corresponding semantic class. This pooling is justified by a multiple instance learning argument and performed efficiently with a hierarchical extension of expectation-maximization. The benefits of the supervised formulation over the more complex, and currently popular, joint modeling of semantic label and visual feature distributions are illustrated through theoretical arguments and extensive experiments. The supervised formulation is shown to achieve higher accuracy than various previously published methods at a fraction of their computational cost. Finally, the proposed method is shown to be fairly robust to parameter tuning.

  5. Variobox: automatic detection and annotation of human genetic variants.

    PubMed

    Gaspar, Paulo; Lopes, Pedro; Oliveira, Jorge; Santos, Rosário; Dalgleish, Raymond; Oliveira, José Luís

    2014-02-01

    Triggered by the sequencing of the human genome, personalized medicine has been one of the fastest growing research areas in the last decade. Multiple software and hardware technologies have been developed by several projects, culminating in the exponential growth of genetic data. Considering the technological developments in this field, it is now fairly easy and inexpensive to obtain genetic profiles for unique individuals, such as those performed by several genetic analysis companies. The availability of computational tools that simplify genetic data analysis and the disclosure of biomedical evidences are of utmost importance. We present Variobox, a desktop tool to annotate, analyze, and compare human genes. Variobox obtains variant annotation data from WAVe, protein metadata annotations from Protein Data Bank, and sequences are obtained from Locus Reference Genomic or RefSeq databases. To explore the data, Variobox provides an advanced sequence visualization that enables agile navigation through genetic regions. DNA sequencing data can be compared with reference sequences retrieved from LRG or RefSeq records, identifying and automatically annotating new potential variants. These features and data, ranging from patient sequences to HGVS-compliant variant descriptions, are combined in an intuitive interface to analyze genes and variants. Variobox is a Java application, available at http://bioinformatics.ua.pt/variobox.

  6. Challenges for an enzymatic reaction kinetics database.

    PubMed

    Wittig, Ulrike; Rey, Maja; Kania, Renate; Bittkowski, Meik; Shi, Lei; Golebiewski, Martin; Weidemann, Andreas; Müller, Wolfgang; Rojas, Isabel

    2014-01-01

    The scientific literature contains a tremendous amount of kinetic data describing the dynamic behaviour of biochemical reactions over time. These data are needed for computational modelling to create models of biochemical reaction networks and to obtain a better understanding of the processes in living cells. To extract the knowledge from the literature, biocurators are required to understand a paper and interpret the data. For modellers, as well as experimentalists, this process is very time consuming because the information is distributed across the publication and, in most cases, is insufficiently structured and often described without standard terminology. In recent years, biological databases for different data types have been developed. The advantages of these databases lie in their unified structure, searchability and the potential for augmented analysis by software, which supports the modelling process. We have developed the SABIO-RK database for biochemical reaction kinetics. In the present review, we describe the challenges for database developers and curators, beginning with an analysis of relevant publications up to the export of database information in a standardized format. The aim of the present review is to draw the experimentalist's attention to the problem (from a data integration point of view) of incompletely and imprecisely written publications. We describe how to lower the barrier to curators and improve this situation. At the same time, we are aware that curating experimental data takes time. There is a community concerned with making the task of publishing data with the proper structure and annotation to ontologies much easier. In this respect, we highlight some useful initiatives and tools.

  7. MEGAnnotator: a user-friendly pipeline for microbial genomes assembly and annotation.

    PubMed

    Lugli, Gabriele Andrea; Milani, Christian; Mancabelli, Leonardo; van Sinderen, Douwe; Ventura, Marco

    2016-04-01

    Genome annotation is one of the key actions that must be undertaken in order to decipher the genetic blueprint of organisms. Thus, a correct and reliable annotation is essential in rendering genomic data valuable. Here, we describe a bioinformatics pipeline based on freely available software programs coordinated by a multithreaded script named MEGAnnotator (Multithreaded Enhanced prokaryotic Genome Annotator). This pipeline allows the generation of multiple annotated formats fulfilling the NCBI guidelines for assembled microbial genome submission, based on DNA shotgun sequencing reads, and minimizes manual intervention, while also reducing waiting times between software program executions and improving final quality of both assembly and annotation outputs. MEGAnnotator provides an efficient way to pre-arrange the assembly and annotation work required to process NGS genome sequence data. The script improves the final quality of microbial genome annotation by reducing ambiguous annotations. Moreover, the MEGAnnotator platform allows the user to perform a partial annotation of pre-assembled genomes and includes an option to accomplish metagenomic data set assemblies. MEGAnnotator platform will be useful for microbiologists interested in genome analyses of bacteria as well as those investigating the complexity of microbial communities that do not possess the necessary skills to prepare their own bioinformatics pipeline.

  8. Systems Theory and Communication. Annotated Bibliography.

    ERIC Educational Resources Information Center

    Covington, William G., Jr.

    This annotated bibliography presents annotations of 31 books and journal articles dealing with systems theory and its relation to organizational communication, marketing, information theory, and cybernetics. Materials were published between 1963 and 1992 and are listed alphabetically by author. (RS)

  9. Stackfile Database

    NASA Technical Reports Server (NTRS)

    deVarvalho, Robert; Desai, Shailen D.; Haines, Bruce J.; Kruizinga, Gerhard L.; Gilmer, Christopher

    2013-01-01

    This software provides storage retrieval and analysis functionality for managing satellite altimetry data. It improves the efficiency and analysis capabilities of existing database software with improved flexibility and documentation. It offers flexibility in the type of data that can be stored. There is efficient retrieval either across the spatial domain or the time domain. Built-in analysis tools are provided for frequently performed altimetry tasks. This software package is used for storing and manipulating satellite measurement data. It was developed with a focus on handling the requirements of repeat-track altimetry missions such as Topex and Jason. It was, however, designed to work with a wide variety of satellite measurement data [e.g., Gravity Recovery And Climate Experiment -- GRACE). The software consists of several command-line tools for importing, retrieving, and analyzing satellite measurement data.

  10. Genome-Wide Functional Annotation of Human Protein-Coding Splice Variants Using Multiple Instance Learning.

    PubMed

    Panwar, Bharat; Menon, Rajasree; Eksi, Ridvan; Li, Hong-Dong; Omenn, Gilbert S; Guan, Yuanfang

    2016-06-01

    The vast majority of human multiexon genes undergo alternative splicing and produce a variety of splice variant transcripts and proteins, which can perform different functions. These protein-coding splice variants (PCSVs) greatly increase the functional diversity of proteins. Most functional annotation algorithms have been developed at the gene level; the lack of isoform-level gold standards is an important intellectual limitation for currently available machine learning algorithms. The accumulation of a large amount of RNA-seq data in the public domain greatly increases our ability to examine the functional annotation of genes at isoform level. In the present study, we used a multiple instance learning (MIL)-based approach for predicting the function of PCSVs. We used transcript-level expression values and gene-level functional associations from the Gene Ontology database. A support vector machine (SVM)-based 5-fold cross-validation technique was applied. Comparatively, genes with multiple PCSVs performed better than single PCSV genes, and performance also improved when more examples were available to train the models. We demonstrated our predictions using literature evidence of ADAM15, LMNA/C, and DMXL2 genes. All predictions have been implemented in a web resource called "IsoFunc", which is freely available for the global scientific community through http://guanlab.ccmb.med.umich.edu/isofunc . PMID:27142340

  11. Video annotations of Mexican nature in a collaborative environment

    NASA Astrophysics Data System (ADS)

    Oropesa Morales, Lester Arturo; Montoya Obeso, Abraham; Hernández García, Rosaura; Cocolán Almeda, Sara Ivonne; García Vázquez, Mireya Saraí; Benois-Pineau, Jenny; Zamudio Fuentes, Luis Miguel; Martinez Nuño, Jesús A.; Ramírez Acosta, Alejandro Alvaro

    2015-09-01

    Multimedia content production and storage in repositories are now an increasingly widespread practice. Indexing concepts for search in multimedia libraries are very useful for users of the repositories. However the search tools of content-based retrieval and automatic video tagging, still do not have great consistency. Regardless of how these systems are implemented, it is of vital importance to possess lots of videos that have concepts tagged with ground truth (training and testing sets). This paper describes a novel methodology to make complex annotations on video resources through ELAN software. The concepts are annotated and related to Mexican nature in a High Level Features (HLF) from development set of TRECVID 2014 in a collaborative environment. Based on this set, each nature concept observed is tagged on each video shot using concepts of the TRECVid 2014 dataset. We also propose new concepts, -like tropical settings, urban scenes, actions, events, weather, places for name a few. We also propose specific concepts that best describe video content of Mexican culture. We have been careful to get the database tagged with concepts of nature and ground truth. It is evident that a collaborative environment is more suitable for annotation of concepts related to ground truth and nature. As a result a Mexican nature database was built. It also is the basis for testing and training sets to automatically classify new multimedia content of Mexican nature.

  12. Development and annotation of perennial Triticeae ESTs and SSR markers.

    PubMed

    Bushman, B Shaun; Larson, Steve R; Mott, Ivan W; Cliften, Paul F; Wang, Richard R-C; Chatterton, N Jerry; Hernandez, Alvaro G; Ali, Shahjahan; Kim, Ryan W; Thimmapuram, Jyothi; Gong, George; Liu, Lei; Mikel, Mark A

    2008-10-01

    Triticeae contains hundreds of species of both annual and perennial types. Although substantial genomic tools are available for annual Triticeae cereals such as wheat and barley, the perennial Triticeae lack sufficient genomic resources for genetic mapping or diversity research. To increase the amount of sequence information available in the perennial Triticeae, three expressed sequence tag (EST) libraries were developed and annotated for Pseudoroegneria spicata, a mixture of both Elymus wawawaiensis and E. lanceolatus, and a Leymus cinereus x L. triticoides interspecific hybrid. The ESTs were combined into unigene sets of 8 780 unigenes for P. spicata, 11 281 unigenes for Leymus, and 7 212 unigenes for Elymus. Unigenes were annotated based on putative orthology to genes from rice, wheat, barley, other Poaceae, Arabidopsis, and the non-redundant database of the NCBI. Simple sequence repeat (SSR) markers were developed, tested for amplification and polymorphism, and aligned to the rice genome. Leymus EST markers homologous to rice chromosome 2 genes were syntenous on Leymus homeologous groups 6a and 6b (previously 1b), demonstrating promise for in silico comparative mapping. All ESTs and SSR markers are available on an EST information management and annotation database (http://titan.biotec.uiuc.edu/triticeae/). PMID:18923529

  13. Use of Annotations for Component and Framework Interoperability

    NASA Astrophysics Data System (ADS)

    David, O.; Lloyd, W.; Carlson, J.; Leavesley, G. H.; Geter, F.

    2009-12-01

    The popular programming languages Java and C# provide annotations, a form of meta-data construct. Software frameworks for web integration, web services, database access, and unit testing now take advantage of annotations to reduce the complexity of APIs and the quantity of integration code between the application and framework infrastructure. Adopting annotation features in frameworks has been observed to lead to cleaner and leaner application code. The USDA Object Modeling System (OMS) version 3.0 fully embraces the annotation approach and additionally defines a meta-data standard for components and models. In version 3.0 framework/model integration previously accomplished using API calls is now achieved using descriptive annotations. This enables the framework to provide additional functionality non-invasively such as implicit multithreading, and auto-documenting capabilities while achieving a significant reduction in the size of the model source code. Using a non-invasive methodology leads to models and modeling components with only minimal dependencies on the modeling framework. Since models and modeling components are not directly bound to framework by the use of specific APIs and/or data types they can more easily be reused both within the framework as well as outside of it. To study the effectiveness of an annotation based framework approach with other modeling frameworks, a framework-invasiveness study was conducted to evaluate the effects of framework design on model code quality. A monthly water balance model was implemented across several modeling frameworks and several software metrics were collected. The metrics selected were measures of non-invasive design methods for modeling frameworks from a software engineering perspective. It appears that the use of annotations positively impacts several software quality measures. In a next step, the PRMS model was implemented in OMS 3.0 and is currently being implemented for water supply forecasting in the

  14. ANNOTATED BIBLIOGRAPHY ON CREATIVITY AND GIFTEDNESS.

    ERIC Educational Resources Information Center

    GOWAN, JOHN CURTIS

    THIS ANNOTATED BIBLIOGRAPHY REPRESENTS A SAMPLING OF PUBLISHED WRITING ON CREATIVITY AND GIFTED CHILDREN SINCE 1960. THE LIST WAS COMPILED FOR EDUCATIONAL RESEARCHERS. IN A FEW INSTANCES THE ANNOTATIONS HAVE BEEN MODIFIED OR ABRIDGED FROM THOSE FOUND IN "PSYCHOLOGICAL ABSTRACTS" OR OTHER JOURNAL ABSTRACTS. SOME OF THE ANNOTATIONS HAVE PREVIOUSLY…

  15. Alcohol Education Materials; An Annotated Bibliography.

    ERIC Educational Resources Information Center

    Milgram, Gail Gleason

    This 873-item annotated bibliography cites books, pamphlets, leaflets, and other materials produced for education about alcohol from 1950 to May 1973. The major part of each annotation is a brief summary of the contents. The annotation also contains a statement of orientation or type of presentation and evaluative comments. Each item is classified…

  16. Annotation and Classification of Argumentative Writing Revisions

    ERIC Educational Resources Information Center

    Zhang, Fan; Litman, Diane

    2015-01-01

    This paper explores the annotation and classification of students' revision behaviors in argumentative writing. A sentence-level revision schema is proposed to capture why and how students make revisions. Based on the proposed schema, a small corpus of student essays and revisions was annotated. Studies show that manual annotation is reliable with…

  17. BioC viewer: a web-based tool for displaying and merging annotations in BioC

    PubMed Central

    Shin, Soo-Yong; Kim, Sun; Wilbur, W. John; Kwon, Dongseop

    2016-01-01

    BioC is an XML-based format designed to provide interoperability for text mining tools and manual curation results. A challenge of BioC as a standard format is to align annotations from multiple systems. Ideally, this should not be a major problem if users follow guidelines given by BioC key files. Nevertheless, the misalignment between text and annotations happens quite often because different systems tend to use different software development environments, e.g. ASCII vs. Unicode. We first implemented the BioC Viewer to assist BioGRID curators as a part of the BioCreative V BioC track (Collaborative Biocurator Assistant Task). For the BioC track, the BioC Viewer helped curate protein-protein interaction and genetic interaction pairs appearing in full-text articles. Here, we describe the BioC Viewer itself as well as improvements made to the BioC Viewer since the BioCreative V Workshop to address the misalignment issue of BioC annotations. While uploading BioC files, a BioC merge process is offered when there are files from the same full-text article. If there is a mismatch between an annotated offset and text, the BioC Viewer adjusts the offset to correctly align with the text. The BioC Viewer has a user-friendly interface, where most operations can be performed within a few mouse clicks. The feedback from BioGRID curators has been positive for the web interface, particularly for its usability and learnability. Database URL: http://viewer.bioqrator.org PMID:27515823

  18. BioC viewer: a web-based tool for displaying and merging annotations in BioC.

    PubMed

    Shin, Soo-Yong; Kim, Sun; Wilbur, W John; Kwon, Dongseop

    2016-01-01

    BioC is an XML-based format designed to provide interoperability for text mining tools and manual curation results. A challenge of BioC as a standard format is to align annotations from multiple systems. Ideally, this should not be a major problem if users follow guidelines given by BioC key files. Nevertheless, the misalignment between text and annotations happens quite often because different systems tend to use different software development environments, e.g. ASCII vs. Unicode. We first implemented the BioC Viewer to assist BioGRID curators as a part of the BioCreative V BioC track (Collaborative Biocurator Assistant Task). For the BioC track, the BioC Viewer helped curate protein-protein interaction and genetic interaction pairs appearing in full-text articles. Here, we describe the BioC Viewer itself as well as improvements made to the BioC Viewer since the BioCreative V Workshop to address the misalignment issue of BioC annotations. While uploading BioC files, a BioC merge process is offered when there are files from the same full-text article. If there is a mismatch between an annotated offset and text, the BioC Viewer adjusts the offset to correctly align with the text. The BioC Viewer has a user-friendly interface, where most operations can be performed within a few mouse clicks. The feedback from BioGRID curators has been positive for the web interface, particularly for its usability and learnability.Database URL: http://viewer.bioqrator.org. PMID:27515823

  19. Enabling Ontology Based Semantic Queries in Biomedical Database Systems.

    PubMed

    Zheng, Shuai; Wang, Fusheng; Lu, James; Saltz, Joel

    2012-01-01

    While current biomedical ontology repositories offer primitive query capabilities, it is difficult or cumbersome to support ontology based semantic queries directly in semantically annotated biomedical databases. The problem may be largely attributed to the mismatch between the models of the ontologies and the databases, and the mismatch between the query interfaces of the two systems. To fully realize semantic query capabilities based on ontologies, we develop a system DBOntoLink to provide unified semantic query interfaces by extending database query languages. With DBOntoLink, semantic queries can be directly and naturally specified as extended functions of the database query languages without any programming needed. DBOntoLink is adaptable to different ontologies through customizations and supports major biomedical ontologies hosted at the NCBO BioPortal. We demonstrate the use of DBOntoLink in a real world biomedical database with semantically annotated medical image annotations. PMID:23404054

  20. The NRSub database: update 1997.

    PubMed

    Perrière, G; Moszer, I; Gojobori, T

    1997-01-01

    In the context of the international project aiming at sequencing the whole genome of Bacillus subtilis we have developed NRSub, a non-redundant database of sequences from this organism. Starting from the B.subtilis sequences available in the repository collections we have removed all encountered duplications, then we have added extra annotations to the sequences (e.g. accession numbers for the genes, locations on the genetic map, codon usage index). We have also added cross-references with EMBL/GenBank/DDBJ, MEDLINE, SWISS-PROT and ENZYME databases. NRSub is distributed through anonymous FTP as a text file in EMBL format and as an ACNUC database. It is also possible to access the database through two dedicated World Wide Web servers located in France (http://acnuc.univ-lyon1.fr/nrsub/nrsub.++ +html ) and in Japan (http://ddbjs4h.genes.nig.ac.jp/ ). PMID:9016504

  1. PFAAT version 2.0: A tool for editing, annotating, and analyzing multiple sequence alignments

    PubMed Central

    Caffrey, Daniel R; Dana, Paul H; Mathur, Vidhya; Ocano, Marco; Hong, Eun-Jong; Wang, Yaoyu E; Somaroo, Shyamal; Caffrey, Brian E; Potluri, Shobha; Huang, Enoch S

    2007-01-01

    Background By virtue of their shared ancestry, homologous sequences are similar in their structure and function. Consequently, multiple sequence alignments are routinely used to identify trends that relate to function. This type of analysis is particularly productive when it is combined with structural and phylogenetic analysis. Results Here we describe the release of PFAAT version 2.0, a tool for editing, analyzing, and annotating multiple sequence alignments. Support for multiple annotations is a key component of this release as it provides a framework for most of the new functionalities. The sequence annotations are accessible from the alignment and tree, where they are typically used to label sequences or hyperlink them to related databases. Sequence annotations can be created manually or extracted automatically from UniProt entries. Once a multiple sequence alignment is populated with sequence annotations, sequences can be easily selected and sorted through a sophisticated search dialog. The selected sequences can be further analyzed using statistical methods that explicitly model relationships between the sequence annotations and residue properties. Residue annotations are accessible from the alignment viewer and are typically used to designate binding sites or properties for a particular residue. Residue annotations are also searchable, and allow one to quickly select alignment columns for further sequence analysis, e.g. computing percent identities. Other features include: novel algorithms to compute sequence conservation, mapping conservation scores to a 3D structure in Jmol, displaying secondary structure elements, and sorting sequences by residue composition. Conclusion PFAAT provides a framework whereby end-users can specify knowledge for a protein family in the form of annotation. The annotations can be combined with sophisticated analysis to test hypothesis that relate to sequence, structure and function. PMID:17931421

  2. DBGC: A Database of Human Gastric Cancer.

    PubMed

    Wang, Chao; Zhang, Jun; Cai, Mingdeng; Zhu, Zhenggang; Gu, Wenjie; Yu, Yingyan; Zhang, Xiaoyan

    2015-01-01

    The Database of Human Gastric Cancer (DBGC) is a comprehensive database that integrates various human gastric cancer-related data resources. Human gastric cancer-related transcriptomics projects, proteomics projects, mutations, biomarkers and drug-sensitive genes from different sources were collected and unified in this database. Moreover, epidemiological statistics of gastric cancer patients in China and clinicopathological information annotated with gastric cancer cases were also integrated into the DBGC. We believe that this database will greatly facilitate research regarding human gastric cancer in many fields. DBGC is freely available at http://bminfor.tongji.edu.cn/dbgc/index.do. PMID:26566288

  3. DBGC: A Database of Human Gastric Cancer.

    PubMed

    Wang, Chao; Zhang, Jun; Cai, Mingdeng; Zhu, Zhenggang; Gu, Wenjie; Yu, Yingyan; Zhang, Xiaoyan

    2015-01-01

    The Database of Human Gastric Cancer (DBGC) is a comprehensive database that integrates various human gastric cancer-related data resources. Human gastric cancer-related transcriptomics projects, proteomics projects, mutations, biomarkers and drug-sensitive genes from different sources were collected and unified in this database. Moreover, epidemiological statistics of gastric cancer patients in China and clinicopathological information annotated with gastric cancer cases were also integrated into the DBGC. We believe that this database will greatly facilitate research regarding human gastric cancer in many fields. DBGC is freely available at http://bminfor.tongji.edu.cn/dbgc/index.do.

  4. Effects of Teaching Strategies in Annotated Bibliography Writing

    ERIC Educational Resources Information Center

    Tan-de Ramos, Jennifer

    2015-01-01

    The study examines the effect of teaching strategies to improved writing of students in the tertiary level. Specifically, three teaching approaches--the use of modelling, grammar-based, and information element-focused--were tested on their effect on the writing of annotated bibliography in three research classes at a university in Manila.…

  5. Women and Girls in Vocational Education. Annotated Resource List.

    ERIC Educational Resources Information Center

    National Center for Research in Vocational Education, Berkeley, CA.

    This annotated but nonexhaustive resource list, describing 21 publications and 23 organizations, supports efforts funded through the Carl D. Perkins Vocational and Applied Technology Education Act of 1990 to improve the academic and economic outcomes of women and girls in vocational education. The listings are grouped under the following topics:…

  6. An Assessment of Reliability of Dialogue-Annotation Instructions.

    ERIC Educational Resources Information Center

    Mann, William C.; And Others

    This report is part of ongoing research engaged in transforming knowledge of how human communication works into improvements in man-machine communication of existing and planned computer systems. The methodology includes having a trained "Observer" annotate transcripts of human communication in a prescribed manner. One of the issues, therefore, in…

  7. A Multi-Disciplinary Annotated Bibliography on Graduate Teaching Assistants.

    ERIC Educational Resources Information Center

    Worthen, Thomas Kenne

    This bibliography annotates 68 articles on the graduate teaching assistant in the areas of (1) training, improvement, and development; (2) college internship programs; (3) support; (4) effectiveness; (5) evaluation; and (6) job satisfaction. The bibliography covers the disciplines of biology, teacher education, foreign languages, communications,…

  8. Automatic annotation of organellar genomes with DOGMA

    SciTech Connect

    Wyman, Stacia; Jansen, Robert K.; Boore, Jeffrey L.

    2004-06-01

    Dual Organellar GenoMe Annotator (DOGMA) automates the annotation of extra-nuclear organellar (chloroplast and animal mitochondrial) genomes. It is a web-based package that allows the use of comparative BLAST searches to identify and annotate genes in a genome. DOGMA presents a list of putative genes to the user in a graphical format for viewing and editing. Annotations are stored on our password-protected server. Complete annotations can be extracted for direct submission to GenBank. Furthermore, intergenic regions of specified length can be extracted, as well the nucleotide sequences and amino acid sequences of the genes.

  9. IMG ER: A System for Microbial Genome Annotation Expert Review and Curation

    SciTech Connect

    Markowitz, Victor M.; Mavromatis, Konstantinos; Ivanova, Natalia N.; Chen, I-Min A.; Chu, Ken; Kyrpides, Nikos C.

    2009-05-25

    A rapidly increasing number of microbial genomes are sequenced by organizations worldwide and are eventually included into various public genome data resources. The quality of the annotations depends largely on the original dataset providers, with erroneous or incomplete annotations often carried over into the public resources and difficult to correct. We have developed an Expert Review (ER) version of the Integrated Microbial Genomes (IMG) system, with the goal of supporting systematic and efficient revision of microbial genome annotations. IMG ER provides tools for the review and curation of annotations of both new and publicly available microbial genomes within IMG's rich integrated genome framework. New genome datasets are included into IMG ER prior to their public release either with their native annotations or with annotations generated by IMG ER's annotation pipeline. IMG ER tools allow addressing annotation problems detected with IMG's comparative analysis tools, such as genes missed by gene prediction pipelines or genes without an associated function. Over the past year, IMG ER was used for improving the annotations of about 150 microbial genomes.

  10. Design and Evaluation of Data Annotation Workflows for CAVE-like Virtual Environments.

    PubMed

    Pick, Sebastian; Weyers, Benjamin; Hentschel, Bernd; Kuhlen, Torsten W

    2016-04-01

    Data annotation finds increasing use in Virtual Reality applications with the goal to support the data analysis process, such as architectural reviews. In this context, a variety of different annotation systems for application to immersive virtual environments have been presented. While many interesting interaction designs for the data annotation workflow have emerged from them, important details and evaluations are often omitted. In particular, we observe that the process of handling metadata to interactively create and manage complex annotations is often not covered in detail. In this paper, we strive to improve this situation by focusing on the design of data annotation workflows and their evaluation. We propose a workflow design that facilitates the most important annotation operations, i.e., annotation creation, review, and modification. Our workflow design is easily extensible in terms of supported annotation and metadata types as well as interaction techniques, which makes it suitable for a variety of application scenarios. To evaluate it, we have conducted a user study in a CAVE-like virtual environment in which we compared our design to two alternatives in terms of a realistic annotation creation task. Our design obtained good results in terms of task performance and user experience.

  11. Oncotator: cancer variant annotation tool.

    PubMed

    Ramos, Alex H; Lichtenstein, Lee; Gupta, Manaswi; Lawrence, Michael S; Pugh, Trevor J; Saksena, Gordon; Meyerson, Matthew; Getz, Gad

    2015-04-01

    Oncotator is a tool for annotating genomic point mutations and short nucleotide insertions/deletions (indels) with variant- and gene-centric information relevant to cancer researchers. This information is drawn from 14 different publicly available resources that have been pooled and indexed, and we provide an extensible framework to add additional data sources. Annotations linked to variants range from basic information, such as gene names and functional classification (e.g. missense), to cancer-specific data from resources such as the Catalogue of Somatic Mutations in Cancer (COSMIC), the Cancer Gene Census, and The Cancer Genome Atlas (TCGA). For local use, Oncotator is freely available as a python module hosted on Github (https://github.com/broadinstitute/oncotator). Furthermore, Oncotator is also available as a web service and web application at http://www.broadinstitute.org/oncotator/.

  12. VCF-Miner: GUI-based application for mining variants and annotations stored in VCF files.

    PubMed

    Hart, Steven N; Duffy, Patrick; Quest, Daniel J; Hossain, Asif; Meiners, Mike A; Kocher, Jean-Pierre

    2016-03-01

    Next-generation sequencing platforms are widely used to discover variants associated with disease. The processing of sequencing data involves read alignment, variant calling, variant annotation and variant filtering. The standard file format to hold variant calls is the variant call format (VCF) file. According to the format specifications, any arbitrary annotation can be added to the VCF file for downstream processing. However, most downstream analysis programs disregard annotations already present in the VCF and re-annotate variants using the annotation provided by that particular program. This precludes investigators who have collected information on variants from literature or other sources from including these annotations in the filtering and mining of variants. We have developed VCF-Miner, a graphical user interface-based stand-alone tool, to mine variants and annotation stored in the VCF. Powered by a MongoDB database engine, VCF-Miner enables the stepwise trimming of non-relevant variants. The grouping feature implemented in VCF-Miner can be used to identify somatic variants by contrasting variants in tumor and in normal samples or to identify recessive/dominant variants in family studies. It is not limited to human data, but can also be extended to include non-diploid organisms. It also supports copy number or any other variant type supported by the VCF specification. VCF-Miner can be used on a personal computer or large institutional servers and is freely available for download from http://bioinformaticstools.mayo.edu/research/vcf-miner/. PMID:26210358

  13. VCF-Miner: GUI-based application for mining variants and annotations stored in VCF files

    PubMed Central

    Hart, Steven N.; Duffy, Patrick; Quest, Daniel J.; Hossain, Asif; Meiners, Mike A

    2016-01-01

    Next-generation sequencing platforms are widely used to discover variants associated with disease. The processing of sequencing data involves read alignment, variant calling, variant annotation and variant filtering. The standard file format to hold variant calls is the variant call format (VCF) file. According to the format specifications, any arbitrary annotation can be added to the VCF file for downstream processing. However, most downstream analysis programs disregard annotations already present in the VCF and re-annotate variants using the annotation provided by that particular program. This precludes investigators who have collected information on variants from literature or other sources from including these annotations in the filtering and mining of variants. We have developed VCF-Miner, a graphical user interface-based stand-alone tool, to mine variants and annotation stored in the VCF. Powered by a MongoDB database engine, VCF-Miner enables the stepwise trimming of non-relevant variants. The grouping feature implemented in VCF-Miner can be used to identify somatic variants by contrasting variants in tumor and in normal samples or to identify recessive/dominant variants in family studies. It is not limited to human data, but can also be extended to include non-diploid organisms. It also supports copy number or any other variant type supported by the VCF specification. VCF-Miner can be used on a personal computer or large institutional servers and is freely available for download from http://bioinformaticstools.mayo.edu/research/vcf-miner/. PMID:26210358

  14. Rapid storage and retrieval of genomic intervals from a relational database system using nested containment lists.

    PubMed

    Wiley, Laura K; Sivley, R Michael; Bush, William S

    2013-01-01

    Efficient storage and retrieval of genomic annotations based on range intervals is necessary, given the amount of data produced by next-generation sequencing studies. The indexing strategies of relational database systems (such as MySQL) greatly inhibit their use in genomic annotation tasks. This has led to the development of stand-alone applications that are dependent on flat-file libraries. In this work, we introduce MyNCList, an implementation of the NCList data structure within a MySQL database. MyNCList enables the storage, update and rapid retrieval of genomic annotations from the convenience of a relational database system. Range-based annotations of 1 million variants are retrieved in under a minute, making this approach feasible for whole-genome annotation tasks. Database URL: https://github.com/bushlab/mynclist. PMID:23894185

  15. Rapid storage and retrieval of genomic intervals from a relational database system using nested containment lists.

    PubMed

    Wiley, Laura K; Sivley, R Michael; Bush, William S

    2013-01-01

    Efficient storage and retrieval of genomic annotations based on range intervals is necessary, given the amount of data produced by next-generation sequencing studies. The indexing strategies of relational database systems (such as MySQL) greatly inhibit their use in genomic annotation tasks. This has led to the development of stand-alone applications that are dependent on flat-file libraries. In this work, we introduce MyNCList, an implementation of the NCList data structure within a MySQL database. MyNCList enables the storage, update and rapid retrieval of genomic annotations from the convenience of a relational database system. Range-based annotations of 1 million variants are retrieved in under a minute, making this approach feasible for whole-genome annotation tasks. Database URL: https://github.com/bushlab/mynclist.

  16. Biofuel Database

    National Institute of Standards and Technology Data Gateway

    Biofuel Database (Web, free access)   This database brings together structural, biological, and thermodynamic data for enzymes that are either in current use or are being considered for use in the production of biofuels.

  17. The standard operating procedure of the DOE-JGI Metagenome Annotation Pipeline (MAP v.4).

    PubMed

    Huntemann, Marcel; Ivanova, Natalia N; Mavromatis, Konstantinos; Tripp, H James; Paez-Espino, David; Tennessen, Kristin; Palaniappan, Krishnaveni; Szeto, Ernest; Pillay, Manoj; Chen, I-Min A; Pati, Amrita; Nielsen, Torben; Markowitz, Victor M; Kyrpides, Nikos C

    2016-01-01

    The DOE-JGI Metagenome Annotation Pipeline (MAP v.4) performs structural and functional annotation for metagenomic sequences that are submitted to the Integrated Microbial Genomes with Microbiomes (IMG/M) system for comparative analysis. The pipeline runs on nucleotide sequences provided via the IMG submission site. Users must first define their analysis projects in GOLD and then submit the associated sequence datasets consisting of scaffolds/contigs with optional coverage information and/or unassembled reads in fasta and fastq file formats. The MAP processing consists of feature prediction including identification of protein-coding genes, non-coding RNAs and regulatory RNAs, as well as CRISPR elements. Structural annotation is followed by functional annotation including assignment of protein product names and connection to various protein family databases. PMID:26918089

  18. The Signal Recognition Particle Database (SRPDB).

    PubMed

    Larsen, N; Zwieb, C

    1996-01-01

    The Signal Recognition Particle Database (SRPDB) provides aligned SRP RNA and SRP protein sequences, annotated and phylogenetically ordered. The current release included 93 RNAs and 29 proteins representing SRP9, SRP14, SRP19, SRP21, SRP54, SRP68 and SRP72. The SRPDB can be downloaded and is accessible via the World Wide Web.

  19. Database Administrator

    ERIC Educational Resources Information Center

    Moore, Pam

    2010-01-01

    The Internet and electronic commerce (e-commerce) generate lots of data. Data must be stored, organized, and managed. Database administrators, or DBAs, work with database software to find ways to do this. They identify user needs, set up computer databases, and test systems. They ensure that systems perform as they should and add people to the…

  20. Algal Functional Annotation Tool from the DOE-UCLA Institute for Genomics and Proteomics

    DOE Data Explorer

    Lopez, David

    The Algal Functional Annotation Tool is a bioinformatics resource to visualize pathway maps, identify enriched biological terms, or convert gene identifiers to elucidate biological function in silico. These types of analysis have been catered to support lists of gene identifiers, such as those coming from transcriptome gene expression analysis. By analyzing the functional annotation of an interesting set of genes, common biological motifs may be elucidated and a first-pass analysis can point further research in the right direction. Currently, the following databases have been parsed, processed, and added to the tool: 1( Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathways Database, 2) MetaCyc Encyclopedia of Metabolic Pathways, 3) Panther Pathways Database, 4) Reactome Pathways Database, 5) Gene Ontology, 6) MapMan Ontology, 7) KOG (Eukaryotic Clusters of Orthologous Groups), 5)Pfam, 6) InterPro.

  1. "Good annotation practice" for chemical data in biology.

    PubMed

    Degtyarenko, Kirill; Ennis, Marcus; Garavelli, John S

    2007-01-01

    A structural diagram, in the form of a two-dimensional (2-D) sketch, remains the most effective portrait of a "small molecule" or chemical reaction. However, such structural diagrams, as for any other core data, cannot be used in speech (and should not be used in free text). "Good annotation practice" for biological databases is to use either consistent and widely recognised terminology or unique identifiers from a dedicated database to refer to the molecule of interest. Ideally, scientists should use terminology that is both pronounceable and meaningful. Thus, a viable solution for a bioinformatician is to use a definitive controlled vocabulary of biochemical compounds and reactions, which contains both systematic and common names. In addition, chemical ontologies provide a means for placing entities of interest into wider chemical, biological or medical contexts. We present some challenges and achievements in the standardisation of chemical language in biological databases, with emphasis on three aspects of annotation: 1. good drawing practice: how to draw unambiguous 2-D diagrams; 2. good naming practice: how to give most appropriate names; and 3. good ontology practice: how to link the entity of interest by defined logical relationships to other entities. PMID:17822390

  2. VHLdb: A database of von Hippel-Lindau protein interactors and mutations.

    PubMed

    Tabaro, Francesco; Minervini, Giovanni; Sundus, Faiza; Quaglia, Federica; Leonardi, Emanuela; Piovesan, Damiano; Tosatto, Silvio C E

    2016-01-01

    Mutations in von Hippel-Lindau tumor suppressor protein (pVHL) predispose to develop tumors affecting specific target organs, such as the retina, epididymis, adrenal glands, pancreas and kidneys. Currently, more than 400 pVHL interacting proteins are either described in the literature or predicted in public databases. This data is scattered among several different sources, slowing down the comprehension of pVHL's biological role. Here we present VHLdb, a novel database collecting available interaction and mutation data on pVHL to provide novel integrated annotations. In VHLdb, pVHL interactors are organized according to two annotation levels, manual and automatic. Mutation data are easily accessible and a novel visualization tool has been implemented. A user-friendly feedback function to improve database content through community-driven curation is also provided. VHLdb presently contains 478 interactors, of which 117 have been manually curated, and 1,074 mutations. This makes it the largest available database for pVHL-related information. VHLdb is available from URL: http://vhldb.bio.unipd.it/. PMID:27511743

  3. VHLdb: A database of von Hippel-Lindau protein interactors and mutations

    PubMed Central

    Tabaro, Francesco; Minervini, Giovanni; Sundus, Faiza; Quaglia, Federica; Leonardi, Emanuela; Piovesan, Damiano; Tosatto, Silvio C. E.

    2016-01-01

    Mutations in von Hippel-Lindau tumor suppressor protein (pVHL) predispose to develop tumors affecting specific target organs, such as the retina, epididymis, adrenal glands, pancreas and kidneys. Currently, more than 400 pVHL interacting proteins are either described in the literature or predicted in public databases. This data is scattered among several different sources, slowing down the comprehension of pVHL’s biological role. Here we present VHLdb, a novel database collecting available interaction and mutation data on pVHL to provide novel integrated annotations. In VHLdb, pVHL interactors are organized according to two annotation levels, manual and automatic. Mutation data are easily accessible and a novel visualization tool has been implemented. A user-friendly feedback function to improve database content through community-driven curation is also provided. VHLdb presently contains 478 interactors, of which 117 have been manually curated, and 1,074 mutations. This makes it the largest available database for pVHL-related information. VHLdb is available from URL: http://vhldb.bio.unipd.it/. PMID:27511743

  4. [Analysis of the Cochrane Review: Interventions for Improving Upper Limb Function after Stroke. Cochrane Database Syst Rev. 2014,11:CD010820].

    PubMed

    Sousa Nanji, Liliana; Torres Cardoso, André; Costa, João; Vaz-Carneiro, António

    2015-01-01

    Impairment of the upper limbs is quite frequent after stroke, making rehabilitation an essential step towards clinical recovery and patient empowerment. This review aimed to synthetize existing evidence regarding interventions for upper limb function improvement after Stroke and to assess which would bring some benefit. The Cochrane Database of Systematic Reviews, the Database of Reviews of Effects and PROSPERO databases were searched until June 2013 and 40 reviews have been included, covering 503 studies, 18 078 participants and 18 interventions, as well as different doses and settings of interventions. The main results were: 1- Information currently available is insufficient to assess effectiveness of each intervention and to enable comparison of interventions; 2- Transcranial direct current stimulation brings no benefit for outcomes of activities of daily living; 3- Moderate-quality evidence showed a beneficial effect of constraint-induced movement therapy, mental practice, mirror therapy, interventions for sensory impairment, virtual reality and repetitive task practice; 4- Unilateral arm training may be more effective than bilateral arm training; 5- Moderate-quality evidence showed a beneficial effect of robotics on measures of impairment and ADLs; 6- There is no evidence of benefit or harm for technics such as repetitive transcranial magnetic stimulation, music therapy, pharmacological interventions, electrical stimulation and other therapies. Currently available evidence is insufficient and of low quality, not supporting clear clinical decisions. High-quality studies are still needed. PMID:26667856

  5. The Biofuel Feedstock Genomics Resource: a web-based portal and database to enable functional genomics of plant biofuel feedstock species.

    PubMed

    Childs, Kevin L; Konganti, Kranti; Buell, C Robin

    2012-01-01

    Major feedstock sources for future biofuel production are likely to be high biomass producing plant species such as poplar, pine, switchgrass, sorghum and maize. One active area of research in these species is genome-enabled improvement of lignocellulosic biofuel feedstock quality and yield. To facilitate genomic-based investigations in these species, we developed the Biofuel Feedstock Genomic Resource (BFGR), a database and web-portal that provides high-quality, uniform and integrated functional annotation of gene and transcript assembly sequences from species of interest to lignocellulosic biofuel feedstock researchers. The BFGR includes sequence data from 54 species and permits researchers to view, analyze and obtain annotation at the gene, transcript, protein and genome level. Annotation of biochemical pathways permits the identification of key genes and transcripts central to the improvement of lignocellulosic properties in these species. The integrated nature of the BFGR in terms of annotation methods, orthologous/paralogous relationships and linkage to seven species with complete genome sequences allows comparative analyses for biofuel feedstock species with limited sequence resources. Database URL: http://bfgr.plantbiology.msu.edu.

  6. Lynx web services for annotations and systems analysis of multi-gene disorders.

    PubMed

    Sulakhe, Dinanath; Taylor, Andrew; Balasubramanian, Sandhya; Feng, Bo; Xie, Bingqing; Börnigen, Daniela; Dave, Utpal J; Foster, Ian T; Gilliam, T Conrad; Maltsev, Natalia

    2014-07-01

    Lynx is a web-based integrated systems biology platform that supports annotation and analysis of experimental data and generation of weighted hypotheses on molecular mechanisms contributing to human phenotypes and disorders of interest. Lynx has integrated multiple classes of biomedical data (genomic, proteomic, pathways, phenotypic, toxicogenomic, contextual and others) from various public databases as well as manually curated data from our group and collaborators (LynxKB). Lynx provides tools for gene list enrichment analysis using multiple functional annotations and network-based gene prioritization. Lynx provides access to the integrated database and the analytical tools via REST based Web Services (http://lynx.ci.uchicago.edu/webservices.html). This comprises data retrieval services for specific functional annotations, services to search across the complete LynxKB (powered by Lucene), and services to access the analytical tools built within the Lynx platform.

  7. Studying Oogenesis in a Non-model Organism Using Transcriptomics: Assembling, Annotating, and Analyzing Your Data.

    PubMed

    Carter, Jean-Michel; Gibbs, Melanie; Breuker, Casper J

    2016-01-01

    This chapter provides a guide to processing and analyzing RNA-Seq data in a non-model organism. This approach was implemented for studying oogenesis in the Speckled Wood Butterfly Pararge aegeria. We focus in particular on how to perform a more informative primary annotation of your non-model organism by implementing our multi-BLAST annotation strategy. We also provide a general guide to other essential steps in the next-generation sequencing analysis workflow. Before undertaking these methods, we recommend you familiarize yourself with command line usage and fundamental concepts of database handling. Most of the operations in the primary annotation pipeline can be performed in Galaxy (or equivalent standalone versions of the tools) and through the use of common database operations (e.g. to remove duplicates) but other equivalent programs and/or custom scripts can be implemented for further automation. PMID:27557578

  8. An editing environment for DNA sequence analysis and annotation

    SciTech Connect

    Uberbacher, E.C.; Xu, Y.; Shah, M.B.; Olman, V.; Parang, M.; Mural, R.

    1998-12-31

    This paper presents a computer system for analyzing and annotating large-scale genomic sequences. The core of the system is a multiple-gene structure identification program, which predicts the most probable gene structures based on the given evidence, including pattern recognition, EST and protein homology information. A graphics-based user interface provides an environment which allows the user to interactively control the evidence to be used in the gene identification process. To overcome the computational bottleneck in the database similarity search used in the gene identification process, the authors have developed an effective way to partition a database into a set of sub-databases of related sequences, and reduced the search problem on a large database to a signature identification problem and a search problem on a much smaller sub-database. This reduces the number of sequences to be searched from N to O({radical}N) on average, and hence greatly reduces the search time, where N is the number of sequences in the original database. The system provides the user with the ability to facilitate and modify the analysis and modeling in real time.

  9. BIOFILTER AS A FUNCTIONAL ANNOTATION PIPELINE FOR COMMON AND RARE COPY NUMBER BURDEN.

    PubMed

    Kim, Dokyoon; Lucas, Anastasia; Glessner, Joseph; Verma, Shefali S; Bradford, Yuki; Li, Ruowang; Frase, Alex T; Hakonarson, Hakon; Peissig, Peggy; Brilliant, Murray; Ritchie, Marylyn D

    2016-01-01

    Recent studies on copy number variation (CNV) have suggested that an increasing burden of CNVs is associated with susceptibility or resistance to disease. A large number of genes or genomic loci contribute to complex diseases such as autism. Thus, total genomic copy number burden, as an accumulation of copy number change, is a meaningful measure of genomic instability to identify the association between global genetic effects and phenotypes of interest. However, no systematic annotation pipeline has been developed to interpret biological meaning based on the accumulation of copy number change across the genome associated with a phenotype of interest. In this study, we develop a comprehensive and systematic pipeline for annotating copy number variants into genes/genomic regions and subsequently pathways and other gene groups using Biofilter - a bioinformatics tool that aggregates over a dozen publicly available databases of prior biological knowledge. Next we conduct enrichment tests of biologically defined groupings of CNVs including genes, pathways, Gene Ontology, or protein families. We applied the proposed pipeline to a CNV dataset from the Marshfield Clinic Personalized Medicine Research Project (PMRP) in a quantitative trait phenotype derived from the electronic health record - total cholesterol. We identified several significant pathways such as toll-like receptor signaling pathway and hepatitis C pathway, gene ontologies (GOs) of nucleoside triphosphatase activity (NTPase) and response to virus, and protein families such as cell morphogenesis that are associated with the total cholesterol phenotype based on CNV profiles (permutation p-value < 0.01). Based on the copy number burden analysis, it follows that the more and larger the copy number changes, the more likely that one or more target genes that influence disease risk and phenotypic severity will be affected. Thus, our study suggests the proposed enrichment pipeline could improve the interpretability of

  10. MIDST: Interoperability for Semantic Annotations

    NASA Astrophysics Data System (ADS)

    Atzeni, Paolo; Del Nostro, Pierluigi; Paolozzi, Stefano

    In the last years, interoperability of ontologies and databases has received a lot of attention. However, most of the work has concentrated on specific problems (such as storing an ontology in a database or making database data available to ontologies) and referred to specific models for each of the two. Here, we propose an approach that aims at being more general and model independent. In fact, it works for different dialects for ontologies and for various data models for databases. Also, it supports translations in both directions (ontologies to databases and vice versa) and it allows for flexibility in the translations, so that customization is possible. The proposal extends recent work for schema and data translation (the MIDST project, which implements the ModelGen operator proposed in model management), which relies on a metamodel approach, where data models and variations thereof are described in a common framework and translations are built as compositions of elementary ones.

  11. Sexuality and Disability: A SIECUS Annotated Bibliography of Available Print Materials.

    ERIC Educational Resources Information Center

    Shortridge, James; And Others

    This annotated listing of print materials on sexuality and disability includes 61 publications as well as 2 databases and 23 organizations. Print materials are listed alphabetically by title within the following categories: books, materials for parents, materials for professionals, curricula, and journals/newsletters. Prices, addresses, and…

  12. Adding Value to Large Multimedia Collections through Annotation Technologies and Tools: Serving Communities of Interest.

    ERIC Educational Resources Information Center

    Shabajee, Paul; Miller, Libby; Dingley, Andy

    A group of research projects based at HP-Labs Bristol, the University of Bristol (England) and ARKive (a new large multimedia database project focused on the worlds biodiversity based in the United Kingdom) are working to develop a flexible model for the indexing of multimedia collections that allows users to annotate content utilizing extensible…

  13. The Comparative Toxicogenomics Database: update 2013.

    PubMed

    Davis, Allan Peter; Murphy, Cynthia Grondin; Johnson, Robin; Lay, Jean M; Lennon-Hopkins, Kelley; Saraceni-Richards, Cynthia; Sciaky, Daniela; King, Benjamin L; Rosenstein, Michael C; Wiegers, Thomas C; Mattingly, Carolyn J

    2013-01-01

    The Comparative Toxicogenomics Database (CTD; http://ctdbase.org/) provides information about interactions between environmental chemicals and gene products and their relationships to diseases. Chemical-gene, chemical-disease and gene-disease interactions manually curated from the literature are integrated to generate expanded networks and predict many novel associations between different data types. CTD now contains over 15 million toxicogenomic relationships. To navigate this sea of data, we added several new features, including DiseaseComps (which finds comparable diseases that share toxicogenomic profiles), statistical scoring for inferred gene-disease and pathway-chemical relationships, filtering options for several tools to refine user analysis and our new Gene Set Enricher (which provides biological annotations that are enriched for gene sets). To improve data visualization, we added a Cytoscape Web view to our ChemComps feature, included color-coded interactions and created a 'slim list' for our MEDIC disease vocabulary (allowing diseases to be grouped for meta-analysis, visualization and better data management). CTD continues to promote interoperability with external databases by providing content and cross-links to their sites. Together, this wealth of expanded chemical-gene-disease data, combined with novel ways to analyze and view content, continues to help users generate testable hypotheses about the molecular mechanisms of environmental diseases.

  14. 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/.

  15. 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

  16. 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/. PMID:27465131

  17. Annotations for the Collaboration of the Health Professionals

    PubMed Central

    Bringay, Sandra; Barry, Catherine; Charlet, Jean

    2006-01-01

    In the French DocPatient project, we work on documentary functionalities to improve the use of the electronic medical record. We suggest that integration of specific uses for paper medical documents in the design of the electronic medical record will improve its utility, use and acceptance. We propose in this paper to add a functionality of annotations in the electronic medical record to reinforce collaboration, coordination and awareness. PMID:17238309

  18. A Novel Quality Measure and Correction Procedure for the Annotation of Microbial Translation Initiation Sites.

    PubMed

    Overmars, Lex; Siezen, Roland J; Francke, Christof

    2015-01-01

    The identification of translation initiation sites (TISs) constitutes an important aspect of sequence-based genome analysis. An erroneous TIS annotation can impair the identification of regulatory elements and N-terminal signal peptides, and also may flaw the determination of descent, for any particular gene. We have formulated a reference-free method to score the TIS annotation quality. The method is based on a comparison of the observed and expected distribution of all TISs in a particular genome given prior gene-calling. We have assessed the TIS annotations for all available NCBI RefSeq microbial genomes and found that approximately 87% is of appropriate quality, whereas 13% needs substantial improvement. We have analyzed a number of factors that could affect TIS annotation quality such as GC-content, taxonomy, the fraction of genes with a Shine-Dalgarno sequence and the year of publication. The analysis showed that only the first factor has a clear effect. We have then formulated a straightforward Principle Component Analysis-based TIS identification strategy to self-organize and score potential TISs. The strategy is independent of reference data and a priori calculations. A representative set of 277 genomes was subjected to the analysis and we found a clear increase in TIS annotation quality for the genomes with a low quality score. The PCA-based annotation was also compared with annotation with the current tool of reference, Prodigal. The comparison for the model genome of Escherichia coli K12 showed that both methods supplement each other and that prediction agreement can be used as an indicator of a correct TIS annotation. Importantly, the data suggest that the addition of a PCA-based strategy to a Prodigal prediction can be used to 'flag' TIS annotations for re-evaluation and in addition can be used to evaluate a given annotation in case a Prodigal annotation is lacking.

  19. A Novel Quality Measure and Correction Procedure for the Annotation of Microbial Translation Initiation Sites

    PubMed Central

    Overmars, Lex; Siezen, Roland J.; Francke, Christof

    2015-01-01

    The identification of translation initiation sites (TISs) constitutes an important aspect of sequence-based genome analysis. An erroneous TIS annotation can impair the identification of regulatory elements and N-terminal signal peptides, and also may flaw the determination of descent, for any particular gene. We have formulated a reference-free method to score the TIS annotation quality. The method is based on a comparison of the observed and expected distribution of all TISs in a particular genome given prior gene-calling. We have assessed the TIS annotations for all available NCBI RefSeq microbial genomes and found that approximately 87% is of appropriate quality, whereas 13% needs substantial improvement. We have analyzed a number of factors that could affect TIS annotation quality such as GC-content, taxonomy, the fraction of genes with a Shine-Dalgarno sequence and the year of publication. The analysis showed that only the first factor has a clear effect. We have then formulated a straightforward Principle Component Analysis-based TIS identification strategy to self-organize and score potential TISs. The strategy is independent of reference data and a priori calculations. A representative set of 277 genomes was subjected to the analysis and we found a clear increase in TIS annotation quality for the genomes with a low quality score. The PCA-based annotation was also compared with annotation with the current tool of reference, Prodigal. The comparison for the model genome of Escherichia coli K12 showed that both methods supplement each other and that prediction agreement can be used as an indicator of a correct TIS annotation. Importantly, the data suggest that the addition of a PCA-based strategy to a Prodigal prediction can be used to ‘flag’ TIS annotations for re-evaluation and in addition can be used to evaluate a given annotation in case a Prodigal annotation is lacking. PMID:26204119

  20. Ribosomal Database Project II

    DOE Data Explorer

    The Ribosomal Database Project (RDP) provides ribosome related data and services to the scientific community, including online data analysis and aligned and annotated Bacterial small-subunit 16S rRNA sequences. As of March 2008, RDP Release 10 is available and currently (August 2009) contains 1,074,075 aligned 16S rRNA sequences. Data that can be downloaded include zipped GenBank and FASTA alignment files, a histogram (in Excel) of the number of RDP sequences spanning each base position, data in the Functional Gene Pipeline Repository, and various user submitted data. The RDP-II website also provides numerous analysis tools.[From the RDP-II home page at http://rdp.cme.msu.edu/index.jsp

  1. High-throughput comparison, functional annotation, and metabolic modeling of plant genomes using the PlantSEED resource.

    PubMed

    Seaver, Samuel M D; Gerdes, Svetlana; Frelin, Océane; Lerma-Ortiz, Claudia; Bradbury, Louis M T; Zallot, Rémi; Hasnain, Ghulam; Niehaus, Thomas D; El Yacoubi, Basma; Pasternak, Shiran; Olson, Robert; Pusch, Gordon; Overbeek, Ross; Stevens, Rick; de Crécy-Lagard, Valérie; Ware, Doreen; Hanson, Andrew D; Henry, Christopher S

    2014-07-01

    The increasing number of sequenced plant genomes is placing new demands on the methods applied to analyze, annotate, and model these genomes. Today's annotation pipelines result in inconsistent gene assignments that complicate comparative analyses and prevent efficient construction of metabolic models. To overcome these problems, we have developed the PlantSEED, an integrated, metabolism-centric database to support subsystems-based annotation and metabolic model reconstruction for plant genomes. PlantSEED combines SEED subsystems technology, first developed for microbial genomes, with refined protein families and biochemical data to assign fully consistent functional annotations to orthologous genes, particularly those encoding primary metabolic pathways. Seamless integration with its parent, the prokaryotic SEED database, makes PlantSEED a unique environment for cross-kingdom comparative analysis of plant and bacterial genomes. The consistent annotations imposed by PlantSEED permit rapid reconstruction and modeling of primary metabolism for all plant genomes in the database. This feature opens the unique possibility of model-based assessment of the completeness and accuracy of gene annotation and thus allows computational identification of genes and pathways that are restricted to certain genomes or need better curation. We demonstrate the PlantSEED system by producing consistent annotations for 10 reference genomes. We also produce a functioning metabolic model for each genome, gapfilling to identify missing annotations and proposing gene candidates for missing annotations. Models are built around an extended biomass composition representing the most comprehensive published to date. To our knowledge, our models are the first to be published for seven of the genomes analyzed. PMID:24927599

  2. Semantic annotation of Web data applied to risk in food.

    PubMed

    Hignette, Gaëlle; Buche, Patrice; Couvert, Olivier; Dibie-Barthélemy, Juliette; Doussot, David; Haemmerlé, Ollivier; Mettler, Eric; Soler, Lydie

    2008-11-30

    A preliminary step to risk in food assessment is the gathering of experimental data. In the framework of the Sym'Previus project (http://www.symprevius.org), a complete data integration system has been designed, grouping data provided by industrial partners and data extracted from papers published in the main scientific journals of the domain. Those data have been classified by means of a predefined vocabulary, called ontology. Our aim is to complement the database with data extracted from the Web. In the framework of the WebContent project (www.webcontent.fr), we have designed a semi-automatic acquisition tool, called @WEB, which retrieves scientific documents from the Web. During the @WEB process, data tables are extracted from the documents and then annotated with the ontology. We focus on the data tables as they contain, in general, a synthesis of data published in the documents. In this paper, we explain how the columns of the data tables are automatically annotated with data types of the ontology and how the relations represented by the table are recognised. We also give the results of our experimentation to assess the quality of such an annotation.

  3. Automatically Annotating Topics in Transcripts of Patient-Provider Interactions via Machine Learning

    PubMed Central

    Wallace, Byron C.; Laws, M. Barton; Small, Kevin; Wilson, Ira B.; Trikalinos, Thomas A.

    2013-01-01

    Background Annotated patient-provider encounters can provide important insights into clinical communication, ultimately suggesting how it might be improved to effect better health outcomes. But annotating outpatient transcripts with Roter or General Medical Interaction Analysis System (GMIAS) codes is expensive, limiting the scope of such analyses. We propose automatically annotating transcripts of patient-provider interactions with topic codes via machine learning. Methods We use a conditional random field (CRF) to model utterance topic probabilities. The model accounts for the sequential structure of conversations and the words comprising utterances. We assess predictive performance via 10- fold cross-validation over GMIAS-annotated transcripts of 360 outpatient visits (over 230,000 utterances). We then used automated in place of manual annotations to reproduce an analysis of 116 additional visits from a randomized trial that used GMIAS to assess the efficacy of an intervention aimed at improving communication around antiretroviral (ARV) adherence. Results With respect to six topic codes, the CRF achieved a mean pairwise kappa compared with human annotators of 0.49 (range: 0.47, 0.53) and a mean overall accuracy of 0.64 (range: 0.62, 0.66). With respect to the RCT re-analysis, results using automated annotations agreed with those obtained using manual ones. According to the manual annotations, the median number of ARV-related utterances without and with the intervention was 49.5 versus 76, respectively (paired sign test p=0.07). Using automated annotations, the respective numbers were 39 versus 55 (p=0.04). Limitations While moderately accurate, the predicted annotations are far from perfect. Conversational topics are intermediate outcomes; their utility is still being researched. Conclusions This foray into automated topic inference suggests that machine learning methods can classify utterances comprising patient-provider interactions into clinically relevant

  4. A State Survey's Experience with the National Geothermal Database System: Lessons Learned to Improve Data Discovery, Access, and Stewardship

    NASA Astrophysics Data System (ADS)

    Hills, D. J.; Richard, S. M.

    2013-12-01

    State Geological Surveys in the U.S., in conjunction with the U.S. Geological Survey, have thousands of databases, directories, and 85,000+ geologic maps that collectively constitute a national geoscience data 'backbone' for research and practical applications. Much of this data has been at-risk in its current format or difficult to access. Organized by the Association of American State Geologists (AASG) with funding from the U.S. Department of Energy, the National Geothermal Data System (NGDS) has been able to make large quantities of geothermal-relevant geoscience data available to the public by creating a national, sustainable, distributed, and interoperable network of data providers. State Surveys or their equivalent have been instrumental to the success of the NGDS, but many have not had previous experience developing the necessary resources for credibility, sustainability, and interoperability beyond their area. The Geological Survey of Alabama (GSA) was no exception; here we expand upon some of the lessons the GSA has learned throughout this process, including a vision of a path forward. A major challenge that had to be overcome was the disconnect between interoperability requirements for the content models and the research interests of scientists providing the data. This was overcome by open and direct dialogue between the content developers and content providers. Although the iterative process could be frustrating at times, the result is a robust and thoroughly tested content model for geothermal data. This content model will provide an excellent starting point for other geoscience data content models. The greatest challenges the GSA encountered during the NGDS project were lack of standardization of our own data resources; lack of documentation; unknown quality of data; and lack of provenance of data. Moving forward, the GSA now has a model for stewardship of data, including what information and metadata should be collected to ensure future

  5. Mining a database of single amplified genomes from Red Sea brine pool extremophiles-improving reliability of gene function prediction using a profile and pattern matching algorithm (PPMA).

    PubMed

    Grötzinger, Stefan W; Alam, Intikhab; Ba Alawi, Wail; Bajic, Vladimir B; Stingl, Ulrich; Eppinger, Jörg

    2014-01-01

    Reliable functional annotation of genomic data is the key-step in the discovery of novel enzymes. Intrinsic sequencing data quality problems of single amplified genomes (SAGs) and poor homology of novel extremophile's genomes pose significant challenges for the attribution of functions to the coding sequences identified. The anoxic deep-sea brine pools of the Red Sea are a promising source of novel enzymes with unique evolutionary adaptation. Sequencing data from Red Sea brine pool cultures and SAGs are annotated and stored in the Integrated Data Warehouse of Microbial Genomes (INDIGO) data warehouse. Low sequence homology of annotated genes (no similarity for 35% of these genes) may translate into false positives when searching for specific functions. The Profile and Pattern Matching (PPM) strategy described here was developed to eliminate false positive annotations of enzyme function before progressing to labor-intensive hyper-saline gene expression and characterization. It utilizes InterPro-derived Gene Ontology (GO)-terms (which represent enzyme function profiles) and annotated relevant PROSITE IDs (which are linked to an amino acid consensus pattern). The PPM algorithm was tested on 15 protein families, which were selected based on scientific and commercial potential. An initial list of 2577 enzyme commission (E.C.) numbers was translated into 171 GO-terms and 49 consensus patterns. A subset of INDIGO-sequences consisting of 58 SAGs from six different taxons of bacteria and archaea were selected from six different brine pool environments. Those SAGs code for 74,516 genes, which were independently scanned for the GO-terms (profile filter) and PROSITE IDs (pattern filter). Following stringent reliability filtering, the non-redundant hits (106 profile hits and 147 pattern hits) are classified as reliable, if at least two relevant descriptors (GO-terms and/or consensus patterns) are present. Scripts for annotation, as well as for the PPM algorithm, are available

  6. Mining a database of single amplified genomes from Red Sea brine pool extremophiles—improving reliability of gene function prediction using a profile and pattern matching algorithm (PPMA)

    PubMed Central

    Grötzinger, Stefan W.; Alam, Intikhab; Ba Alawi, Wail; Bajic, Vladimir B.; Stingl, Ulrich; Eppinger, Jörg

    2014-01-01

    Reliable functional annotation of genomic data is the key-step in the discovery of novel enzymes. Intrinsic sequencing data quality problems of single amplified genomes (SAGs) and poor homology of novel extremophile's genomes pose significant challenges for the attribution of functions to the coding sequences identified. The anoxic deep-sea brine pools of the Red Sea are a promising source of novel enzymes with unique evolutionary adaptation. Sequencing data from Red Sea brine pool cultures and SAGs are annotated and stored in the Integrated Data Warehouse of Microbial Genomes (INDIGO) data warehouse. Low sequence homology of annotated genes (no similarity for 35% of these genes) may translate into false positives when searching for specific functions. The Profile and Pattern Matching (PPM) strategy described here was developed to eliminate false positive annotations of enzyme function before progressing to labor-intensive hyper-saline gene expression and characterization. It utilizes InterPro-derived Gene Ontology (GO)-terms (which represent enzyme function profiles) and annotated relevant PROSITE IDs (which are linked to an amino acid consensus pattern). The PPM algorithm was tested on 15 protein families, which were selected based on scientific and commercial potential. An initial list of 2577 enzyme commission (E.C.) numbers was translated into 171 GO-terms and 49 consensus patterns. A subset of INDIGO-sequences consisting of 58 SAGs from six different taxons of bacteria and archaea were selected from six different brine pool environments. Those SAGs code for 74,516 genes, which were independently scanned for the GO-terms (profile filter) and PROSITE IDs (pattern filter). Following stringent reliability filtering, the non-redundant hits (106 profile hits and 147 pattern hits) are classified as reliable, if at least two relevant descriptors (GO-terms and/or consensus patterns) are present. Scripts for annotation, as well as for the PPM algorithm, are available

  7. OMIGA: Optimized Maker-Based Insect Genome Annotation.

    PubMed

    Liu, Jinding; Xiao, Huamei; Huang, Shuiqing; Li, Fei

    2014-08-01

    Insects are one of the largest classes of animals on Earth and constitute more than half of all living species. The i5k initiative has begun sequencing of more than 5,000 insect genomes, which should greatly help in exploring insect resource and pest control. Insect genome annotation remains challenging because many insects have high levels of heterozygosity. To improve the quality of insect genome annotation, we developed a pipeline, named Optimized Maker-Based Insect Genome Annotation (OMIGA), to predict protein-coding genes from insect genomes. We first mapped RNA-Seq reads to genomic scaffolds to determine transcribed regions using Bowtie, and the putative transcripts were assembled using Cufflink. We then selected highly reliable transcripts with intact coding sequences to train de novo gene prediction software, including Augustus. The re-trained software was used to predict genes from insect genomes. Exonerate was used to refine gene structure and to determine near exact exon/intron boundary in the genome. Finally, we used the software Maker to integrate data from RNA-Seq, de novo gene prediction, and protein alignment to produce an official gene set. The OMIGA pipeline was used to annotate the draft genome of an important insect pest, Chilo suppressalis, yielding 12,548 genes. Different strategies were compared, which demonstrated that OMIGA had the best performance. In summary, we present a comprehensive pipeline for identifying genes in insect genomes that can be widely used to improve the annotation quality in insects. OMIGA is provided at http://ento.njau.edu.cn/omiga.html . PMID:24609470

  8. 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

  9. The development of PIPA: an integrated and automated pipeline for genome-wide protein function annotation

    PubMed Central

    Yu, Chenggang; Zavaljevski, Nela; Desai, Valmik; Johnson, Seth; Stevens, Fred J; Reifman, Jaques

    2008-01-01

    Background Automated protein function prediction methods are needed to keep pace with high-throughput sequencing. With the existence of many programs and databases for inferring different protein functions, a pipeline that properly integrates these resources will benefit from the advantages of each method. However, integrated systems usually do not provide mechanisms to generate customized databases to predict particular protein functions. Here, we describe a tool termed PIPA (Pipeline for Protein Annotation) that has these capabilities. Results PIPA annotates protein functions by combining the results of multiple programs and databases, such as InterPro and the Conserved Domains Database, into common Gene Ontology (GO) terms. The major algorithms implemented in PIPA are: (1) a profile database generation algorithm, which generates customized profile databases to predict particular protein functions, (2) an automated ontology mapping generation algorithm, which maps various classification schemes into GO, and (3) a consensus algorithm to reconcile annotations from the integrated programs and databases. PIPA's profile generation algorithm is employed to construct the enzyme profile database CatFam, which predicts catalytic functions described by Enzyme Commission (EC) numbers. Validation tests show that CatFam yields average recall and precision larger than 95.0%. CatFam is integrated with PIPA. We use an association rule mining algorithm to automatically generate mappings between terms of two ontologies from annotated sample proteins. Incorporating the ontologies' hierarchical topology into the algorithm increases the number of generated mappings. In particular, it generates 40.0% additional mappings from the Clusters of Orthologous Groups (COG) to EC numbers and a six-fold increase in mappings from COG to GO terms. The mappings to EC numbers show a very high precision (99.8%) and recall (96.6%), while the mappings to GO terms show moderate precision (80.0%) and

  10. Automated annotation of chemical names in the literature with tunable accuracy

    PubMed Central

    2011-01-01

    Background A significant portion of the biomedical and chemical literature refers to small molecules. The accurate identification and annotation of compound name that are relevant to the topic of the given literature can establish links between scientific publications and various chemical and life science databases. Manual annotation is the preferred method for these works because well-trained indexers can understand the paper topics as well as recognize key terms. However, considering the hundreds of thousands of new papers published annually, an automatic annotation system with high precision and relevance can be a useful complement to manual annotation. Results An automated chemical name annotation system, MeSH Automated Annotations (MAA), was developed to annotate small molecule names in scientific abstracts with tunable accuracy. This system aims to reproduce the MeSH term annotations on biomedical and chemical literature that would be created by indexers. When comparing automated free text matching to those indexed manually of 26 thousand MEDLINE abstracts, more than 40% of the annotations were false-positive (FP) cases. To reduce the FP rate, MAA incorporated several filters to remove "incorrect" annotations caused by nonspecific, partial, and low relevance chemical names. In part, relevance was measured by the position of the chemical name in the text. Tunable accuracy was obtained by adding or restricting the sections of the text scanned for chemical names. The best precision obtained was 96% with a 28% recall rate. The best performance of MAA, as measured with the F statistic was 66%, which favorably compares to other chemical name annotation systems. Conclusions Accurate chemical name annotation can help researchers not only identify important chemical names in abstracts, but also match unindexed and unstructured abstracts to chemical records. The current work is tested against MEDLINE, but the algorithm is not specific to this corpus and it is possible

  11. Optimizing high performance computing workflow for protein functional annotation.

    PubMed

    Stanberry, Larissa; Rekepalli, Bhanu; Liu, Yuan; Giblock, Paul; Higdon, Roger; Montague, Elizabeth; Broomall, William; Kolker, Natali; Kolker, Eugene

    2014-09-10

    Functional annotation of newly sequenced genomes is one of the major challenges in modern biology. With modern sequencing technologies, the protein sequence universe is rapidly expanding. Newly sequenced bacterial genomes alone contain over 7.5 million proteins. The rate of data generation has far surpassed that of protein annotation. The volume of protein data makes manual curation infeasible, whereas a high compute cost limits the utility of existing automated approaches. In this work, we present an improved and optmized automated workflow to enable large-scale protein annotation. The workflow uses high performance computing architectures and a low complexity classification algorithm to assign proteins into existing clusters of orthologous groups of proteins. On the basis of the Position-Specific Iterative Basic Local Alignment Search Tool the algorithm ensures at least 80% specificity and sensitivity of the resulting classifications. The workflow utilizes highly scalable parallel applications for classification and sequence alignment. Using Extreme Science and Engineering Discovery Environment supercomputers, the workflow processed 1,200,000 newly sequenced bacterial proteins. With the rapid expansion of the protein sequence universe, the proposed workflow will enable scientists to annotate big genome data. PMID:25313296

  12. Functional Annotations of Paralogs: A Blessing and a Curse

    PubMed Central

    Zallot, Rémi; Harrison, Katherine J.; Kolaczkowski, Bryan; de Crécy-Lagard, Valérie

    2016-01-01

    Gene duplication followed by mutation is a classic mechanism of neofunctionalization, producing gene families with functional diversity. In some cases, a single point mutation is sufficient to change the substrate specificity and/or the chemistry performed by an enzyme, making it difficult to accurately separate enzymes with identical functions from homologs with different functions. Because sequence similarity is often used as a basis for assigning functional annotations to genes, non-isofunctional gene families pose a great challenge for genome annotation pipelines. Here we describe how integrating evolutionary and functional information such as genome context, phylogeny, metabolic reconstruction and signature motifs may be required to correctly annotate multifunctional families. These integrative analyses can also lead to the discovery of novel gene functions, as hints from specific subgroups can guide the functional characterization of other members of the family. We demonstrate how careful manual curation processes using comparative genomics can disambiguate subgroups within large multifunctional families and discover their functions. We present the COG0720 protein family as a case study. We also discuss strategies to automate this process to improve the accuracy of genome functional annotation pipelines. PMID:27618105

  13. Functional Annotations of Paralogs: A Blessing and a Curse.

    PubMed

    Zallot, Rémi; Harrison, Katherine J; Kolaczkowski, Bryan; de Crécy-Lagard, Valérie

    2016-01-01

    Gene duplication followed by mutation is a classic mechanism of neofunctionalization, producing gene families with functional diversity. In some cases, a single point mutation is sufficient to change the substrate specificity and/or the chemistry performed by an enzyme, making it difficult to accurately separate enzymes with identical functions from homologs with different functions. Because sequence similarity is often used as a basis for assigning functional annotations to genes, non-isofunctional gene families pose a great challenge for genome annotation pipelines. Here we describe how integrating evolutionary and functional information such as genome context, phylogeny, metabolic reconstruction and signature motifs may be required to correctly annotate multifunctional families. These integrative analyses can also lead to the discovery of novel gene functions, as hints from specific subgroups can guide the functional characterization of other members of the family. We demonstrate how careful manual curation processes using comparative genomics can disambiguate subgroups within large multifunctional families and discover their functions. We present the COG0720 protein family as a case study. We also discuss strategies to automate this process to improve the accuracy of genome functional annotation pipelines. PMID:27618105

  14. Optimizing high performance computing workflow for protein functional annotation.

    PubMed

    Stanberry, Larissa; Rekepalli, Bhanu; Liu, Yuan; Giblock, Paul; Higdon, Roger; Montague, Elizabeth; Broomall, William; Kolker, Natali; Kolker, Eugene

    2014-09-10

    Functional annotation of newly sequenced genomes is one of the major challenges in modern biology. With modern sequencing technologies, the protein sequence universe is rapidly expanding. Newly sequenced bacterial genomes alone contain over 7.5 million proteins. The rate of data generation has far surpassed that of protein annotation. The volume of protein data makes manual curation infeasible, whereas a high compute cost limits the utility of existing automated approaches. In this work, we present an improved and optmized automated workflow to enable large-scale protein annotation. The workflow uses high performance computing architectures and a low complexity classification algorithm to assign proteins into existing clusters of orthologous groups of proteins. On the basis of the Position-Specific Iterative Basic Local Alignment Search Tool the algorithm ensures at least 80% specificity and sensitivity of the resulting classifications. The workflow utilizes highly scalable parallel applications for classification and sequence alignment. Using Extreme Science and Engineering Discovery Environment supercomputers, the workflow processed 1,200,000 newly sequenced bacterial proteins. With the rapid expansion of the protein sequence universe, the proposed workflow will enable scientists to annotate big genome data.

  15. Reevaluating Human Gene Annotation: A Second-Generation Analysis of Chromosome 22

    PubMed Central

    Collins, John E.; Goward, Melanie E.; Cole, Charlotte G.; Smink, Luc J.; Huckle, Elizabeth J.; Knowles, Sarah; Bye, Jacqueline M.; Beare, David M.; Dunham, Ian

    2003-01-01

    We report a second-generation gene annotation of human chromosome 22. Using expressed sequence databases, comparative sequence analysis, and experimental verification, we have extended genes, fused previously fragmented structures, and identified new genes. The total length in exons of annotation was increased by 74% over our previously published annotation and includes 546 protein-coding genes and 234 pseudogenes. Thirty-two potential protein-coding annotations are partial copies of other genes, and may represent duplications on an evolutionary path to change or loss of function. We also identified 31 non-protein-coding transcripts, including 16 possible antisense RNAs. By extrapolation, we estimate the human genome contains 29,000–36,000 protein-coding genes, 21,300 pseudogenes, and 1500 antisense RNAs. We suggest that our revised annotation criteria provide a paradigm for future annotation of the human genome. [Supplemental material is available online at www.genome.org. The sequence data from this study have been submitted to GenBank under accession nos. , -3, , , -2, , , , , -8, -6, , -81, -81, , , , , -3, -2, -2, , , , , , , -5, , , , , -7, , -8, –. The following individuals kindly provided reagents, samples, or unpublished information as indicated in the paper: J. Seilhamer, L. Stuve, H. Roest-Crollius, A. Levine, G. Slater, and J. Kent.] PMID:12529303

  16. Mercator: a fast and simple web server for genome scale functional annotation of plant sequence data.

    PubMed

    Lohse, Marc; Nagel, Axel; Herter, Thomas; May, Patrick; Schroda, Michael; Zrenner, Rita; Tohge, Takayuki; Fernie, Alisdair R; Stitt, Mark; Usadel, Björn

    2014-05-01

    Next-generation technologies generate an overwhelming amount of gene sequence data. Efficient annotation tools are required to make these data amenable to functional genomics analyses. The Mercator pipeline automatically assigns functional terms to protein or nucleotide sequences. It uses the MapMan 'BIN' ontology, which is tailored for functional annotation of plant 'omics' data. The classification procedure performs parallel sequence searches against reference databases, compiles the results and computes the most likely MapMan BINs for each query. In the current version, the pipeline relies on manually curated reference classifications originating from the three reference organisms (Arabidopsis, Chlamydomonas, rice), various other plant species that have a reviewed SwissProt annotation, and more than 2000 protein domain and family profiles at InterPro, CDD and KOG. Functional annotations predicted by Mercator achieve accuracies above 90% when benchmarked against manual annotation. In addition to mapping files for direct use in the visualization software MapMan, Mercator provides graphical overview charts, detailed annotation information in a convenient web browser interface and a MapMan-to-GO translation table to export results as GO terms. Mercator is available free of charge via http://mapman.gabipd.org/web/guest/app/Mercator.

  17. EXTRACT: interactive extraction of environment metadata and term suggestion for metagenomic sample annotation

    PubMed Central

    Pafilis, Evangelos; Buttigieg, Pier Luigi; Ferrell, Barbra; Pereira, Emiliano; Schnetzer, Julia; Arvanitidis, Christos; Jensen, Lars Juhl

    2016-01-01

    The microbial and molecular ecology research communities have made substantial progress on developing standards for annotating samples with environment metadata. However, sample manual annotation is a highly labor intensive process and requires familiarity with the terminologies used. We have therefore developed an interactive annotation tool, EXTRACT, which helps curators identify and extract standard-compliant terms for annotation of metagenomic records and other samples. Behind its web-based user interface, the system combines published methods for named entity recognition of environment, organism, tissue and disease terms. The evaluators in the BioCreative V Interactive Annotation Task found the system to be intuitive, useful, well documented and sufficiently accurate to be helpful in spotting relevant text passages and extracting organism and environment terms. Comparison of fully manual and text-mining-assisted curation revealed that EXTRACT speeds up annotation by 15–25% and helps curators to detect terms that would otherwise have been missed. Database URL: https://extract.hcmr.gr/ PMID:26896844

  18. Database Manager

    ERIC Educational Resources Information Center

    Martin, Andrew

    2010-01-01

    It is normal practice today for organizations to store large quantities of records of related information as computer-based files or databases. Purposeful information is retrieved by performing queries on the data sets. The purpose of DATABASE MANAGER is to communicate to students the method by which the computer performs these queries. This…

  19. Maize databases

    Technology Transfer Automated Retrieval System (TEKTRAN)

    This chapter is a succinct overview of maize data held in the species-specific database MaizeGDB (the Maize Genomics and Genetics Database), and selected multi-species data repositories, such as Gramene/Ensembl Plants, Phytozome, UniProt and the National Center for Biotechnology Information (NCBI), ...

  20. GEMINI: Integrative Exploration of Genetic Variation and Genome Annotations

    PubMed Central

    Paila, Umadevi; Chapman, Brad A.; Kirchner, Rory; Quinlan, Aaron R.

    2013-01-01

    Modern DNA sequencing technologies enable geneticists to rapidly identify genetic variation among many human genomes. However, isolating the minority of variants underlying disease remains an important, yet formidable challenge for medical genetics. We have developed GEMINI (GEnome MINIng), a flexible software package for exploring all forms of human genetic variation. Unlike existing tools, GEMINI integrates genetic variation with a diverse and adaptable set of genome annotations (e.g., dbSNP, ENCODE, UCSC, ClinVar, KEGG) into a unified database to facilitate interpretation and data exploration. Whereas other methods provide an inflexible set of variant filters or prioritization methods, GEMINI allows researchers to compose complex queries based on sample genotypes, inheritance patterns, and both pre-installed and custom genome annotations. GEMINI also provides methods for ad hoc queries and data exploration, a simple programming interface for custom analyses that leverage the underlying database, and both command line and graphical tools for common analyses. We demonstrate GEMINI's utility for exploring variation in personal genomes and family based genetic studies, and illustrate its ability to scale to studies involving thousands of human samples. GEMINI is designed for reproducibility and flexibility and our goal is to provide researchers with a standard framework for medical genomics. PMID:23874191