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Sample records for large public microarray

  1. Microarray Data Processing Techniques for Genome-Scale Network Inference from Large Public Repositories.

    PubMed

    Chockalingam, Sriram; Aluru, Maneesha; Aluru, Srinivas

    2016-09-19

    Pre-processing of microarray data is a well-studied problem. Furthermore, all popular platforms come with their own recommended best practices for differential analysis of genes. However, for genome-scale network inference using microarray data collected from large public repositories, these methods filter out a considerable number of genes. This is primarily due to the effects of aggregating a diverse array of experiments with different technical and biological scenarios. Here we introduce a pre-processing pipeline suitable for inferring genome-scale gene networks from large microarray datasets. We show that partitioning of the available microarray datasets according to biological relevance into tissue- and process-specific categories significantly extends the limits of downstream network construction. We demonstrate the effectiveness of our pre-processing pipeline by inferring genome-scale networks for the model plant Arabidopsis thaliana using two different construction methods and a collection of 11,760 Affymetrix ATH1 microarray chips. Our pre-processing pipeline and the datasets used in this paper are made available at http://alurulab.cc.gatech.edu/microarray-pp.

  2. Gene Expression Browser: Large-Scale and Cross-Experiment Microarray Data Management, Search & Visualization

    USDA-ARS?s Scientific Manuscript database

    The amount of microarray gene expression data in public repositories has been increasing exponentially for the last couple of decades. High-throughput microarray data integration and analysis has become a critical step in exploring the large amount of expression data for biological discovery. Howeve...

  3. Gene Expression Browser: large-scale and cross-experiment microarray data integration, management, search & visualization

    PubMed Central

    2010-01-01

    Background In the last decade, a large amount of microarray gene expression data has been accumulated in public repositories. Integrating and analyzing high-throughput gene expression data have become key activities for exploring gene functions, gene networks and biological pathways. Effectively utilizing these invaluable microarray data remains challenging due to a lack of powerful tools to integrate large-scale gene-expression information across diverse experiments and to search and visualize a large number of gene-expression data points. Results Gene Expression Browser is a microarray data integration, management and processing system with web-based search and visualization functions. An innovative method has been developed to define a treatment over a control for every microarray experiment to standardize and make microarray data from different experiments homogeneous. In the browser, data are pre-processed offline and the resulting data points are visualized online with a 2-layer dynamic web display. Users can view all treatments over control that affect the expression of a selected gene via Gene View, and view all genes that change in a selected treatment over control via treatment over control View. Users can also check the changes of expression profiles of a set of either the treatments over control or genes via Slide View. In addition, the relationships between genes and treatments over control are computed according to gene expression ratio and are shown as co-responsive genes and co-regulation treatments over control. Conclusion Gene Expression Browser is composed of a set of software tools, including a data extraction tool, a microarray data-management system, a data-annotation tool, a microarray data-processing pipeline, and a data search & visualization tool. The browser is deployed as a free public web service (http://www.ExpressionBrowser.com) that integrates 301 ATH1 gene microarray experiments from public data repositories (viz. the Gene

  4. Microarrays

    ERIC Educational Resources Information Center

    Plomin, Robert; Schalkwyk, Leonard C.

    2007-01-01

    Microarrays are revolutionizing genetics by making it possible to genotype hundreds of thousands of DNA markers and to assess the expression (RNA transcripts) of all of the genes in the genome. Microarrays are slides the size of a postage stamp that contain millions of DNA sequences to which single-stranded DNA or RNA can hybridize. This…

  5. Microarrays

    ERIC Educational Resources Information Center

    Plomin, Robert; Schalkwyk, Leonard C.

    2007-01-01

    Microarrays are revolutionizing genetics by making it possible to genotype hundreds of thousands of DNA markers and to assess the expression (RNA transcripts) of all of the genes in the genome. Microarrays are slides the size of a postage stamp that contain millions of DNA sequences to which single-stranded DNA or RNA can hybridize. This…

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

    PubMed

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

    2014-06-15

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

  7. Classification of large microarray datasets using fast random forest construction.

    PubMed

    Manilich, Elena A; Özsoyoğlu, Z Meral; Trubachev, Valeriy; Radivoyevitch, Tomas

    2011-04-01

    Random forest is an ensemble classification algorithm. It performs well when most predictive variables are noisy and can be used when the number of variables is much larger than the number of observations. The use of bootstrap samples and restricted subsets of attributes makes it more powerful than simple ensembles of trees. The main advantage of a random forest classifier is its explanatory power: it measures variable importance or impact of each factor on a predicted class label. These characteristics make the algorithm ideal for microarray data. It was shown to build models with high accuracy when tested on high-dimensional microarray datasets. Current implementations of random forest in the machine learning and statistics community, however, limit its usability for mining over large datasets, as they require that the entire dataset remains permanently in memory. We propose a new framework, an optimized implementation of a random forest classifier, which addresses specific properties of microarray data, takes computational complexity of a decision tree algorithm into consideration, and shows excellent computing performance while preserving predictive accuracy. The implementation is based on reducing overlapping computations and eliminating dependency on the size of main memory. The implementation's excellent computational performance makes the algorithm useful for interactive data analyses and data mining.

  8. Microarrays for Public Health: Genomic Epidemiology of Tuberculosis

    PubMed Central

    Shafi, Jamila; Andrew, Peter W.

    2002-01-01

    In response to a large local school-based outbreak of tuberculosis, we have been evaluating the utility of microarray bacterial genomic analysis in outbreak management. After initial comparison of the isolate from the index case with Mycobacterium tuberculosis H37Rv, it was possible to design robust PCRs directed towards strain-specific deletions. Rapid PCR analysis of isolates proved valuable in determining whether or not other isolates were compatible with the outbreak strain and further microarray studies revealed genetic markers that could be used to discriminate between locally circulating strains.We suggest that this approach forms the basis for developing rapid local genotyping schemes applicable to M. tuberculosis and that application to other pathogens warrants consideration. PMID:18629269

  9. Assessment and integration of publicly available SAGE, cDNA microarray, and oligonucleotide microarray expression data for global coexpression analyses.

    PubMed

    Griffith, Obi L; Pleasance, Erin D; Fulton, Debra L; Oveisi, Mehrdad; Ester, Martin; Siddiqui, Asim S; Jones, Steven J M

    2005-10-01

    Large amounts of gene expression data from several different technologies are becoming available to the scientific community. A common practice is to use these data to calculate global gene coexpression for validation or integration of other "omic" data. To assess the utility of publicly available datasets for this purpose we have analyzed Homo sapiens data from 1202 cDNA microarray experiments, 242 SAGE libraries, and 667 Affymetrix oligonucleotide microarray experiments. The three datasets compared demonstrate significant but low levels of global concordance (rc<0.11). Assessment against Gene Ontology (GO) revealed that all three platforms identify more coexpressed gene pairs with common biological processes than expected by chance. As the Pearson correlation for a gene pair increased it was more likely to be confirmed by GO. The Affymetrix dataset performed best individually with gene pairs of correlation 0.9-1.0 confirmed by GO in 74% of cases. However, in all cases, gene pairs confirmed by multiple platforms were more likely to be confirmed by GO. We show that combining results from different expression platforms increases reliability of coexpression. A comparison with other recently published coexpression studies found similar results in terms of performance against GO but with each method producing distinctly different gene pair lists.

  10. Rapid large-scale oligonucleotide selection for microarrays.

    PubMed

    Rahmann, Sven

    2002-01-01

    We present the first algorithm that selects oligonucleotide probes (e.g. 25-mers) for microarray experiments on a large scale. For example, oligos for human genes can be found within 50 hours. This becomes possible by using the longest common substring as a specificity measure for candidate oligos. We present an algorithm based on a suffix array with additional information that is efficient both in terms of memory usage and running time to rank all candidate oligos according to their specificity. We also introduce the concept of master sequences to describe the sequences from which oligos are to be selected. Constraints such as oligo length, melting temperature, and self-complementarity are incorporated in the master sequence at a preprocessing stage and thus kept separate from the main selection problem. As a result, custom oligos can now be designed for any sequenced genome, just as the technology for on-site chip synthesis is becoming increasingly mature.

  11. The Importance of Normalization on Large and Heterogeneous Microarray Datasets

    EPA Science Inventory

    DNA microarray technology is a powerful functional genomics tool increasingly used for investigating global gene expression in environmental studies. Microarrays can also be used in identifying biological networks, as they give insight on the complex gene-to-gene interactions, ne...

  12. The Importance of Normalization on Large and Heterogeneous Microarray Datasets

    EPA Science Inventory

    DNA microarray technology is a powerful functional genomics tool increasingly used for investigating global gene expression in environmental studies. Microarrays can also be used in identifying biological networks, as they give insight on the complex gene-to-gene interactions, ne...

  13. Large scale patterning of hydrogel microarrays using capillary pinning.

    PubMed

    Gumuscu, Burcu; Bomer, Johan G; van den Berg, Albert; Eijkel, Jan C T

    2015-02-07

    Capillary barriers provide a simple and elegant means for autonomous fluid-flow control in microfluidic systems. In this work, we report on the fabrication of periodic hydrogel microarrays in closed microfluidic systems using non-fluorescent capillary barriers. This design strategy enables the fabrication of picoliter-volume patterns of photopolymerized and thermo-gelling hydrogels without any defects and distortions.

  14. Dealing with missing values in large-scale studies: microarray data imputation and beyond.

    PubMed

    Aittokallio, Tero

    2010-03-01

    High-throughput biotechnologies, such as gene expression microarrays or mass-spectrometry-based proteomic assays, suffer from frequent missing values due to various experimental reasons. Since the missing data points can hinder downstream analyses, there exists a wide variety of ways in which to deal with missing values in large-scale data sets. Nowadays, it has become routine to estimate (or impute) the missing values prior to the actual data analysis. After nearly a decade since the publication of the first missing value imputation methods for gene expression microarray data, new imputation approaches are still being developed at an increasing rate. However, what is lagging behind is a systematic and objective evaluation of the strengths and weaknesses of the different approaches when faced with different types of data sets and experimental questions. In this review, the present strategies for missing value imputation and the measures for evaluating their performance are described. The imputation methods are first reviewed in the context of gene expression microarray data, since most of the methods have been developed for estimating gene expression levels; then, we turn to other large-scale data sets that also suffer from the problems posed by missing values, together with pointers to possible imputation approaches in these settings. Along with a description of the basic principles behind the different imputation approaches, the review tries to provide practical guidance for the users of high-throughput technologies on how to choose the imputation tool for their data and questions, and some additional research directions for the developers of imputation methodologies.

  15. Assessing the utility of confirmatory studies following identification of large-scale genomic imbalances by microarray.

    PubMed

    Sanmann, Jennifer N; Pickering, Diane L; Golden, Denae M; Stevens, Jadd M; Hempel, Thomas E; Althof, Pamela A; Wiggins, Michele L; Starr, Lois J; Davé, Bhavana J; Sanger, Warren G

    2015-11-01

    The identification of clinically relevant genomic dosage anomalies assists in accurate diagnosis, prognosis, and medical management of affected individuals. Technological advancements within the field, such as the advent of microarray, have markedly increased the resolution of detection; however, clinical laboratories have maintained conventional techniques for confirmation of genomic imbalances identified by microarray to ensure diagnostic accuracy. In recent years the utility of this confirmatory testing of large-scale aberrations has been questioned but has not been scientifically addressed. We retrospectively reviewed 519 laboratory cases with genomic imbalances meeting reportable criteria by microarray and subsequently confirmed with a second technology, primarily fluorescence in situ hybridization. All genomic imbalances meeting reportable criteria detected by microarray were confirmed with a second technology. Microarray analysis generated no false-positive results. Confirmatory testing of large-scale genomic imbalances (deletion of ≥150 kb, duplication of ≥500 kb) solely for the purpose of microarray verification may be unwarranted. In some cases, however, adjunct testing is necessary to overcome limitations inherent to microarray. A recommended clinical strategy for adjunct testing following identified genomic imbalances using microarray is detailed.

  16. Large-scale microarray profiling reveals four stages of immune escape in non-Hodgkin lymphomas

    PubMed Central

    Tosolini, Marie; Algans, Christelle; Pont, Frédéric; Ycart, Bernard; Fournié, Jean-Jacques

    2016-01-01

    ABSTRACT Non-Hodgkin B-cell lymphoma (B-NHL) are aggressive lymphoid malignancies that develop in patients due to oncogenic activation, chemo-resistance, and immune evasion. Tumor biopsies show that B-NHL frequently uses several immune escape strategies, which has hindered the development of checkpoint blockade immunotherapies in these diseases. To gain a better understanding of B-NHL immune editing, we hypothesized that the transcriptional hallmarks of immune escape associated with these diseases could be identified from the meta-analysis of large series of microarrays from B-NHL biopsies. Thus, 1446 transcriptome microarrays from seven types of B-NHL were downloaded and assembled from 33 public Gene Expression Omnibus (GEO) datasets, and a method for scoring the transcriptional hallmarks in single samples was developed. This approach was validated by matching scores to phenotypic hallmarks of B-NHL such as proliferation, signaling, metabolic activity, and leucocyte infiltration. Through this method, we observed a significant enrichment of 33 immune escape genes in most diffuse large B-cell lymphoma (DLBCL) and follicular lymphoma (FL) samples, with fewer in mantle cell lymphoma (MCL) and marginal zone lymphoma (MZL) samples. Comparing these gene expression patterns with overall survival data evidenced four stages of cancer immune editing in B-NHL: non-immunogenic tumors (stage 1), immunogenic tumors without immune escape (stage 2), immunogenic tumors with immune escape (stage 3), and fully immuno-edited tumors (stage 4). This model complements the standard international prognostic indices for B-NHL and proposes that immune escape stages 3 and 4 (76% of the FL and DLBCL samples in this data set) identify patients relevant for checkpoint blockade immunotherapies. PMID:27622044

  17. Fabrication of a microarray using a combination of the large circular sense and antisense DNA.

    PubMed

    Doh, Kyung-Oh; Lee, Yun-Han; Han, Kil-Hwan; Uhm, Seok-Yong; Kim, Jong-Pil; Bae, Yun-Ui; Park, Jeong-Hoh; Moon, Ik-Jae; Park, Jong-Gu

    2010-01-01

    In the present study, single-stranded large circular (LC)-sense molecules were utilized as probes for DNA microarrays and showed stronger binding signals than those of PCR-amplified cDNA probes. A microarray experiment using 284 LC-sense DNA probes found 6 upregulated and 7 downregulated genes in A549 cells as compared to WI38VA13 cells. Repeated experiments showed largely consistent results, and microarray data strongly correlated with data acquired from quantitative real-time RT-PCR. A large array comprising 5,079 LC-sense DNA was prepared, and analysis of the mean differential expression from dye-swap experiments revealed 332 upregulated and 509 downregulated genes in A549 cells compared to WI38VA13 cells. Subsequent functional analysis using an LC-antisense library of overexpressed genes identified 28 genes involved in A549 cell growth. These experiments demonstrated the proper features of LC-sense molecules as probe DNA for microarray and the potential utility of the combination of LC-sense and -antisense libraries for an effective functional validation of genes.

  18. Verification of gene expression profiles for colorectal cancer using 12 internet public microarray datasets

    PubMed Central

    Chang, Yu-Tien; Yao, Chung-Tay; Su, Sui-Lung; Chou, Yu-Ching; Chu, Chi-Ming; Huang, Chi-Shuan; Terng, Harn-Jing; Chou, Hsiu-Ling; Wetter, Thomas; Chen, Kang-Hua; Chang, Chi-Wen; Shih, Yun-Wen; Lai, Ching-Huang

    2014-01-01

    AIM: To verify gene expression profiles for colorectal cancer using 12 internet public microarray datasets. METHODS: Logistic regression analysis was performed, and odds ratios for each gene were determined between colorectal cancer (CRC) and controls. Twelve public microarray datasets of GSE 4107, 4183, 8671, 9348, 10961, 13067, 13294, 13471, 14333, 15960, 17538, and 18105, which included 519 cases of adenocarcinoma and 88 normal mucosa controls, were pooled and used to verify 17 selective genes from 3 published studies and estimate the external generality. RESULTS: We validated the 17 CRC-associated genes from studies by Chang et al (Model 1: 5 genes), Marshall et al (Model 2: 7 genes) and Han et al (Model 3: 5 genes) and performed the multivariate logistic regression analysis using the pooled 12 public microarray datasets as well as the external validation. The goodness-of-fit test of Hosmer-Lemeshow (H-L) showed statistical significance (P = 0.044) for Model 2 of Marshall et al in which observed event rates did not match expected event rates in subgroups of the model population. Expected and observed event rates in subgroups were similar, which are called well calibrated, in Models 1, 3 and 4 with non-significant P values of 0.460, 0.194 and 1.000 for H-L tests, respectively. A 7-gene model of CPEB4, EIF2S3, MGC20553, MS4A1, ANXA3, TNFAIP6 and IL2RB was pairwise selected, which showed the best results in logistic regression analysis (H-L P = 1.000, R2 = 0.951, areas under the curve = 0.999, accuracy = 0.968, specificity = 0.966 and sensitivity = 0.994). CONCLUSION: A novel gene expression profile was associated with CRC and can potentially be applied to blood-based detection assays. PMID:25516661

  19. MPrime: efficient large scale multiple primer and oligonucleotide design for customized gene microarrays

    PubMed Central

    Rouchka, Eric C; Khalyfa, Abdelnaby; Cooper, Nigel GF

    2005-01-01

    Background Enhancements in sequencing technology have recently yielded assemblies of large genomes including rat, mouse, human, fruit fly, and zebrafish. The availability of large-scale genomic and genic sequence data coupled with advances in microarray technology have made it possible to study the expression of large numbers of sequence products under several different conditions in days where traditional molecular biology techniques might have taken months, or even years. Therefore, to efficiently study a number of gene products associated with a disease, pathway, or other biological process, it is necessary to be able to design primer pairs or oligonucleotides en masse rather than using a time consuming and laborious gene-by-gene method. Results We have developed an integrated system, MPrime, in order to efficiently calculate primer pairs or specific oligonucleotides for multiple genic regions based on a keyword, gene name, accession number, or sequence fasta format within the rat, mouse, human, fruit fly, and zebrafish genomes. A set of products created for mouse housekeeping genes from MPrime-designed primer pairs has been validated using both PCR-amplification and DNA sequencing. Conclusion These results indicate MPrime accurately incorporates standard PCR primer design characteristics to produce high scoring primer pairs for genes of interest. In addition, sequence similarity for a set of oligonucleotides constructed for the same set of genes indicates high specificity in oligo design. PMID:16014168

  20. Classification of a large microarray data set: Algorithm comparison and analysis of drug signatures

    PubMed Central

    Natsoulis, Georges; El Ghaoui, Laurent; Lanckriet, Gert R.G.; Tolley, Alexander M.; Leroy, Fabrice; Dunlea, Shane; Eynon, Barrett P.; Pearson, Cecelia I.; Tugendreich, Stuart; Jarnagin, Kurt

    2005-01-01

    A large gene expression database has been produced that characterizes the gene expression and physiological effects of hundreds of approved and withdrawn drugs, toxicants, and biochemical standards in various organs of live rats. In order to derive useful biological knowledge from this large database, a variety of supervised classification algorithms were compared using a 597-microarray subset of the data. Our studies show that several types of linear classifiers based on Support Vector Machines (SVMs) and Logistic Regression can be used to derive readily interpretable drug signatures with high classification performance. Both methods can be tuned to produce classifiers of drug treatments in the form of short, weighted gene lists which upon analysis reveal that some of the signature genes have a positive contribution (act as “rewards” for the class-of-interest) while others have a negative contribution (act as “penalties”) to the classification decision. The combination of reward and penalty genes enhances performance by keeping the number of false positive treatments low. The results of these algorithms are combined with feature selection techniques that further reduce the length of the drug signatures, an important step towards the development of useful diagnostic biomarkers and low-cost assays. Multiple signatures with no genes in common can be generated for the same classification end-point. Comparison of these gene lists identifies biological processes characteristic of a given class. PMID:15867433

  1. Large scale comparison of gene expression levels by microarrays and RNAseq using TCGA data.

    PubMed

    Guo, Yan; Sheng, Quanhu; Li, Jiang; Ye, Fei; Samuels, David C; Shyr, Yu

    2013-01-01

    RNAseq and microarray methods are frequently used to measure gene expression level. While similar in purpose, there are fundamental differences between the two technologies. Here, we present the largest comparative study between microarray and RNAseq methods to date using The Cancer Genome Atlas (TCGA) data. We found high correlations between expression data obtained from the Affymetrix one-channel microarray and RNAseq (Spearman correlations coefficients of ∼0.8). We also observed that the low abundance genes had poorer correlations between microarray and RNAseq data than high abundance genes. As expected, due to measurement and normalization differences, Agilent two-channel microarray and RNAseq data were poorly correlated (Spearman correlations coefficients of only ∼0.2). By examining the differentially expressed genes between tumor and normal samples we observed reasonable concordance in directionality between Agilent two-channel microarray and RNAseq data, although a small group of genes were found to have expression changes reported in opposite directions using these two technologies. Overall, RNAseq produces comparable results to microarray technologies in term of expression profiling. The RNAseq normalization methods RPKM and RSEM produce similar results on the gene level and reasonably concordant results on the exon level. Longer exons tended to have better concordance between the two normalization methods than shorter exons.

  2. Large Scale Comparison of Gene Expression Levels by Microarrays and RNAseq Using TCGA Data

    PubMed Central

    Li, Jiang; Ye, Fei; Samuels, David C.; Shyr, Yu

    2013-01-01

    RNAseq and microarray methods are frequently used to measure gene expression level. While similar in purpose, there are fundamental differences between the two technologies. Here, we present the largest comparative study between microarray and RNAseq methods to date using The Cancer Genome Atlas (TCGA) data. We found high correlations between expression data obtained from the Affymetrix one-channel microarray and RNAseq (Spearman correlations coefficients of ∼0.8). We also observed that the low abundance genes had poorer correlations between microarray and RNAseq data than high abundance genes. As expected, due to measurement and normalization differences, Agilent two-channel microarray and RNAseq data were poorly correlated (Spearman correlations coefficients of only ∼0.2). By examining the differentially expressed genes between tumor and normal samples we observed reasonable concordance in directionality between Agilent two-channel microarray and RNAseq data, although a small group of genes were found to have expression changes reported in opposite directions using these two technologies. Overall, RNAseq produces comparable results to microarray technologies in term of expression profiling. The RNAseq normalization methods RPKM and RSEM produce similar results on the gene level and reasonably concordant results on the exon level. Longer exons tended to have better concordance between the two normalization methods than shorter exons. PMID:23977046

  3. Large-scale meta-analysis of cancer microarray data identifies common transcriptional profiles of neoplastic transformation and progression

    PubMed Central

    Rhodes, Daniel R.; Yu, Jianjun; Shanker, K.; Deshpande, Nandan; Varambally, Radhika; Ghosh, Debashis; Barrette, Terrence; Pandey, Akhilesh; Chinnaiyan, Arul M.

    2004-01-01

    Many studies have used DNA microarrays to identify the gene expression signatures of human cancer, yet the critical features of these often unmanageably large signatures remain elusive. To address this, we developed a statistical method, comparative metaprofiling, which identifies and assesses the intersection of multiple gene expression signatures from a diverse collection of microarray data sets. We collected and analyzed 40 published cancer microarray data sets, comprising 38 million gene expression measurements from >3,700 cancer samples. From this, we characterized a common transcriptional profile that is universally activated in most cancer types relative to the normal tissues from which they arose, likely reflecting essential transcriptional features of neoplastic transformation. In addition, we characterized a transcriptional profile that is commonly activated in various types of undifferentiated cancer, suggesting common molecular mechanisms by which cancer cells progress and avoid differentiation. Finally, we validated these transcriptional profiles on independent data sets. PMID:15184677

  4. Development of the first marmoset-specific DNA microarray (EUMAMA): a new genetic tool for large-scale expression profiling in a non-human primate

    PubMed Central

    Datson, Nicole A; Morsink, Maarten C; Atanasova, Srebrena; Armstrong, Victor W; Zischler, Hans; Schlumbohm, Christina; Dutilh, Bas E; Huynen, Martijn A; Waegele, Brigitte; Ruepp, Andreas; de Kloet, E Ronald; Fuchs, Eberhard

    2007-01-01

    Background The common marmoset monkey (Callithrix jacchus), a small non-endangered New World primate native to eastern Brazil, is becoming increasingly used as a non-human primate model in biomedical research, drug development and safety assessment. In contrast to the growing interest for the marmoset as an animal model, the molecular tools for genetic analysis are extremely limited. Results Here we report the development of the first marmoset-specific oligonucleotide microarray (EUMAMA) containing probe sets targeting 1541 different marmoset transcripts expressed in hippocampus. These 1541 transcripts represent a wide variety of different functional gene classes. Hybridisation of the marmoset microarray with labelled RNA from hippocampus, cortex and a panel of 7 different peripheral tissues resulted in high detection rates of 85% in the neuronal tissues and on average 70% in the non-neuronal tissues. The expression profiles of the 2 neuronal tissues, hippocampus and cortex, were highly similar, as indicated by a correlation coefficient of 0.96. Several transcripts with a tissue-specific pattern of expression were identified. Besides the marmoset microarray we have generated 3215 ESTs derived from marmoset hippocampus, which have been annotated and submitted to GenBank [GenBank: EF214838 – EF215447, EH380242 – EH382846]. Conclusion We have generated the first marmoset-specific DNA microarray and demonstrated its use to characterise large-scale gene expression profiles of hippocampus but also of other neuronal and non-neuronal tissues. In addition, we have generated a large collection of ESTs of marmoset origin, which are now available in the public domain. These new tools will facilitate molecular genetic research into this non-human primate animal model. PMID:17592630

  5. Unique gene expression profile in osteoarthritis synovium compared with cartilage: analysis of publicly accessible microarray datasets.

    PubMed

    Park, Robin; Ji, Jong Dae

    2016-06-01

    The purpose of this study was to identify a gene expression signature in osteoarthritis (OA) synovium and genomic pathways likely to be involved in the pathogenesis of OA. Four publicly accessible microarray studies from synovium of OA patients were integrated, and a transcriptomic and network-based meta-analysis was performed. Based on pathways according to the Kyoto Encyclopedia of Genes and Genomes, functional enrichment analysis was performed. Meta-analysis results of OA synovium were compared to two previously published studies of OA cartilage to determine the relative number of common and specific DEGs of the cartilage and synovium. According to our meta-analysis, a total of 1350 genes were found to be differentially expressed in the synovium of OA patients as compared to that of healthy controls. Pathway analysis found 41 significant pathways in the total DEGs, and 22 and 16 pathways in the upregulated and downregulated DEGs, respectively. Cell adhesion molecules and cytokine-cytokine receptor interaction were the most significant pathway in the upregulated and downregulated DEGs, respectively. Comparison of meta-analysis results of OA synovium with results of two previous studies of OA cartilage identified 85 common genes and 1632 cartilage-specific DEGs and 1265 synovium-specific DEGs in the first study; and 142 common genes, and 856 cartilage-specific DEGs and 1208 synovium-specific DEGs in the second study. Our results show a small overlap between the DEGs of the synovium compared to DEGs of the cartilage, suggesting different pathogenic mechanisms that are specific to the synovium.

  6. Public health impact of large airports.

    PubMed

    Passchier, W; Knottnerus, A; Albering, H; Walda, I

    2000-01-01

    Large airports with the related infrastructure, businesses and industrial activities affect the health of the population living, travelling and working in the surroundings of or at the airport. The employment and contributions to economy from the airport and related operations are expected to have a beneficial effect, which, however, is difficult to quantify. More pertinent data are available on the, largely negative, health effects of environmental factors, such as air and soil pollution, noise, accident risk, and landscape changes. Information on the concurrent and cumulative impact of these factors is lacking, but is of primary relevance for public health policy. A committee of the Health Council of The Netherlands recently reviewed the data on the health impact of large airports. It was concluded that, generally, integrated health assessments are not available. Such assessments, as part of sustainable mobility policy, should accompany the further development of the global aviation system.

  7. ArrayWiki: an enabling technology for sharing public microarray data repositories and meta-analyses

    PubMed Central

    Stokes, Todd H; Torrance, JT; Li, Henry; Wang, May D

    2008-01-01

    Background A survey of microarray databases reveals that most of the repository contents and data models are heterogeneous (i.e., data obtained from different chip manufacturers), and that the repositories provide only basic biological keywords linking to PubMed. As a result, it is difficult to find datasets using research context or analysis parameters information beyond a few keywords. For example, to reduce the "curse-of-dimension" problem in microarray analysis, the number of samples is often increased by merging array data from different datasets. Knowing chip data parameters such as pre-processing steps (e.g., normalization, artefact removal, etc), and knowing any previous biological validation of the dataset is essential due to the heterogeneity of the data. However, most of the microarray repositories do not have meta-data information in the first place, and do not have a a mechanism to add or insert this information. Thus, there is a critical need to create "intelligent" microarray repositories that (1) enable update of meta-data with the raw array data, and (2) provide standardized archiving protocols to minimize bias from the raw data sources. Results To address the problems discussed, we have developed a community maintained system called ArrayWiki that unites disparate meta-data of microarray meta-experiments from multiple primary sources with four key features. First, ArrayWiki provides a user-friendly knowledge management interface in addition to a programmable interface using standards developed by Wikipedia. Second, ArrayWiki includes automated quality control processes (caCORRECT) and novel visualization methods (BioPNG, Gel Plots), which provide extra information about data quality unavailable in other microarray repositories. Third, it provides a user-curation capability through the familiar Wiki interface. Fourth, ArrayWiki provides users with simple text-based searches across all experiment meta-data, and exposes data to search engine crawlers

  8. ArrayWiki: an enabling technology for sharing public microarray data repositories and meta-analyses.

    PubMed

    Stokes, Todd H; Torrance, J T; Li, Henry; Wang, May D

    2008-05-28

    A survey of microarray databases reveals that most of the repository contents and data models are heterogeneous (i.e., data obtained from different chip manufacturers), and that the repositories provide only basic biological keywords linking to PubMed. As a result, it is difficult to find datasets using research context or analysis parameters information beyond a few keywords. For example, to reduce the "curse-of-dimension" problem in microarray analysis, the number of samples is often increased by merging array data from different datasets. Knowing chip data parameters such as pre-processing steps (e.g., normalization, artefact removal, etc), and knowing any previous biological validation of the dataset is essential due to the heterogeneity of the data. However, most of the microarray repositories do not have meta-data information in the first place, and do not have a a mechanism to add or insert this information. Thus, there is a critical need to create "intelligent" microarray repositories that (1) enable update of meta-data with the raw array data, and (2) provide standardized archiving protocols to minimize bias from the raw data sources. To address the problems discussed, we have developed a community maintained system called ArrayWiki that unites disparate meta-data of microarray meta-experiments from multiple primary sources with four key features. First, ArrayWiki provides a user-friendly knowledge management interface in addition to a programmable interface using standards developed by Wikipedia. Second, ArrayWiki includes automated quality control processes (caCORRECT) and novel visualization methods (BioPNG, Gel Plots), which provide extra information about data quality unavailable in other microarray repositories. Third, it provides a user-curation capability through the familiar Wiki interface. Fourth, ArrayWiki provides users with simple text-based searches across all experiment meta-data, and exposes data to search engine crawlers (Semantic Agents

  9. DNA microarrays in the undergraduate microbiology lab: experimentation and handling large datasets in as few as six weeks.

    PubMed

    Kushner, David B

    2007-01-01

    DNA microarrays have significantly impacted the study of gene expression on a genome-wide level but also have forced a more global consideration of research questions. As such, it has become critical to introduce undergraduate students to genomics approaches to research. A challenge with performing a DNA microarray experiment in the teaching lab is determining the time required for the study and how to handle the voluminous data generated. At an unexpectedly low cost, a 6-week, project-based lab module has been developed that provides 3 weeks for wet lab (hands-on work with the DNA microarrays) and 3 weeks for dry lab (analyzing data, using databases to help with data analysis, and considering the meaning of data within the large dataset). Options exist for extending the number of weeks dedicated to the project, but 6 weeks is sufficient for providing an introduction to both experimental genomics and data analysis. Students indicate that being able to both perform array experiments and thoroughly analyze data enriches their understanding of genomics and the complexity of biological systems.

  10. A classification based framework for quantitative description of large-scale microarray data

    PubMed Central

    Sangurdekar, Dipen P; Srienc, Friedrich; Khodursky, Arkady B

    2006-01-01

    Genome-wide surveys of transcription depend on gene classifications for the purpose of data interpretation. We propose a new information-theoretical-based method to: assess significance of co-expression within any gene group; quantitatively describe condition-specific gene-class activity; and systematically evaluate conditions in terms of gene-class activity. We applied this technique to describe microarray data tracking Escherichia coli transcriptional responses to more than 30 chemical and physiological perturbations. We correlated the nature and breadth of the responses with the nature of perturbation, identified gene group proxies for the perturbation classes and quantitatively compared closely related physiological conditions. PMID:16626502

  11. PTM Microarray: Request for Year 3 Set-Aside Funds — EDRN Public Portal

    Cancer.gov

    We hypothesize that PTMs on proteins that are secreted by the breast will provide a more sensitive method for detecting breast cancer than analysis of the parent protein. We will antibody microarrays to have examine 9 circulating proteins, each of which is known to be actively secreted by the breast, for several structurally and functionally distinct PTMs. We will determine if these modified proteins have the potential to used in the early detection of breast cancer.

  12. High throughput tissue microarray analysis of FHIT expression in diffuse large cell B-cell lymphoma from Saudi Arabia.

    PubMed

    Al Kuraya, Khawla; Siraj, Abdul Khalid; Bavi, Prashant; Al-Jomah, Naif; El-Solh, Hassan; Ezzat, Adnan; Al-Dayel, Fouad; Belgaumi, Asim; Al-Kofide, Amani; Sabbah, Rajeh; Sheikh, Salwa; Amr, Samir; Simon, Ronald; Sauter, Guido

    2006-08-01

    Recent studies have suggested a potential prognostic role of alterations of the fragile histidine triad (FHIT) gene in diffuse large B-cell lymphoma. To evaluate possible mechanisms of FHIT inactivation and to further clarify its potential prognostic relevance, we analyzed a set of 114 diffuse large B-cell lymphoma with clinical follow-up information. Tissue microarrays were analyzed by immunohistochemistry for protein expression, and corresponding DNA samples were analyzed for FHIT promotor hypermethlyation. Reduced or absent FHIT expression was found in 75 of 114 diffuse large B-cell lymphoma (66%), but was unrelated to clinical tumor stage or patient prognosis. FHIT promotor hypermethylation was observed in 29 of 93 (23%) interpretable diffuse large B-cell lymphoma. Hypermethylation was not significantly correlated to protein expression loss, which could be explained by competing mechanisms for FHIT inactivation in a substantial fraction of non FHIT hypermethylated diffuse large B-cell lymphoma. Hypermethylation was significantly associated with poor prognosis of diffuse large B-cell lymphoma patients and predominantly seen in nongerminal center diffuse large B-cell lymphoma (27%), but less frequent (13%) in germinal center diffuse large B-cell lymphoma. In summary, these data suggest that promotor hypermethylation is responsible for reduced FHIT expression in a substantial subset of diffuse large B-cell lymphoma, which is primarily composed of nongerminal center subtype with poor patient prognosis.

  13. MALDI imaging-based identification of prognostically relevant signals in bladder cancer using large-scale tissue microarrays.

    PubMed

    Steurer, Stefan; Singer, Julius Magnus; Rink, Michael; Chun, Felix; Dahlem, Roland; Simon, Ronald; Burandt, Eike; Stahl, Phillip; Terracciano, Luigi; Schlomm, Thorsten; Wagner, Walter; Höppner, Wolfgang; Omidi, Maryam; Kraus, Olga; Kwiatkowski, Marcel; Doh, Ousman; Fisch, Margit; Soave, Armin; Sauter, Guido; Wurlitzer, Marcus; Schlüter, Hartmut; Minner, Sarah

    2014-11-01

    Although most patients with urinary bladder cancer present with noninvasive and low-malignant stages of the disease, about 20% eventually develop life-threatening metastatic tumors. This study was designed to evaluate the potential of matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) to identify molecular markers predicting the clinical course of bladder cancer. We employed MALDI-MSI to a bladder cancer tissue microarray including paraffin-embedded tissue samples from 697 patients with clinical follow-up data to search for prognostically relevant associations. Analysis of our MALDI imaging data revealed 40 signals in the mass spectra (m/z signals) associated with epithelial structures. The presence of numerous m/z signals was statistically related to one or several phenotypical findings including tumor aggressiveness (stage, grade, or nodal status; 30 signals), solid (5 signals) or papillary (3 signals) growth patterns, and increased (6 signals) or decreased (12 signals) cell proliferation, as determined by Ki-67 immunohistochemistry. Two signals were linked with tumor recurrence in noninvasive (pTa category) tumors, of which one was also related to progression from pTa-category to pT1-category disease. The absence of one m/z signal was linked with decreased survival in the subset of 102 muscle-invasive cancers. Our data demonstrate the suitability of combining MSI and large-scale tissue microarrays to simultaneously identify and validate clinically useful molecular markers in urinary bladder cancer. Copyright © 2014 Elsevier Inc. All rights reserved.

  14. Large-scale atlas of microarray data reveals the distinct expression landscape of different tissues in Arabidopsis

    SciTech Connect

    He, Fei; Maslov, Sergei; Yoo, Shinjae; Wang, Daifeng; Kumari, Sunita; Gerstein, Mark; Ware, Doreen

    2016-05-25

    Here, transcriptome datasets from thousands of samples of the model plant Arabidopsis thaliana have been collectively generated by multiple individual labs. Although integration and meta-analysis of these samples has become routine in the plant research community, it is often hampered by the lack of metadata or differences in annotation styles by different labs. In this study, we carefully selected and integrated 6,057 Arabidopsis microarray expression samples from 304 experiments deposited to NCBI GEO. Metadata such as tissue type, growth condition, and developmental stage were manually curated for each sample. We then studied global expression landscape of the integrated dataset and found that samples of the same tissue tend to be more similar to each other than to samples of other tissues, even in different growth conditions or developmental stages. Root has the most distinct transcriptome compared to aerial tissues, but the transcriptome of cultured root is more similar to those of aerial tissues as the former samples lost their cellular identity. Using a simple computational classification method, we showed that the tissue type of a sample can be successfully predicted based on its expression profile, opening the door for automatic metadata extraction and facilitating re-use of plant transcriptome data. As a proof of principle we applied our automated annotation pipeline to 708 RNA-seq samples from public repositories and verified accuracy of our predictions with samples’ metadata provided by authors.

  15. Large-scale atlas of microarray data reveals the distinct expression landscape of different tissues in Arabidopsis

    DOE PAGES

    He, Fei; Maslov, Sergei; Yoo, Shinjae; ...

    2016-05-25

    Here, transcriptome datasets from thousands of samples of the model plant Arabidopsis thaliana have been collectively generated by multiple individual labs. Although integration and meta-analysis of these samples has become routine in the plant research community, it is often hampered by the lack of metadata or differences in annotation styles by different labs. In this study, we carefully selected and integrated 6,057 Arabidopsis microarray expression samples from 304 experiments deposited to NCBI GEO. Metadata such as tissue type, growth condition, and developmental stage were manually curated for each sample. We then studied global expression landscape of the integrated dataset andmore » found that samples of the same tissue tend to be more similar to each other than to samples of other tissues, even in different growth conditions or developmental stages. Root has the most distinct transcriptome compared to aerial tissues, but the transcriptome of cultured root is more similar to those of aerial tissues as the former samples lost their cellular identity. Using a simple computational classification method, we showed that the tissue type of a sample can be successfully predicted based on its expression profile, opening the door for automatic metadata extraction and facilitating re-use of plant transcriptome data. As a proof of principle we applied our automated annotation pipeline to 708 RNA-seq samples from public repositories and verified accuracy of our predictions with samples’ metadata provided by authors.« less

  16. Large-scale atlas of microarray data reveals the distinct expression landscape of different tissues in Arabidopsis

    SciTech Connect

    He, Fei; Maslov, Sergei; Yoo, Shinjae; Wang, Daifeng; Kumari, Sunita; Gerstein, Mark; Ware, Doreen

    2016-05-25

    Here, transcriptome datasets from thousands of samples of the model plant Arabidopsis thaliana have been collectively generated by multiple individual labs. Although integration and meta-analysis of these samples has become routine in the plant research community, it is often hampered by the lack of metadata or differences in annotation styles by different labs. In this study, we carefully selected and integrated 6,057 Arabidopsis microarray expression samples from 304 experiments deposited to NCBI GEO. Metadata such as tissue type, growth condition, and developmental stage were manually curated for each sample. We then studied global expression landscape of the integrated dataset and found that samples of the same tissue tend to be more similar to each other than to samples of other tissues, even in different growth conditions or developmental stages. Root has the most distinct transcriptome compared to aerial tissues, but the transcriptome of cultured root is more similar to those of aerial tissues as the former samples lost their cellular identity. Using a simple computational classification method, we showed that the tissue type of a sample can be successfully predicted based on its expression profile, opening the door for automatic metadata extraction and facilitating re-use of plant transcriptome data. As a proof of principle we applied our automated annotation pipeline to 708 RNA-seq samples from public repositories and verified accuracy of our predictions with samples’ metadata provided by authors.

  17. Transcriptional profiling of epidermal keratinocytes: comparison of genes expressed in skin, cultured keratinocytes, and reconstituted epidermis, using large DNA microarrays.

    PubMed

    Gazel, Alix; Ramphal, Patricia; Rosdy, Martin; De Wever, Bart; Tornier, Carine; Hosein, Nadia; Lee, Brian; Tomic-Canic, Marjana; Blumenberg, Miroslav

    2003-12-01

    Epidermal keratinocytes are complex cells that create a unique three-dimensional (3-D) structure, differentiate through a multistage process, and respond to extracellular stimuli from nearby cells. Consequently, keratinocytes express many genes, i.e., have a relatively large "transcriptome." To determine which of the expressed genes are innate to keratinocytes, which are specific for the differentiation and 3-D architecture, and which are induced by other cell types, we compared the transcriptomes of skin from human subjects, differentiating 3-D reconstituted epidermis, cultured keratinocytes, and nonkeratinocyte cell types. Using large oligonucleotide microarrays, we analyzed five or more replicates of each, which yielded statistically consistent data and allowed identification of the differentially expressed genes. Epidermal keratinocytes, unlike other cells, express many proteases and protease inhibitors and genes that protect from UV light. Skin specifically expresses a higher number of receptors, secreted proteins, and transcription factors, perhaps influenced by the presence of nonkeratinocyte cell types. Surprisingly, mitochondrial proteins were significantly suppressed in skin, suggesting a low metabolic rate. Three-dimensional samples, skin and reconstituted epidermis, are similar to each other, expressing epidermal differentiation markers. Cultured keratinocytes express many cell-cycle and DNA replication genes, as well as integrins and extracellular matrix proteins. These results define innate, architecture-specific, and cell-type-regulated genes in epidermis.

  18. Large-scale atlas of microarray data reveals the distinct expression landscape of different tissues in Arabidopsis.

    PubMed

    He, Fei; Yoo, Shinjae; Wang, Daifeng; Kumari, Sunita; Gerstein, Mark; Ware, Doreen; Maslov, Sergei

    2016-06-01

    Transcriptome data sets from thousands of samples of the model plant Arabidopsis thaliana have been collectively generated by multiple individual labs. Although integration and meta-analysis of these samples has become routine in the plant research community, it is often hampered by a lack of metadata or differences in annotation styles of different labs. In this study, we carefully selected and integrated 6057 Arabidopsis microarray expression samples from 304 experiments deposited to the Gene Expression Omnibus (GEO) at the National Center for Biotechnology Information (NCBI). Metadata such as tissue type, growth conditions and developmental stage were manually curated for each sample. We then studied the global expression landscape of the integrated data set and found that samples of the same tissue tend to be more similar to each other than to samples of other tissues, even in different growth conditions or developmental stages. Root has the most distinct transcriptome, compared with aerial tissues, but the transcriptome of cultured root is more similar to the transcriptome of aerial tissues, as the cultured root samples lost their cellular identity. Using a simple computational classification method, we showed that the tissue type of a sample can be successfully predicted based on its expression profile, opening the door for automatic metadata extraction and facilitating the re-use of plant transcriptome data. As a proof of principle, we applied our automated annotation pipeline to 708 RNA-seq samples from public repositories and verified the accuracy of our predictions with sample metadata provided by the authors. © 2016 The Authors The Plant Journal © 2016 John Wiley & Sons Ltd.

  19. Celsius: a community resource for Affymetrix microarray data.

    PubMed

    Day, Allen; Carlson, Marc R J; Dong, Jun; O'Connor, Brian D; Nelson, Stanley F

    2007-01-01

    Celsius is a data warehousing system to aggregate Affymetrix CEL files and associated metadata. It provides mechanisms for importing, storing, querying, and exporting large volumes of primary and pre-processed microarray data. Celsius contains ten billion assay measurements and affiliated metadata. It is the largest publicly available source of Affymetrix microarray data, and through sheer volume it allows a sophisticated, broad view of transcription that has not previously been possible.

  20. A meta-analysis of public microarray data identifies gene regulatory pathways deregulated in peripheral blood mononuclear cells from individuals with Systemic Lupus Erythematosus compared to those without.

    PubMed

    Kröger, Wendy; Mapiye, Darlington; Entfellner, Jean-Baka Domelevo; Tiffin, Nicki

    2016-11-15

    Systemic Lupus Erythematosus (SLE) is a complex, multi-systemic, autoimmune disease for which the underlying aetiological mechanisms are poorly understood. The genetic and molecular processes underlying lupus have been extensively investigated using a variety of -omics approaches, including genome-wide association studies, candidate gene studies and microarray experiments of differential gene expression in lupus samples compared to controls. This study analyses a combination of existing microarray data sets to identify differentially regulated genetic pathways that are dysregulated in human peripheral blood mononuclear cells from SLE patients compared to unaffected controls. Two statistical approaches, quantile discretisation and scaling, are used to combine publicly available expression microarray datasets and perform a meta-analysis of differentially expressed genes. Differentially expressed genes implicated in interferon signaling were identified by the meta-analysis, in agreement with the findings of the individual studies that generated the datasets used. In contrast to the individual studies, however, the meta-analysis and subsequent pathway analysis additionally highlighted TLR signaling, oxidative phosphorylation and diapedesis and adhesion regulatory networks as being differentially regulated in peripheral blood mononuclear cells (PBMCs) from SLE patients compared to controls. Our analysis demonstrates that it is possible to derive additional information from publicly available expression data using meta-analysis techniques, which is particularly relevant to research into rare diseases where sample numbers can be limiting.

  1. Multievidence microarray mining.

    PubMed

    Seifert, Martin; Scherf, Matthias; Epple, Anton; Werner, Thomas

    2005-10-01

    Microarray mining is a challenging task because of the superposition of several processes in the data. We believe that the combination of microarray data-based analyses (statistical significance analysis of gene expression) with array-independent analyses (literature-mining and promoter analysis) enables some of the problems of traditional array analysis to be overcome. As a proof-of-principle, we revisited publicly available microarray data derived from an experiment with platelet-derived growth factor (PDGF)-stimulated fibroblasts. Our strategy revealed results beyond the detection of the major metabolic pathway known to be linked to the PDGF response: we were able to identify the crosstalking regulatory networks underlying the metabolic pathway without using a priori knowledge about the experiment.

  2. A Serological Protein Microarray for Detection of Multiple Cross-Reactive Flavivirus Infections in Horses for Veterinary and Public Health Surveillance.

    PubMed

    Cleton, N B; van Maanen, K; Bergervoet, S A; Bon, N; Beck, C; Godeke, G-J; Lecollinet, S; Bowen, R; Lelli, D; Nowotny, N; Koopmans, M P G; Reusken, C B E M

    2016-09-15

    The genus Flavivirus in the family Flaviviridae includes some of the most important examples of emerging zoonotic arboviruses that are rapidly spreading across the globe. Japanese encephalitis virus (JEV), West Nile virus (WNV), St. Louis encephalitis virus (SLEV) and Usutu virus (USUV) are mosquito-borne members of the JEV serological group. Although most infections in humans are asymptomatic or present with mild flu-like symptoms, clinical manifestations of JEV, WNV, SLEV, USUV and tick-borne encephalitis virus (TBEV) can include severe neurological disease and death. In horses, infection with WNV and JEV can lead to severe neurological disease and death, while USUV, SLEV and TBEV infections are mainly asymptomatic, however, and induce antibody responses. Horses often serve as sentinels to monitor active virus circulation in serological surveillance programmes specifically for WNV, USUV and JEV. Here, we developed and validated a NS1-antigen protein microarray for the serological differential diagnosis of flavivirus infections in horses using sera of experimentally and naturally infected symptomatic as well as asymptomatic horses. Using samples from experimentally infected horses, an IgG and IgM specificity of 100% and a sensitivity of 95% for WNV and 100% for JEV was achieved with a cut-off titre of 1 : 20 based on ROC calculation. In field settings, the microarray identified 93-100% of IgG-positive horses with recent WNV infections and 87% of TBEV IgG-positive horses. WNV IgM sensitivity was 80%. Differentiation between closely related flaviviruses by the NS1-antigen protein microarray is possible, even though we identified some instances of cross-reactivity among antibodies. However, the assay is not able to differentiate between naturally infected horses and animals vaccinated with an inactivated WNV whole-virus vaccine. We showed that the NS1-microarray can potentially be used for diagnosing and distinguishing flavivirus infections in horses and for public

  3. Microarray gene expression analysis of fixed archival tissue permits molecular classification and identification of potential therapeutic targets in diffuse large B-cell lymphoma.

    PubMed

    Linton, Kim; Howarth, Christopher; Wappett, Mark; Newton, Gillian; Lachel, Cynthia; Iqbal, Javeed; Pepper, Stuart; Byers, Richard; Chan, Wing John; Radford, John

    2012-01-01

    Refractory/relapsed diffuse large B-cell lymphoma (DLBCL) has a poor prognosis. Novel drugs targeting the constitutively activated NF-κB pathway characteristic of ABC-DLBCL are promising, but evaluation depends on accurate activated B cell-like (ABC)/germinal center B cell-like (GCB) molecular classification. This is traditionally performed on gene microarray expression profiles of fresh biopsies, which are not routinely collected, or by immunohistochemistry on formalin-fixed, paraffin-embedded (FFPE) tissue, which lacks reproducibility and classification accuracy. We explored the possibility of using routine archival FFPE tissue for gene microarray applications. We examined Affymetrix HG U133 Plus 2.0 gene expression profiles from paired archival FFPE and fresh-frozen tissues of 40 ABC/GCB-classified DLBCL cases to compare classification accuracy and test the potential for this approach to aid the discovery of therapeutic targets and disease classifiers in DLBCL. Unsupervised hierarchical clustering of unselected present probe sets distinguished ABC/GCB in FFPE with remarkable accuracy, and a Bayesian classifier correctly assigned 32 of 36 cases with >90% probability. Enrichment for NF-κB genes was appropriately seen in ABC-DLBCL FFPE tissues. The top discriminatory genes expressed in FFPE separated cases with high statistical significance and contained novel biology with potential therapeutic insights, warranting further investigation. These results support a growing understanding that archival FFPE tissues can be used in microarray experiments aimed at molecular classification, prognostic biomarker discovery, and molecular exploration of rare diseases. Copyright © 2012 American Society for Investigative Pathology and the Association for Molecular Pathology. Published by Elsevier Inc. All rights reserved.

  4. Publicly Releasing a Large Simulation Dataset with NDS Labs

    NASA Astrophysics Data System (ADS)

    Goldbaum, Nathan

    2016-03-01

    Optimally, all publicly funded research should be accompanied by the tools, code, and data necessary to fully reproduce the analysis performed in journal articles describing the research. This ideal can be difficult to attain, particularly when dealing with large (>10 TB) simulation datasets. In this lightning talk, we describe the process of publicly releasing a large simulation dataset to accompany the submission of a journal article. The simulation was performed using Enzo, an open source, community-developed N-body/hydrodynamics code and was analyzed using a wide range of community- developed tools in the scientific Python ecosystem. Although the simulation was performed and analyzed using an ecosystem of sustainably developed tools, we enable sustainable science using our data by making it publicly available. Combining the data release with the NDS Labs infrastructure allows a substantial amount of added value, including web-based access to analysis and visualization using the yt analysis package through an IPython notebook interface. In addition, we are able to accompany the paper submission to the arXiv preprint server with links to the raw simulation data as well as interactive real-time data visualizations that readers can explore on their own or share with colleagues during journal club discussions. It is our hope that the value added by these services will substantially increase the impact and readership of the paper.

  5. Microarrays for Undergraduate Classes

    ERIC Educational Resources Information Center

    Hancock, Dale; Nguyen, Lisa L.; Denyer, Gareth S.; Johnston, Jill M.

    2006-01-01

    A microarray experiment is presented that, in six laboratory sessions, takes undergraduate students from the tissue sample right through to data analysis. The model chosen, the murine erythroleukemia cell line, can be easily cultured in sufficient quantities for class use. Large changes in gene expression can be induced in these cells by…

  6. Microarrays for Undergraduate Classes

    ERIC Educational Resources Information Center

    Hancock, Dale; Nguyen, Lisa L.; Denyer, Gareth S.; Johnston, Jill M.

    2006-01-01

    A microarray experiment is presented that, in six laboratory sessions, takes undergraduate students from the tissue sample right through to data analysis. The model chosen, the murine erythroleukemia cell line, can be easily cultured in sufficient quantities for class use. Large changes in gene expression can be induced in these cells by…

  7. Improved estimation of the noncentrality parameter distribution from a large number of t-statistics, with applications to false discovery rate estimation in microarray data analysis.

    PubMed

    Qu, Long; Nettleton, Dan; Dekkers, Jack C M

    2012-12-01

    Given a large number of t-statistics, we consider the problem of approximating the distribution of noncentrality parameters (NCPs) by a continuous density. This problem is closely related to the control of false discovery rates (FDR) in massive hypothesis testing applications, e.g., microarray gene expression analysis. Our methodology is similar to, but improves upon, the existing approach by Ruppert, Nettleton, and Hwang (2007, Biometrics, 63, 483-495). We provide parametric, nonparametric, and semiparametric estimators for the distribution of NCPs, as well as estimates of the FDR and local FDR. In the parametric situation, we assume that the NCPs follow a distribution that leads to an analytically available marginal distribution for the test statistics. In the nonparametric situation, we use convex combinations of basis density functions to estimate the density of the NCPs. A sequential quadratic programming procedure is developed to maximize the penalized likelihood. The smoothing parameter is selected with the approximate network information criterion. A semiparametric estimator is also developed to combine both parametric and nonparametric fits. Simulations show that, under a variety of situations, our density estimates are closer to the underlying truth and our FDR estimates are improved compared with alternative methods. Data-based simulations and the analyses of two microarray datasets are used to evaluate the performance in realistic situations.

  8. Chromosome Microarray.

    PubMed

    Anderson, Sharon

    2016-01-01

    Over the last half century, knowledge about genetics, genetic testing, and its complexity has flourished. Completion of the Human Genome Project provided a foundation upon which the accuracy of genetics, genomics, and integration of bioinformatics knowledge and testing has grown exponentially. What is lagging, however, are efforts to reach and engage nurses about this rapidly changing field. The purpose of this article is to familiarize nurses with several frequently ordered genetic tests including chromosomes and fluorescence in situ hybridization followed by a comprehensive review of chromosome microarray. It shares the complexity of microarray including how testing is performed and results analyzed. A case report demonstrates how this technology is applied in clinical practice and reveals benefits and limitations of this scientific and bioinformatics genetic technology. Clinical implications for maternal-child nurses across practice levels are discussed.

  9. Public Relations Handbook for Vocational Education in Large Cities.

    ERIC Educational Resources Information Center

    Koble, Daniel E., Jr.; And Others

    Intended for use by urban vocational staff members who face public relations problems and need to facilitate the outreach process in their cities, this handbook contains guidelines for organizing the public. First, Sanford's definition of public relations is outlined, followed by an explanation of why vocational education needs public relations.…

  10. Multipathogen oligonucleotide microarray for environmental and biodefense applications.

    PubMed

    Sergeev, Nikolay; Distler, Margaret; Courtney, Shannon; Al-Khaldi, Sufian F; Volokhov, Dmitriy; Chizhikov, Vladimir; Rasooly, Avraham

    2004-11-01

    Food-borne pathogens are a major health problem. The large and diverse number of microbial pathogens and their virulence factors has fueled interest in technologies capable of detecting multiple pathogens and multiple virulence factors simultaneously. Some of these pathogens and their toxins have potential use as bioweapons. DNA microarray technology allows the simultaneous analysis of thousands of sequences of DNA in a relatively short time, making it appropriate for biodefense and for public health uses. This paper describes methods for using DNA microarrays to detect and analyze microbial pathogens. The FDA-1 microarray was developed for the simultaneous detection of several food-borne pathogens and their virulence factors including Listeria spp., Campylobacter spp., Staphylococcus aureus enterotoxin genes and Clostridium perfringens toxin genes. Three elements were incorporated to increase confidence in the microarray detection system: redundancy of genes, redundancy of oligonucleotide probes (oligoprobes) for a specific gene, and quality control oligoprobes to monitor array spotting and target DNA hybridization. These elements enhance the reliability of detection and reduce the chance of erroneous results due to the genetic variability of microbes or technical problems with the microarray. The results presented demonstrate the potential of oligonucleotide microarrays for detection of environmental and biodefense relevant microbial pathogens.

  11. Microarray simulator as educational tool.

    PubMed

    Ruusuvuori, Pekka; Nykter, Matti; Mäkiraatikka, Eeva; Lehmussola, Antti; Korpelainen, Tomi; Erkkilä, Timo; Yli-Harja, Olli

    2007-01-01

    As many real-world applications, microarray measurements are inapplicable for large-scale teaching purposes due to their laborious preparation process and expense. Fortunately, many phases of the array preparation process can be efficiently demonstrated by using a software simulator tool. Here we propose the use of microarray simulator as an aiding tool in teaching of computational biology. Three case studies on educational use of the simulator are presented, which demonstrate the effect of gene knock-out, synthetic time series, and effect of noise sources. We conclude that the simulator, used for teaching the principles of microarray measurement technology, proved to be a useful tool in education.

  12. Minimizing DNA microarrays to a single molecule per spot: using zero-mode waveguide technology to obtain kinetic data for a large number of short oligonucleotide hybridization reactions

    NASA Astrophysics Data System (ADS)

    Sobek, Jens; Rehrauer, Hubert; Kuhn, Gerrit; Schlapbach, Ralph

    2016-03-01

    We have shown recently that the hybridization of short oligonucleotides can be studied in a zero-mode waveguide nanostructure (ZMW) chip using a modified DNA sequencer.[1] Here we present an extension of this method enabling the parallel measurement of kinetic constants of a large number of hybridization reactions on a single chip. This can be achieved by immobilization of a mixture of oligonucleotides, which leads to a statistical and random distribution of single molecules in the 150'000 ZMWs of a SMRT™ cell. This setup is comparable to a classical microarray with ZMWs in place of spots but unknown allocation of probes. The probe surface density is reduced by a factor of ~1010 allowing the study of hybridization in the absence of interactions with neighboring probes. Hybridization with a dye labelled oligonucleotide results in trains of fluorescence pulses from which interpulse durations (IPDs) and pulse widths (PWs) can be extracted. Since the identity of a probe in a ZMW is unknown, the immobilized oligonucleotide is sequenced in a subsequent step. After mapping the fluorescence traces to the sequence, the association and dissociation rate constant for each oligonucleotide can be calculated. By selecting suitable probes, the method can be used to determine rate constants of hybridization for a large number of mismatch oligonucleotides in a single measurement and at single-molecule level.

  13. MALDI imaging mass spectrometry reveals multiple clinically relevant masses in colorectal cancer using large-scale tissue microarrays.

    PubMed

    Hinsch, A; Buchholz, M; Odinga, S; Borkowski, C; Koop, C; Izbicki, J R; Wurlitzer, M; Krech, T; Wilczak, W; Steurer, S; Jacobsen, F; Burandt, E-C; Stahl, P; Simon, R; Sauter, G; Schlüter, H

    2017-03-01

    For identification of clinically relevant masses to predict status, grade, relapse and prognosis of colorectal cancer, we applied Matrix-assisted laser desorption ionization (MALDI) imaging mass spectrometry (IMS) to a tissue micro array containing formalin-fixed and paraffin-embedded tissue samples from 349 patients. Analysis of our MALDI-IMS data revealed 27 different m/z signals associated with epithelial structures. Comparison of these signals showed significant association with status, grade and Ki-67 labeling index. Fifteen out of 27 IMS signals revealed a significant association with survival. For seven signals (m/z 654, 776, 788, 904, 944, 975 and 1013) the absence and for eight signals (m/z 643, 678, 836, 886, 898, 1095, 1459 and 1477) the presence were associated with decreased life expectancy, including five masses (m/z 788, 836, 904, 944 and 1013) that provided prognostic information independently from the established prognosticators pT and pN. Combination of these five masses resulted in a three-step classifier that provided prognostic information superior to univariate analysis. In addition, a total of 19 masses were associated with tumor stage, grade, metastasis and cell proliferation. Our data demonstrate the suitability of combining IMS and large-scale tissue micro arrays to simultaneously identify and validate clinically useful molecular marker. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

  14. Crowdsourcing the General Public for Large Scale Molecular Pathology Studies in Cancer

    PubMed Central

    Candido dos Reis, Francisco J.; Lynn, Stuart; Ali, H. Raza; Eccles, Diana; Hanby, Andrew; Provenzano, Elena; Caldas, Carlos; Howat, William J.; McDuffus, Leigh-Anne; Liu, Bin; Daley, Frances; Coulson, Penny; Vyas, Rupesh J.; Harris, Leslie M.; Owens, Joanna M.; Carton, Amy F.M.; McQuillan, Janette P.; Paterson, Andy M.; Hirji, Zohra; Christie, Sarah K.; Holmes, Amber R.; Schmidt, Marjanka K.; Garcia-Closas, Montserrat; Easton, Douglas F.; Bolla, Manjeet K.; Wang, Qin; Benitez, Javier; Milne, Roger L.; Mannermaa, Arto; Couch, Fergus; Devilee, Peter; Tollenaar, Robert A.E.M.; Seynaeve, Caroline; Cox, Angela; Cross, Simon S.; Blows, Fiona M.; Sanders, Joyce; de Groot, Renate; Figueroa, Jonine; Sherman, Mark; Hooning, Maartje; Brenner, Hermann; Holleczek, Bernd; Stegmaier, Christa; Lintott, Chris; Pharoah, Paul D.P.

    2015-01-01

    Background Citizen science, scientific research conducted by non-specialists, has the potential to facilitate biomedical research using available large-scale data, however validating the results is challenging. The Cell Slider is a citizen science project that intends to share images from tumors with the general public, enabling them to score tumor markers independently through an internet-based interface. Methods From October 2012 to June 2014, 98,293 Citizen Scientists accessed the Cell Slider web page and scored 180,172 sub-images derived from images of 12,326 tissue microarray cores labeled for estrogen receptor (ER). We evaluated the accuracy of Citizen Scientist's ER classification, and the association between ER status and prognosis by comparing their test performance against trained pathologists. Findings The area under ROC curve was 0.95 (95% CI 0.94 to 0.96) for cancer cell identification and 0.97 (95% CI 0.96 to 0.97) for ER status. ER positive tumors scored by Citizen Scientists were associated with survival in a similar way to that scored by trained pathologists. Survival probability at 15 years were 0.78 (95% CI 0.76 to 0.80) for ER-positive and 0.72 (95% CI 0.68 to 0.77) for ER-negative tumors based on Citizen Scientists classification. Based on pathologist classification, survival probability was 0.79 (95% CI 0.77 to 0.81) for ER-positive and 0.71 (95% CI 0.67 to 0.74) for ER-negative tumors. The hazard ratio for death was 0.26 (95% CI 0.18 to 0.37) at diagnosis and became greater than one after 6.5 years of follow-up for ER scored by Citizen Scientists, and 0.24 (95% CI 0.18 to 0.33) at diagnosis increasing thereafter to one after 6.7 (95% CI 4.1 to 10.9) years of follow-up for ER scored by pathologists. Interpretation Crowdsourcing of the general public to classify cancer pathology data for research is viable, engages the public and provides accurate ER data. Crowdsourced classification of research data may offer a valid solution to problems of

  15. BAFF, APRIL, TWEAK, BCMA, TACI and Fn14 proteins are related to human glioma tumor grade: immunohistochemistry and public microarray data meta-analysis.

    PubMed

    Pelekanou, Vassiliki; Notas, George; Kampa, Marilena; Tsentelierou, Eleftheria; Stathopoulos, Efstathios N; Tsapis, Andreas; Castanas, Elias

    2013-01-01

    Gliomas are common and lethal tumors of the central nervous system (CNS). Genetic alterations, inflammatory and angiogenic processes have been identified throughout tumor progression; however, treatment still remains palliative for most cases. Biological research on parameters influencing cell survival, invasion and tumor heterogeneity identified several cytokines interfering in CNS inflammation, oxidative stress and malignant transformation, including TNF-superfamily (TNFSF) members. In this report we performed a meta-analysis of public gene-array data on the expression of a group of TNFSF ligands (BAFF, APRIL, TWEAK) and their receptors (BAFF-R, TACI, BCMA, Fn14) in gliomas. In addition, we investigated by immunohistochemistry (IHC) the tumor cells' expression of these ligands and receptors in a series of 56 gliomas of different grade. We show that in IHC, BAFF and APRIL as well as their cognate receptors (BCMA, TACI) and Fn14 expression correlate with tumor grade. This result was not evidenced in micro-arrays meta-analysis. Finally, we detected for the first time Fn14, BAFF, BCMA and TACI in glioma-related vascular endothelium. Our data, combined with our previous report in glioma cell lines, suggest a role for these receptors and ligands in glioma biology and advance these molecules as potential markers for the classification of these tumors to the proliferative, angiogenic or stem-like molecular subtype.

  16. Tissue microarrays in diffuse large B-cell lymphomas: are they really able to identify distinct prognostic groups in lymphomas of both nodal and extranodal origin?

    PubMed

    Laszlo, D; Pruneri, G; Andreola, G; Radice, D; Calabrese, L; Rafaniello, P R; Nassi, L; Sammassimo, S; Alietti, A; Agazzi, A; Vanazzi, A; Martinelli, G

    2011-08-01

    Diffuse large B-cell lymphomas (DLBCL) can be divided into different subgroups (germinal center B-cell-like [GCB] and non-GCB) according to their gene expression profiles. Immunohistochemistry has been proposed as a surrogate for identifying these subgroups, but data about its efficacy in providing prognostic information are conflicting. This study retrospectively analyzed a series of 105 DLBCL, defined as GCB and non-GCB according to CD10, bcl-6, and MUM1 expression. All patients received a first-line anthracycline-based (CHOP-like) chemotherapy. A total of 50 patients (48%) were identified as GCB and 55 (52%) as non-GCB. The overall response rate was 89% (94/105), with 62 (59%) complete response. Disease progressions were equally distributed between the 2 subgroups and were not significantly different (P = .756) considering the primary site of involvement (nodal or extranodal). The median follow-up was 62 months (range 5-126 months). Overall survival at 5 years was not significantly different between the groups (P = .3468) and was 72.3% and 66.6% for GCB and non-GCB, respectively. The results do not support the prognostic value of GCB and non-GCB immunohistochemical categories in DLBCL of both nodal and extranodal origin. Furthermore, a limited number of antigens may be not sufficient to identify the same patterns defined by cDNA microarray. Prospective studies are warranted to address this issue.

  17. Functional clustering and lineage markers: insights into cellular differentiation and gene function from large-scale microarray studies of purified primary cell populations.

    PubMed

    Hume, David A; Summers, Kim M; Raza, Sobia; Baillie, J Kenneth; Freeman, Thomas C

    2010-06-01

    Very large microarray datasets showing gene expression across multiple tissues and cell populations provide a window on the transcriptional networks that underpin the differences in functional activity between biological systems. Clusters of co-expressed genes provide lineage markers, candidate regulators of cell function and, by applying the principle of guilt by association, candidate functions for genes of currently unknown function. We have analysed a dataset comprising pure cell populations from hemopoietic and non-hemopoietic cell types (http://biogps.gnf.org). Using a novel network visualisation and clustering approach, we demonstrate that it is possible to identify very tight expression signatures associated specifically with embryonic stem cells, mesenchymal cells and hematopoietic lineages. Selected examples validate the prediction that gene function can be inferred by co-expression. One expression cluster was enriched in phagocytes, which, alongside endosome-lysosome constituents, contains genes that may make up a 'pathway' for phagocyte differentiation. Promoters of these genes are enriched for binding sites for the ETS/PU.1 and MITF families. Another cluster was associated with the production of a specific extracellular matrix, with high levels of gene expression shared by cells of mesenchymal origin (fibroblasts, adipocytes, osteoblasts and myoblasts). We discuss the limitations placed upon such data by the presence of alternative promoters with distinct tissue specificity within many protein-coding genes.

  18. Cross-platform analysis of cancer microarray data improves gene expression based classification of phenotypes

    PubMed Central

    Warnat, Patrick; Eils, Roland; Brors, Benedikt

    2005-01-01

    Background The extensive use of DNA microarray technology in the characterization of the cell transcriptome is leading to an ever increasing amount of microarray data from cancer studies. Although similar questions for the same type of cancer are addressed in these different studies, a comparative analysis of their results is hampered by the use of heterogeneous microarray platforms and analysis methods. Results In contrast to a meta-analysis approach where results of different studies are combined on an interpretative level, we investigate here how to directly integrate raw microarray data from different studies for the purpose of supervised classification analysis. We use median rank scores and quantile discretization to derive numerically comparable measures of gene expression from different platforms. These transformed data are then used for training of classifiers based on support vector machines. We apply this approach to six publicly available cancer microarray gene expression data sets, which consist of three pairs of studies, each examining the same type of cancer, i.e. breast cancer, prostate cancer or acute myeloid leukemia. For each pair, one study was performed by means of cDNA microarrays and the other by means of oligonucleotide microarrays. In each pair, high classification accuracies (> 85%) were achieved with training and testing on data instances randomly chosen from both data sets in a cross-validation analysis. To exemplify the potential of this cross-platform classification analysis, we use two leukemia microarray data sets to show that important genes with regard to the biology of leukemia are selected in an integrated analysis, which are missed in either single-set analysis. Conclusion Cross-platform classification of multiple cancer microarray data sets yields discriminative gene expression signatures that are found and validated on a large number of microarray samples, generated by different laboratories and microarray technologies

  19. Chemistry of Natural Glycan Microarray

    PubMed Central

    Song, Xuezheng; Heimburg-Molinaro, Jamie; Cummings, Richard D.; Smith, David F.

    2014-01-01

    Glycan microarrays have become indispensable tools for studying protein-glycan interactions. Along with chemo-enzymatic synthesis, glycans isolated from natural sources have played important roles in array development and will continue to be a major source of glycans. N- and O-glycans from glycoproteins, and glycans from glycosphingolipids can be released from corresponding glycoconjugates with relatively mature methods, although isolation of large numbers and quantities of glycans are still very challenging. Glycosylphosphatidylinositol (GPI)-anchors and glycosaminoglycans (GAGs) are less represented on current glycan microarrays. Glycan microarray development has been greatly facilitated by bifunctional fluorescent linkers, which can be applied in a “Shotgun Glycomics” approach to incorporate isolated natural glycans. Glycan presentation on microarrays may affect glycan binding by GBPs, often through multivalent recognition by the GBP. PMID:24487062

  20. Unconventional microarray design reveals the response to obesity is largely tissue specific: analysis of common and divergent responses to diet-induced obesity in insulin-sensitive tissues.

    PubMed

    Lee, Robyn K; Hittel, Dustin S; Nyamandi, Vongai Z; Kang, Li; Soh, Jung; Sensen, Christoph W; Shearer, Jane

    2012-04-01

    Obesity is a chronic condition involving the excessive accumulation of adipose tissue that adversely affects all systems in the body. The aim of the present study was to employ an unbiased, genome-wide assessment of transcript abundance in order to identify common gene expression pathways within insulin-sensitive tissues in response to dietary-induced diabetes. Following 20 weeks of chow or high-fat feeding (60% kcal), age-matched mice underwent a euglycemic-hyperinsulinemic clamp to assess insulin sensitivity. High-fat-fed animals were obese and highly insulin resistant, disposing of ∼75% less glucose compared with their chow-fed counterparts. Tissues were collected, and gene expression was examined by microarray in 4 tissues known to exhibit obesity-related metabolic disturbances: white adipose tissue, skeletal muscle, liver, and heart. A total of 463 genes were differentially expressed between diets. Analysis of individual tissues showed skeletal muscle to exhibit the largest number of differentially expressed genes (191) in response to high-fat feeding, followed by adipose tissue (169), liver (115), and heart (65). Analyses revealed that the response of individual genes to obesity is distinct and largely tissue specific, with less than 10% of transcripts being shared among tissues. Although transcripts are largely tissue specific, a systems approach shows numerous commonly activated pathways, including those involved in signal transduction, inflammation, oxidative stress, substrate transport, and metabolism. This suggests a coordinated attempt by tissues to limit metabolic perturbations occurring in early-stage obesity. Many identified genes were associated with a variety of disorders, thereby serving as potential links between obesity and its related health risks.

  1. The Current Status of DNA Microarrays

    NASA Astrophysics Data System (ADS)

    Shi, Leming; Perkins, Roger G.; Tong, Weida

    DNA microarray technology that allows simultaneous assay of thousands of genes in a single experiment has steadily advanced to become a mainstream method used in research, and has reached a stage that envisions its use in medical applications and personalized medicine. Many different strategies have been developed for manufacturing DNA microarrays. In this chapter, we discuss the manufacturing characteristics of seven microarray platforms that were used in a recently completed large study by the MicroArray Quality Control (MAQC) consortium, which evaluated the concordance of results across these platforms. The platforms can be grouped into three categories: (1) in situ synthesis of oligonucleotide probes on microarrays (Affymetrix GeneChip® arrays based on photolithography synthesis and Agilent's arrays based on inkjet synthesis); (2) spotting of presynthesized oligonucleotide probes on microarrays (GE Healthcare's CodeLink system, Applied Biosystems' Genome Survey Microarrays, and the custom microarrays printed with Operon's oligonucleotide set); and (3) deposition of presynthesized oligonucleotide probes on bead-based microarrays (Illumina's BeadChip microarrays). We conclude this chapter with our views on the challenges and opportunities toward acceptance of DNA microarray data in clinical and regulatory settings.

  2. The Current Status of DNA Microarrays

    NASA Astrophysics Data System (ADS)

    Shi, Leming; Perkins, Roger G.; Tong, Weida

    DNA microarray technology that allows simultaneous assay of thousands of genes in a single experiment has steadily advanced to become a mainstream method used in research, and has reached a stage that envisions its use in medical applications and personalized medicine. Many different strategies have been developed for manufacturing DNA microarrays. In this chapter, we discuss the manu facturing characteristics of seven microarray platforms that were used in a recently completed large study by the MicroArray Quality Control (MAQC) consortium, which evaluated the concordance of results across these platforms. The platforms can be grouped into three categories: (1) in situ synthesis of oligonucleotide probes on microarrays (Affymetrix GeneChip® arrays based on photolithography synthesis and Agilent's arrays based on inkjet synthesis); (2) spotting of presynthe-sized oligonucleotide probes on microarrays (GE Healthcare's CodeLink system, Applied Biosystems' Genome Survey Microarrays, and the custom microarrays printed with Operon's oligonucleotide set); and (3) deposition of presynthesized oligonucleotide probes on bead-based microarrays (Illumina's BeadChip microar-rays). We conclude this chapter with our views on the challenges and opportunities toward acceptance of DNA microarray data in clinical and regulatory settings.

  3. A Microarray Platform-Independent Classification Tool for Cell of Origin Class Allows Comparative Analysis of Gene Expression in Diffuse Large B-cell Lymphoma

    PubMed Central

    Care, Matthew A.; Barrans, Sharon; Worrillow, Lisa; Jack, Andrew; Westhead, David R.; Tooze, Reuben M.

    2013-01-01

    Cell of origin classification of diffuse large B-cell lymphoma (DLBCL) identifies subsets with biological and clinical significance. Despite the established nature of the classification existing studies display variability in classifier implementation, and a comparative analysis across multiple data sets is lacking. Here we describe the validation of a cell of origin classifier for DLBCL, based on balanced voting between 4 machine-learning tools: the DLBCL automatic classifier (DAC). This shows superior survival separation for assigned Activated B-cell (ABC) and Germinal Center B-cell (GCB) DLBCL classes relative to a range of other classifiers. DAC is effective on data derived from multiple microarray platforms and formalin fixed paraffin embedded samples and is parsimonious, using 20 classifier genes. We use DAC to perform a comparative analysis of gene expression in 10 data sets (2030 cases). We generate ranked meta-profiles of genes showing consistent class-association using ≥6 data sets as a cut-off: ABC (414 genes) and GCB (415 genes). The transcription factor ZBTB32 emerges as the most consistent and differentially expressed gene in ABC-DLBCL while other transcription factors such as ARID3A, BATF, and TCF4 are also amongst the 24 genes associated with this class in all datasets. Analysis of enrichment of 12323 gene signatures against meta-profiles and all data sets individually confirms consistent associations with signatures of molecular pathways, chromosomal cytobands, and transcription factor binding sites. We provide DAC as an open access Windows application, and the accompanying meta-analyses as a resource. PMID:23424639

  4. Centralization and Decentralization of Large Public School Districts.

    ERIC Educational Resources Information Center

    Ornstein, Allan C.

    1989-01-01

    A ratio comparing the number of administrators in central offices with those outside central offices was used nationwide in 1988 to assess decentralization in large school districts. Sixteen of 62 districts were decentralized. The same survey in 1980 revealed 39 of 65 districts were decentralized. Decentralization is decreasing as an…

  5. Managing the Editing Function on Large Publication Tasks with Short Flow Times.

    ERIC Educational Resources Information Center

    Santa, Terry M. Dalla

    Large publication tasks with short flow times require that several editors be assigned to work together as part of a larger publication team that includes management, engineer-writers, publishing logistics personnel, word processor operators, illustrators, and printers. Team-edited publications have special problems, and the technical editing and…

  6. Managing the Editing Function on Large Publication Tasks with Short Flow Times.

    ERIC Educational Resources Information Center

    Santa, Terry M. Dalla

    Large publication tasks with short flow times require that several editors be assigned to work together as part of a larger publication team that includes management, engineer-writers, publishing logistics personnel, word processor operators, illustrators, and printers. Team-edited publications have special problems, and the technical editing and…

  7. Identification of potential biomarkers from microarray experiments using multiple criteria optimization.

    PubMed

    Sánchez-Peña, Matilde L; Isaza, Clara E; Pérez-Morales, Jaileene; Rodríguez-Padilla, Cristina; Castro, José M; Cabrera-Ríos, Mauricio

    2013-04-01

    Microarray experiments are capable of determining the relative expression of tens of thousands of genes simultaneously, thus resulting in very large databases. The analysis of these databases and the extraction of biologically relevant knowledge from them are challenging tasks. The identification of potential cancer biomarker genes is one of the most important aims for microarray analysis and, as such, has been widely targeted in the literature. However, identifying a set of these genes consistently across different experiments, researches, microarray platforms, or cancer types is still an elusive endeavor. Besides the inherent difficulty of the large and nonconstant variability in these experiments and the incommensurability between different microarray technologies, there is the issue of the users having to adjust a series of parameters that significantly affect the outcome of the analyses and that do not have a biological or medical meaning. In this study, the identification of potential cancer biomarkers from microarray data is casted as a multiple criteria optimization (MCO) problem. The efficient solutions to this problem, found here through data envelopment analysis (DEA), are associated to genes that are proposed as potential cancer biomarkers. The method does not require any parameter adjustment by the user, and thus fosters repeatability. The approach also allows the analysis of different microarray experiments, microarray platforms, and cancer types simultaneously. The results include the analysis of three publicly available microarray databases related to cervix cancer. This study points to the feasibility of modeling the selection of potential cancer biomarkers from microarray data as an MCO problem and solve it using DEA. Using MCO entails a new optic to the identification of potential cancer biomarkers as it does not require the definition of a threshold value to establish significance for a particular gene and the selection of a normalization

  8. 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

  9. Comparing Bacterial DNA Microarray Fingerprints

    SciTech Connect

    Willse, Alan R.; Chandler, Darrell P.; White, Amanda M.; Protic, Miroslava; Daly, Don S.; Wunschel, Sharon C.

    2005-08-15

    Detecting subtle genetic differences between microorganisms is an important problem in molecular epidemiology and microbial forensics. In a typical investigation, gel electrophoresis is used to compare randomly amplified DNA fragments between microbial strains, where the patterns of DNA fragment sizes are proxies for a microbe's genotype. The limited genomic sample captured on a gel is often insufficient to discriminate nearly identical strains. This paper examines the application of microarray technology to DNA fingerprinting as a high-resolution alternative to gel-based methods. The so-called universal microarray, which uses short oligonucleotide probes that do not target specific genes or species, is intended to be applicable to all microorganisms because it does not require prior knowledge of genomic sequence. In principle, closely related strains can be distinguished if the number of probes on the microarray is sufficiently large, i.e., if the genome is sufficiently sampled. In practice, we confront noisy data, imperfectly matched hybridizations, and a high-dimensional inference problem. We describe the statistical problems of microarray fingerprinting, outline similarities with and differences from more conventional microarray applications, and illustrate the statistical fingerprinting problem for 10 closely related strains from three Bacillus species, and 3 strains from non-Bacillus species.

  10. Analysis of DNA microarray expression data.

    PubMed

    Simon, Richard

    2009-06-01

    DNA microarrays are powerful tools for studying biological mechanisms and for developing prognostic and predictive classifiers for identifying the patients who require treatment and are best candidates for specific treatments. Because microarrays produce so much data from each specimen, they offer great opportunities for discovery and great dangers or producing misleading claims. Microarray based studies require clear objectives for selecting cases and appropriate analysis methods. Effective analysis of microarray data, where the number of measured variables is orders of magnitude greater than the number of cases, requires specialized statistical methods which have recently been developed. Recent literature reviews indicate that serious problems of analysis exist a substantial proportion of publications. This manuscript attempts to provide a non-technical summary of the key principles of statistical design and analysis for studies that utilize microarray expression profiling.

  11. Strategy for the design of custom cDNA microarrays.

    PubMed

    Lorenz, Matthias G O; Cortes, Lizette M; Lorenz, Juergen J; Liu, Edison T

    2003-06-01

    DNA microarrays are valuable but expensive tools for expression profiling of cells, tissues, and organs. The design of custom microarrays leads to cost reduction without necessarily compromising their biological value. Here we present a strategy for designing custom cDNA microarrays and constructed a microarray for mouse immunology research (ImmunoChip). The strategy used interrogates expressed sequence tag databases available in the public domain but overcomes many of the problems encountered. Immunologically relevant clusters were selected based on the expression of expressed sequence tags in relevant libraries. Selected clusters were organized in modules, and the best representative clones were identified. When tested, this microarray was found to have minimal clone identity errors or phage contamination and identified molecular signatures of lymphoid cell lines. Our proposed design of custom microarrays avoids probe redundancy, allows the organization of the chip to optimize chip production, and reduces microarray production costs. The strategy described is also useful for the design of oligonucleotide microarrays.

  12. Living-cell microarrays.

    PubMed

    Yarmush, Martin L; King, Kevin R

    2009-01-01

    Living cells are remarkably complex. To unravel this complexity, living-cell assays have been developed that allow delivery of experimental stimuli and measurement of the resulting cellular responses. High-throughput adaptations of these assays, known as living-cell microarrays, which are based on microtiter plates, high-density spotting, microfabrication, and microfluidics technologies, are being developed for two general applications: (a) to screen large-scale chemical and genomic libraries and (b) to systematically investigate the local cellular microenvironment. These emerging experimental platforms offer exciting opportunities to rapidly identify genetic determinants of disease, to discover modulators of cellular function, and to probe the complex and dynamic relationships between cells and their local environment.

  13. Overview of Protein Microarrays

    PubMed Central

    Reymond Sutandy, FX; Qian, Jiang; Chen, Chien-Sheng; Zhu, Heng

    2013-01-01

    Protein microarray is an emerging technology that provides a versatile platform for characterization of hundreds of thousands of proteins in a highly parallel and high-throughput way. Two major classes of protein microarrays are defined to describe their applications: analytical and functional protein microarrays. In addition, tissue or cell lysates can also be fractionated and spotted on a slide to form a reverse-phase protein microarray. While the fabrication technology is maturing, applications of protein microarrays, especially functional protein microarrays, have flourished during the past decade. Here, we will first review recent advances in the protein microarray technologies, and then present a series of examples to illustrate the applications of analytical and functional protein microarrays in both basic and clinical research. The research areas will include detection of various binding properties of proteins, study of protein posttranslational modifications, analysis of host-microbe interactions, profiling antibody specificity, and identification of biomarkers in autoimmune diseases. As a powerful technology platform, it would not be surprising if protein microarrays will become one of the leading technologies in proteomic and diagnostic fields in the next decade. PMID:23546620

  14. MARS: Microarray analysis, retrieval, and storage system

    PubMed Central

    Maurer, Michael; Molidor, Robert; Sturn, Alexander; Hartler, Juergen; Hackl, Hubert; Stocker, Gernot; Prokesch, Andreas; Scheideler, Marcel; Trajanoski, Zlatko

    2005-01-01

    Background Microarray analysis has become a widely used technique for the study of gene-expression patterns on a genomic scale. As more and more laboratories are adopting microarray technology, there is a need for powerful and easy to use microarray databases facilitating array fabrication, labeling, hybridization, and data analysis. The wealth of data generated by this high throughput approach renders adequate database and analysis tools crucial for the pursuit of insights into the transcriptomic behavior of cells. Results MARS (Microarray Analysis and Retrieval System) provides a comprehensive MIAME supportive suite for storing, retrieving, and analyzing multi color microarray data. The system comprises a laboratory information management system (LIMS), a quality control management, as well as a sophisticated user management system. MARS is fully integrated into an analytical pipeline of microarray image analysis, normalization, gene expression clustering, and mapping of gene expression data onto biological pathways. The incorporation of ontologies and the use of MAGE-ML enables an export of studies stored in MARS to public repositories and other databases accepting these documents. Conclusion We have developed an integrated system tailored to serve the specific needs of microarray based research projects using a unique fusion of Web based and standalone applications connected to the latest J2EE application server technology. The presented system is freely available for academic and non-profit institutions. More information can be found at . PMID:15836795

  15. PMD: A Resource for Archiving and Analyzing Protein Microarray data

    PubMed Central

    Xu, Zhaowei; Huang, Likun; Zhang, Hainan; Li, Yang; Guo, Shujuan; Wang, Nan; Wang, Shi-hua; Chen, Ziqing; Wang, Jingfang; Tao, Sheng-ce

    2016-01-01

    Protein microarray is a powerful technology for both basic research and clinical study. However, because there is no database specifically tailored for protein microarray, the majority of the valuable original protein microarray data is still not publically accessible. To address this issue, we constructed Protein Microarray Database (PMD), which is specifically designed for archiving and analyzing protein microarray data. In PMD, users can easily browse and search the entire database by experimental name, protein microarray type, and sample information. Additionally, PMD integrates several data analysis tools and provides an automated data analysis pipeline for users. With just one click, users can obtain a comprehensive analysis report for their protein microarray data. The report includes preliminary data analysis, such as data normalization, candidate identification, and an in-depth bioinformatics analysis of the candidates, which include functional annotation, pathway analysis, and protein-protein interaction network analysis. PMD is now freely available at www.proteinmicroarray.cn. PMID:26813635

  16. PMD: A Resource for Archiving and Analyzing Protein Microarray data.

    PubMed

    Xu, Zhaowei; Huang, Likun; Zhang, Hainan; Li, Yang; Guo, Shujuan; Wang, Nan; Wang, Shi-Hua; Chen, Ziqing; Wang, Jingfang; Tao, Sheng-Ce

    2016-01-27

    Protein microarray is a powerful technology for both basic research and clinical study. However, because there is no database specifically tailored for protein microarray, the majority of the valuable original protein microarray data is still not publically accessible. To address this issue, we constructed Protein Microarray Database (PMD), which is specifically designed for archiving and analyzing protein microarray data. In PMD, users can easily browse and search the entire database by experimental name, protein microarray type, and sample information. Additionally, PMD integrates several data analysis tools and provides an automated data analysis pipeline for users. With just one click, users can obtain a comprehensive analysis report for their protein microarray data. The report includes preliminary data analysis, such as data normalization, candidate identification, and an in-depth bioinformatics analysis of the candidates, which include functional annotation, pathway analysis, and protein-protein interaction network analysis. PMD is now freely available at www.proteinmicroarray.cn.

  17. CD14 and Complement Crosstalk and Largely Mediate the Transcriptional Response to Escherichia coli in Human Whole Blood as Revealed by DNA Microarray

    PubMed Central

    Lau, Corinna; Nygård, Ståle; Fure, Hilde; Olstad, Ole Kristoffer; Holden, Marit; Lappegård, Knut Tore; Brekke, Ole-Lars; Espevik, Terje; Hovig, Eivind; Mollnes, Tom Eirik

    2015-01-01

    Systemic inflammation like in sepsis is still lacking specific diagnostic markers and effective therapeutics. The first line of defense against intruding pathogens and endogenous damage signals is pattern recognition by e.g., complement and Toll-like receptors (TLR). Combined inhibition of a key complement component (C3 and C5) and TLR-co-receptor CD14 has been shown to attenuate certain systemic inflammatory responses. Using DNA microarray and gene annotation analyses, we aimed to decipher the effect of combined inhibition of C3 and CD14 on the transcriptional response to bacterial challenge in human whole blood. Importantly, combined inhibition reversed the transcriptional changes of 70% of the 2335 genes which significantly responded to heat-inactivated Escherichia coli by on average 80%. Single inhibition was less efficient (p<0.001) but revealed a suppressive effect of C3 on 21% of the responding genes which was partially counteracted by CD14. Furthermore, CD14 dependency of the Escherichia coli-induced response was increased in C5-deficient compared to C5-sufficient blood. The observed crucial distinct and synergistic roles for complement and CD14 on the transcriptional level correspond to their broad impact on the inflammatory response in human blood, and their combined inhibition may become inevitable in the early treatment of acute systemic inflammation. PMID:25706641

  18. DNA microarray technology in dermatology.

    PubMed

    Kunz, Manfred

    2008-03-01

    In recent years, DNA microarray technology has been used for the analysis of gene expression patterns in a variety of skin diseases, including malignant melanoma, psoriasis, lupus erythematosus, and systemic sclerosis. Many of the studies described herein confirmed earlier results on individual genes or functional groups of genes. However, a plethora of new candidate genes, gene patterns, and regulatory pathways have been identified. Major progresses were reached by the identification of a prognostic gene pattern in malignant melanoma, an immune signaling cluster in psoriasis, and a so-called interferon signature in systemic lupus erythematosus. In future, interference with genes or regulatory pathways with the use of different RNA interference technologies or targeted therapy may not only underscore the functional significance of microarray data but also may open interesting therapeutic perspectives. Large-scale gene expression analyses may also help to design more individualized treatment approaches of cutaneous diseases.

  19. Microarray in parasitic infections

    PubMed Central

    Sehgal, Rakesh; Misra, Shubham; Anand, Namrata; Sharma, Monika

    2012-01-01

    Modern biology and genomic sciences are rooted in parasitic disease research. Genome sequencing efforts have provided a wealth of new biological information that promises to have a major impact on our understanding of parasites. Microarrays provide one of the major high-throughput platforms by which this information can be exploited in the laboratory. Many excellent reviews and technique articles have recently been published on applying microarrays to organisms for which fully annotated genomes are at hand. However, many parasitologists work on organisms whose genomes have been only partially sequenced. This review is mainly focused on how to use microarray in these situations. PMID:23508469

  20. Conifer defence against insects: microarray gene expression profiling of Sitka spruce (Picea sitchensis) induced by mechanical wounding or feeding by spruce budworms (Choristoneura occidentalis) or white pine weevils (Pissodes strobi) reveals large-scale changes of the host transcriptome.

    PubMed

    Ralph, Steven G; Yueh, Hesther; Friedmann, Michael; Aeschliman, Dana; Zeznik, Jeffrey A; Nelson, Colleen C; Butterfield, Yaron S N; Kirkpatrick, Robert; Liu, Jerry; Jones, Steven J M; Marra, Marco A; Douglas, Carl J; Ritland, Kermit; Bohlmann, Jörg

    2006-08-01

    Conifers are resistant to attack from a large number of potential herbivores or pathogens. Previous molecular and biochemical characterization of selected conifer defence systems support a model of multigenic, constitutive and induced defences that act on invading insects via physical, chemical, biochemical or ecological (multitrophic) mechanisms. However, the genomic foundation of the complex defence and resistance mechanisms of conifers is largely unknown. As part of a genomics strategy to characterize inducible defences and possible resistance mechanisms of conifers against insect herbivory, we developed a cDNA microarray building upon a new spruce (Picea spp.) expressed sequence tag resource. This first-generation spruce cDNA microarray contains 9720 cDNA elements representing c. 5500 unique genes. We used this array to monitor gene expression in Sitka spruce (Picea sitchensis) bark in response to herbivory by white pine weevils (Pissodes strobi, Curculionidae) or wounding, and in young shoot tips in response to western spruce budworm (Choristoneura occidentalis, Lepidopterae) feeding. Weevils are stem-boring insects that feed on phloem, while budworms are foliage feeding larvae that consume needles and young shoot tips. Both insect species and wounding treatment caused substantial changes of the host plant transcriptome detected in each case by differential gene expression of several thousand array elements at 1 or 2 d after the onset of treatment. Overall, there was considerable overlap among differentially expressed gene sets from these three stress treatments. Functional classification of the induced transcripts revealed genes with roles in general plant defence, octadecanoid and ethylene signalling, transport, secondary metabolism, and transcriptional regulation. Several genes involved in primary metabolic processes such as photosynthesis were down-regulated upon insect feeding or wounding, fitting with the concept of dynamic resource allocation in plant

  1. Association analyses of large-scale glycan microarray data reveal novel host-specific substructures in influenza A virus binding glycans

    NASA Astrophysics Data System (ADS)

    Zhao, Nan; Martin, Brigitte E.; Yang, Chun-Kai; Luo, Feng; Wan, Xiu-Feng

    2015-10-01

    Influenza A viruses can infect a wide variety of animal species and, occasionally, humans. Infection occurs through the binding formed by viral surface glycoprotein hemagglutinin and certain types of glycan receptors on host cell membranes. Studies have shown that the α2,3-linked sialic acid motif (SA2,3Gal) in avian, equine, and canine species; the α2,6-linked sialic acid motif (SA2,6Gal) in humans; and SA2,3Gal and SA2,6Gal in swine are responsible for the corresponding host tropisms. However, more detailed and refined substructures that determine host tropisms are still not clear. Thus, in this study, we applied association mining on a set of glycan microarray data for 211 influenza viruses from five host groups: humans, swine, canine, migratory waterfowl, and terrestrial birds. The results suggest that besides Neu5Acα2-6Galβ, human-origin viruses could bind glycans with Neu5Acα2-8Neu5Acα2-8Neu5Ac and Neu5Gcα2-6Galβ1-4GlcNAc substructures; Galβ and GlcNAcβ terminal substructures, without sialic acid branches, were associated with the binding of human-, swine-, and avian-origin viruses; sulfated Neu5Acα2-3 substructures were associated with the binding of human- and swine-origin viruses. Finally, through three-dimensional structure characterization, we revealed that the role of glycan chain shapes is more important than that of torsion angles or of overall structural similarities in virus host tropisms.

  2. A Seven-Marker Signature and Clinical Outcome in Malignant Melanoma: A Large-Scale Tissue-Microarray Study with Two Independent Patient Cohorts

    PubMed Central

    Bosserhoff, Anja K.; Hofstädter, Ferdinand; Pauer, Armin; Roth, Volker; Buhmann, Joachim M.; Moll, Ingrid; Anagnostou, Nikos; Brandner, Johanna M.; Ikenberg, Kristian; Moch, Holger; Landthaler, Michael; Vogt, Thomas; Wild, Peter J.

    2012-01-01

    Background Current staging methods such as tumor thickness, ulceration and invasion of the sentinel node are known to be prognostic parameters in patients with malignant melanoma (MM). However, predictive molecular marker profiles for risk stratification and therapy optimization are not yet available for routine clinical assessment. Methods and Findings Using tissue microarrays, we retrospectively analyzed samples from 364 patients with primary MM. We investigated a panel of 70 immunohistochemical (IHC) antibodies for cell cycle, apoptosis, DNA mismatch repair, differentiation, proliferation, cell adhesion, signaling and metabolism. A marker selection procedure based on univariate Cox regression and multiple testing correction was employed to correlate the IHC expression data with the clinical follow-up (overall and recurrence-free survival). The model was thoroughly evaluated with two different cross validation experiments, a permutation test and a multivariate Cox regression analysis. In addition, the predictive power of the identified marker signature was validated on a second independent external test cohort (n = 225). A signature of seven biomarkers (Bax, Bcl-X, PTEN, COX-2, loss of β-Catenin, loss of MTAP, and presence of CD20 positive B-lymphocytes) was found to be an independent negative predictor for overall and recurrence-free survival in patients with MM. The seven-marker signature could also predict a high risk of disease recurrence in patients with localized primary MM stage pT1-2 (tumor thickness ≤2.00 mm). In particular, three of these markers (MTAP, COX-2, Bcl-X) were shown to offer direct therapeutic implications. Conclusions The seven-marker signature might serve as a prognostic tool enabling physicians to selectively triage, at the time of diagnosis, the subset of high recurrence risk stage I–II patients for adjuvant therapy. Selective treatment of those patients that are more likely to develop distant metastatic disease could

  3. Association analyses of large-scale glycan microarray data reveal novel host-specific substructures in influenza A virus binding glycans

    PubMed Central

    Zhao, Nan; Martin, Brigitte E.; Yang, Chun-Kai; Luo, Feng; Wan, Xiu-Feng

    2015-01-01

    Influenza A viruses can infect a wide variety of animal species and, occasionally, humans. Infection occurs through the binding formed by viral surface glycoprotein hemagglutinin and certain types of glycan receptors on host cell membranes. Studies have shown that the α2,3-linked sialic acid motif (SA2,3Gal) in avian, equine, and canine species; the α2,6-linked sialic acid motif (SA2,6Gal) in humans; and SA2,3Gal and SA2,6Gal in swine are responsible for the corresponding host tropisms. However, more detailed and refined substructures that determine host tropisms are still not clear. Thus, in this study, we applied association mining on a set of glycan microarray data for 211 influenza viruses from five host groups: humans, swine, canine, migratory waterfowl, and terrestrial birds. The results suggest that besides Neu5Acα2–6Galβ, human-origin viruses could bind glycans with Neu5Acα2–8Neu5Acα2–8Neu5Ac and Neu5Gcα2–6Galβ1–4GlcNAc substructures; Galβ and GlcNAcβ terminal substructures, without sialic acid branches, were associated with the binding of human-, swine-, and avian-origin viruses; sulfated Neu5Acα2–3 substructures were associated with the binding of human- and swine-origin viruses. Finally, through three-dimensional structure characterization, we revealed that the role of glycan chain shapes is more important than that of torsion angles or of overall structural similarities in virus host tropisms. PMID:26508590

  4. Keeping Campus Visits Attuned to Change: The Experience at a Large Public University

    ERIC Educational Resources Information Center

    Head, Joe F.; Dunagan, Margaret W.; Hughes, Thomas M.

    2010-01-01

    Many factors affect an institution's ability to provide campus visitors a high-quality experience: traffic, parking deterrents, street people, navigation mazes, concrete facades, and political agendas, among others. These challenges can be particularly significant for large public, metro, or suburban institutions. Changes as simple as the…

  5. A Case Study Examining the Career Academy Model at a Large Urban Public High School

    ERIC Educational Resources Information Center

    Ho, Howard

    2013-01-01

    This study focused on how career academies were implemented at a large, urban, public high school. Research shows that the career academy model should consist of 3 core components: (a) a small learning community (SLC), (b) a theme-based curriculum, and (c) business partnerships (Stern, Dayton, & Raby, 2010). The purpose of this qualitative…

  6. Public health response to a measles outbreak in a large correctional facility, Queensland, 2013.

    PubMed

    Chatterji, Madhumati; Baldwin, Anne M; Prakash, Rajendra; Vlack, Susan A; Lambert, Stephen B

    2014-12-31

    This report documents the prompt, co-ordinated and effective public health response to a measles outbreak in Queensland in 2013. There were 17 cases in a large, high-security, regional correctional facility, a setting with unique challenges. Recommendations are provided to reduce the likelihood and magnitude of measles outbreaks in correctional facilities.

  7. Keeping Campus Visits Attuned to Change: The Experience at a Large Public University

    ERIC Educational Resources Information Center

    Head, Joe F.; Dunagan, Margaret W.; Hughes, Thomas M.

    2010-01-01

    Many factors affect an institution's ability to provide campus visitors a high-quality experience: traffic, parking deterrents, street people, navigation mazes, concrete facades, and political agendas, among others. These challenges can be particularly significant for large public, metro, or suburban institutions. Changes as simple as the…

  8. Assessing Large-Scale Public Job Creation. R&D Monograph 67.

    ERIC Educational Resources Information Center

    Employment and Training Administration (DOL), Washington, DC.

    To assess the feasibility of large-scale, countercyclical public job creation, a study was initiated. Job creation program activities were examined in terms of how many activities could be undertaken; what would be their costs; and what would be their characteristics (labor-intensity, skill-mix, and political acceptability) that might contribute…

  9. A Case Study Examining the Career Academy Model at a Large Urban Public High School

    ERIC Educational Resources Information Center

    Ho, Howard

    2013-01-01

    This study focused on how career academies were implemented at a large, urban, public high school. Research shows that the career academy model should consist of 3 core components: (a) a small learning community (SLC), (b) a theme-based curriculum, and (c) business partnerships (Stern, Dayton, & Raby, 2010). The purpose of this qualitative…

  10. Evaluation of Large-Scale Public-Sector Reforms: A Comparative Analysis

    ERIC Educational Resources Information Center

    Breidahl, Karen N.; Gjelstrup, Gunnar; Hansen, Hanne Foss; Hansen, Morten Balle

    2017-01-01

    Research on the evaluation of large-scale public-sector reforms is rare. This article sets out to fill that gap in the evaluation literature and argues that it is of vital importance since the impact of such reforms is considerable and they change the context in which evaluations of other and more delimited policy areas take place. In our…

  11. Case Study of a Secondary Online Program in a Large, Diverse Midwestern Public School District

    ERIC Educational Resources Information Center

    Cruzan, Carla Dale

    2010-01-01

    In a time of growth in secondary education online programs, there have been few studies directed at understanding secondary online programs and the students they serve. That is particularly true for large, inner-city public school districts with a diverse student body. This is a mixed methods case study which identified that students' primary…

  12. DNA Microarray Technology

    SciTech Connect

    WERNER-WASHBURNE, MARGARET; DAVIDSON, GEORGE S.

    2002-01-01

    Collaboration between Sandia National Laboratories and the University of New Mexico Biology Department resulted in the capability to train students in microarray techniques and the interpretation of data from microarray experiments. These studies provide for a better understanding of the role of stationary phase and the gene regulation involved in exit from stationary phase, which may eventually have important clinical implications. Importantly, this research trained numerous students and is the basis for three new Ph.D. projects.

  13. Public attitudes toward programs of large-scale technological changes: Some reflections and policy prescriptions, appendix E

    NASA Technical Reports Server (NTRS)

    Shostak, A. B.

    1973-01-01

    The question of how ready the public is for the implementation of large-scale programs of technological change is considered. Four vital aspects of the issue are discussed which include: (1) the ways in which the public mis-perceives the change process, (2) the ways in which recent history impacts on public attitudes, (3) the ways in which the public divides among itself, and (4) the fundamentals of public attitudes towards change. It is concluded that nothing is so critical in the 1970's to securing public approval for large-scale planned change projects as is securing the approval by change-agents of the public.

  14. Public attitudes toward programs of large-scale technological changes: Some reflections and policy prescriptions, appendix E

    NASA Technical Reports Server (NTRS)

    Shostak, A. B.

    1973-01-01

    The question of how ready the public is for the implementation of large-scale programs of technological change is considered. Four vital aspects of the issue are discussed which include: (1) the ways in which the public mis-perceives the change process, (2) the ways in which recent history impacts on public attitudes, (3) the ways in which the public divides among itself, and (4) the fundamentals of public attitudes towards change. It is concluded that nothing is so critical in the 1970's to securing public approval for large-scale planned change projects as is securing the approval by change-agents of the public.

  15. Transcriptome of Cultured Lung Fibroblasts in Idiopathic Pulmonary Fibrosis: Meta-Analysis of Publically Available Microarray Datasets Reveals Repression of Inflammation and Immunity Pathways

    PubMed Central

    Plantier, Laurent; Renaud, Hélène; Respaud, Renaud; Marchand-Adam, Sylvain; Crestani, Bruno

    2016-01-01

    Heritable profibrotic differentiation of lung fibroblasts is a key mechanism of idiopathic pulmonary fibrosis (IPF). Its mechanisms are yet to be fully understood. In this study, individual data from four independent microarray studies comparing the transcriptome of fibroblasts cultured in vitro from normal (total n = 20) and IPF (total n = 20) human lung were compiled for meta-analysis following normalization to z-scores. One hundred and thirteen transcripts were upregulated and 115 were downregulated in IPF fibroblasts using the Significance Analysis of Microrrays algorithm with a false discovery rate of 5%. Downregulated genes were highly enriched for Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional classes related to inflammation and immunity such as Defense response to virus, Influenza A, tumor necrosis factor (TNF) mediated signaling pathway, interferon-inducible absent in melanoma2 (AIM2) inflammasome as well as Apoptosis. Although upregulated genes were not enriched for any functional class, select factors known to play key roles in lung fibrogenesis were overexpressed in IPF fibroblasts, most notably connective tissue growth factor (CTGF) and serum response factor (SRF), supporting their role as drivers of IPF. The full data table is available as a supplement. PMID:27983601

  16. Transcriptome of Cultured Lung Fibroblasts in Idiopathic Pulmonary Fibrosis: Meta-Analysis of Publically Available Microarray Datasets Reveals Repression of Inflammation and Immunity Pathways.

    PubMed

    Plantier, Laurent; Renaud, Hélène; Respaud, Renaud; Marchand-Adam, Sylvain; Crestani, Bruno

    2016-12-13

    Heritable profibrotic differentiation of lung fibroblasts is a key mechanism of idiopathic pulmonary fibrosis (IPF). Its mechanisms are yet to be fully understood. In this study, individual data from four independent microarray studies comparing the transcriptome of fibroblasts cultured in vitro from normal (total n = 20) and IPF (total n = 20) human lung were compiled for meta-analysis following normalization to z-scores. One hundred and thirteen transcripts were upregulated and 115 were downregulated in IPF fibroblasts using the Significance Analysis of Microrrays algorithm with a false discovery rate of 5%. Downregulated genes were highly enriched for Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional classes related to inflammation and immunity such as Defense response to virus, Influenza A, tumor necrosis factor (TNF) mediated signaling pathway, interferon-inducible absent in melanoma2 (AIM2) inflammasome as well as Apoptosis. Although upregulated genes were not enriched for any functional class, select factors known to play key roles in lung fibrogenesis were overexpressed in IPF fibroblasts, most notably connective tissue growth factor (CTGF) and serum response factor (SRF), supporting their role as drivers of IPF. The full data table is available as a supplement.

  17. MiMiR – an integrated platform for microarray data sharing, mining and analysis

    PubMed Central

    Tomlinson, Chris; Thimma, Manjula; Alexandrakis, Stelios; Castillo, Tito; Dennis, Jayne L; Brooks, Anthony; Bradley, Thomas; Turnbull, Carly; Blaveri, Ekaterini; Barton, Geraint; Chiba, Norie; Maratou, Klio; Soutter, Pat; Aitman, Tim; Game, Laurence

    2008-01-01

    Background Despite considerable efforts within the microarray community for standardising data format, content and description, microarray technologies present major challenges in managing, sharing, analysing and re-using the large amount of data generated locally or internationally. Additionally, it is recognised that inconsistent and low quality experimental annotation in public data repositories significantly compromises the re-use of microarray data for meta-analysis. MiMiR, the Microarray data Mining Resource was designed to tackle some of these limitations and challenges. Here we present new software components and enhancements to the original infrastructure that increase accessibility, utility and opportunities for large scale mining of experimental and clinical data. Results A user friendly Online Annotation Tool allows researchers to submit detailed experimental information via the web at the time of data generation rather than at the time of publication. This ensures the easy access and high accuracy of meta-data collected. Experiments are programmatically built in the MiMiR database from the submitted information and details are systematically curated and further annotated by a team of trained annotators using a new Curation and Annotation Tool. Clinical information can be annotated and coded with a clinical Data Mapping Tool within an appropriate ethical framework. Users can visualise experimental annotation, assess data quality, download and share data via a web-based experiment browser called MiMiR Online. All requests to access data in MiMiR are routed through a sophisticated middleware security layer thereby allowing secure data access and sharing amongst MiMiR registered users prior to publication. Data in MiMiR can be mined and analysed using the integrated EMAAS open source analysis web portal or via export of data and meta-data into Rosetta Resolver data analysis package. Conclusion The new MiMiR suite of software enables systematic and

  18. Evaluating the Health Impact of Large-Scale Public Policy Changes: Classical and Novel Approaches.

    PubMed

    Basu, Sanjay; Meghani, Ankita; Siddiqi, Arjumand

    2017-03-20

    Large-scale public policy changes are often recommended to improve public health. Despite varying widely-from tobacco taxes to poverty-relief programs-such policies present a common dilemma to public health researchers: how to evaluate their health effects when randomized controlled trials are not possible. Here, we review the state of knowledge and experience of public health researchers who rigorously evaluate the health consequences of large-scale public policy changes. We organize our discussion by detailing approaches to address three common challenges of conducting policy evaluations: distinguishing a policy effect from time trends in health outcomes or preexisting differences between policy-affected and -unaffected communities (using difference-in-differences approaches); constructing a comparison population when a policy affects a population for whom a well-matched comparator is not immediately available (using propensity score or synthetic control approaches); and addressing unobserved confounders by utilizing quasi-random variations in policy exposure (using regression discontinuity, instrumental variables, or near-far matching approaches).

  19. Development and application of a microarray meter tool to optimize microarray experiments

    PubMed Central

    Rouse, Richard JD; Field, Katrine; Lapira, Jennifer; Lee, Allen; Wick, Ivan; Eckhardt, Colleen; Bhasker, C Ramana; Soverchia, Laura; Hardiman, Gary

    2008-01-01

    Background Successful microarray experimentation requires a complex interplay between the slide chemistry, the printing pins, the nucleic acid probes and targets, and the hybridization milieu. Optimization of these parameters and a careful evaluation of emerging slide chemistries are a prerequisite to any large scale array fabrication effort. We have developed a 'microarray meter' tool which assesses the inherent variations associated with microarray measurement prior to embarking on large scale projects. Findings The microarray meter consists of nucleic acid targets (reference and dynamic range control) and probe components. Different plate designs containing identical probe material were formulated to accommodate different robotic and pin designs. We examined the variability in probe quality and quantity (as judged by the amount of DNA printed and remaining post-hybridization) using three robots equipped with capillary printing pins. Discussion The generation of microarray data with minimal variation requires consistent quality control of the (DNA microarray) manufacturing and experimental processes. Spot reproducibility is a measure primarily of the variations associated with printing. The microarray meter assesses array quality by measuring the DNA content for every feature. It provides a post-hybridization analysis of array quality by scoring probe performance using three metrics, a) a measure of variability in the signal intensities, b) a measure of the signal dynamic range and c) a measure of variability of the spot morphologies. PMID:18710498

  20. In Situ-Synthesized Novel Microarray Optimized for Mouse Stem Cell and Early Developmental Expression Profiling

    PubMed Central

    Carter, Mark G.; Hamatani, Toshio; Sharov, Alexei A.; Carmack, Condie E.; Qian, Yong; Aiba, Kazuhiro; Ko, Naomi T.; Dudekula, Dawood B.; Brzoska, Pius M.; Hwang, S. Stuart; Ko, Minoru S.H.

    2003-01-01

    Applications of microarray technologies to mouse embryology/genetics have been limited, due to the nonavailability of microarrays containing large numbers of embryonic genes and the gap between microgram quantities of RNA required by typical microarray methods and the miniscule amounts of tissue available to researchers. To overcome these problems, we have developed a microarray platform containing in situ-synthesized 60-mer oligonucleotide probes representing approximately 22,000 unique mouse transcripts, assembled primarily from sequences of stem cell and embryo cDNA libraries. We have optimized RNA labeling protocols and experimental designs to use as little as 2 ng total RNA reliably and reproducibly. At least 98% of the probes contained in the microarray correspond to clones in our publicly available collections, making cDNAs readily available for further experimentation on genes of interest. These characteristics, combined with the ability to profile very small samples, make this system a resource for stem cell and embryogenomics research. [Supplemental material is available online at www.genome.org and at the NIA Mouse cDNA Project Web site, http://lgsun.grc.nia.nih.gov/cDNA/cDNA.html.] PMID:12727912

  1. Generation of a non-small cell lung cancer transcriptome microarray

    PubMed Central

    Tanney, Austin; Oliver, Gavin R; Farztdinov, Vadim; Kennedy, Richard D; Mulligan, Jude M; Fulton, Ciaran E; Farragher, Susan M; Field, John K; Johnston, Patrick G; Harkin, D Paul; Proutski, Vitali; Mulligan, Karl A

    2008-01-01

    Background Non-small cell lung cancer (NSCLC) is the leading cause of cancer mortality worldwide. At present no reliable biomarkers are available to guide the management of this condition. Microarray technology may allow appropriate biomarkers to be identified but present platforms are lacking disease focus and are thus likely to miss potentially vital information contained in patient tissue samples. Methods A combination of large-scale in-house sequencing, gene expression profiling and public sequence and gene expression data mining were used to characterise the transcriptome of NSCLC and the data used to generate a disease-focused microarray – the Lung Cancer DSA research tool. Results Built on the Affymetrix GeneChip platform, the Lung Cancer DSA research tool allows for interrogation of ~60,000 transcripts relevant to Lung Cancer, tens of thousands of which are unavailable on leading commercial microarrays. Conclusion We have developed the first high-density disease specific transcriptome microarray. We present the array design process and the results of experiments carried out to demonstrate the array's utility. This approach serves as a template for the development of other disease transcriptome microarrays, including non-neoplastic diseases. PMID:18513400

  2. Quantitative methods for genome-scale analysis of in situ hybridization and correlation with microarray data

    PubMed Central

    Lee, Chang-Kyu; Sunkin, Susan M; Kuan, Chihchau; Thompson, Carol L; Pathak, Sayan; Ng, Lydia; Lau, Chris; Fischer, Shanna; Mortrud, Marty; Slaughterbeck, Cliff; Jones, Allan; Lein, Ed; Hawrylycz, Michael

    2008-01-01

    With the emergence of genome-wide colorimetric in situ hybridization (ISH) data sets such as the Allen Brain Atlas, it is important to understand the relationship between this gene expression modality and those derived from more quantitative based technologies. This study introduces a novel method for standardized relative quantification of colorimetric ISH signal that enables a large-scale cross-platform expression level comparison of ISH with two publicly available microarray brain data sources. PMID:18234097

  3. Gene expression profiling in peanut using high density oligonucleotide microarrays

    PubMed Central

    Payton, Paxton; Kottapalli, Kameswara Rao; Rowland, Diane; Faircloth, Wilson; Guo, Baozhu; Burow, Mark; Puppala, Naveen; Gallo, Maria

    2009-01-01

    Background Transcriptome expression analysis in peanut to date has been limited to a relatively small set of genes and only recently has a significant number of ESTs been released into the public domain. Utilization of these ESTs for oligonucleotide microarrays provides a means to investigate large-scale transcript responses to a variety of developmental and environmental signals, ultimately improving our understanding of plant biology. Results We have developed a high-density oligonucleotide microarray for peanut using 49,205 publicly available ESTs and tested the utility of this array for expression profiling in a variety of peanut tissues. To identify putatively tissue-specific genes and demonstrate the utility of this array for expression profiling in a variety of peanut tissues, we compared transcript levels in pod, peg, leaf, stem, and root tissues. Results from this experiment showed 108 putatively pod-specific/abundant genes, as well as transcripts whose expression was low or undetected in pod compared to peg, leaf, stem, or root. The transcripts significantly over-represented in pod include genes responsible for seed storage proteins and desiccation (e.g., late-embryogenesis abundant proteins, aquaporins, legumin B), oil production, and cellular defense. Additionally, almost half of the pod-abundant genes represent unknown genes allowing for the possibility of associating putative function to these previously uncharacterized genes. Conclusion The peanut oligonucleotide array represents the majority of publicly available peanut ESTs and can be used as a tool for expression profiling studies in diverse tissues. PMID:19523230

  4. Building Community Disaster Resilience: Perspectives From a Large Urban County Department of Public Health

    PubMed Central

    Fielding, Jonathan E.; Chandra, Anita; Williams, Malcolm; Eisenman, David; Wells, Kenneth B.; Law, Grace Y.; Fogleman, Stella; Magaña, Aizita

    2013-01-01

    An emerging approach to public health emergency preparedness and response, community resilience encompasses individual preparedness as well as establishing a supportive social context in communities to withstand and recover from disasters. We examine why building community resilience has become a key component of national policy across multiple federal agencies and discuss the core principles embodied in community resilience theory—specifically, the focus on incorporating equity and social justice considerations in preparedness planning and response. We also examine the challenges of integrating community resilience with traditional public health practices and the importance of developing metrics for evaluation and strategic planning purposes. Using the example of the Los Angeles County Community Disaster Resilience Project, we discuss our experience and perspective from a large urban county to better understand how to implement a community resilience framework in public health practice. PMID:23678937

  5. Building community disaster resilience: perspectives from a large urban county department of public health.

    PubMed

    Plough, Alonzo; Fielding, Jonathan E; Chandra, Anita; Williams, Malcolm; Eisenman, David; Wells, Kenneth B; Law, Grace Y; Fogleman, Stella; Magaña, Aizita

    2013-07-01

    An emerging approach to public health emergency preparedness and response, community resilience encompasses individual preparedness as well as establishing a supportive social context in communities to withstand and recover from disasters. We examine why building community resilience has become a key component of national policy across multiple federal agencies and discuss the core principles embodied in community resilience theory-specifically, the focus on incorporating equity and social justice considerations in preparedness planning and response. We also examine the challenges of integrating community resilience with traditional public health practices and the importance of developing metrics for evaluation and strategic planning purposes. Using the example of the Los Angeles County Community Disaster Resilience Project, we discuss our experience and perspective from a large urban county to better understand how to implement a community resilience framework in public health practice.

  6. Protein Microarrays for the Detection of Biothreats

    NASA Astrophysics Data System (ADS)

    Herr, Amy E.

    Although protein microarrays have proven to be an important tool in proteomics research, the technology is emerging as useful for public health and defense applications. Recent progress in the measurement and characterization of biothreat agents is reviewed in this chapter. Details concerning validation of various protein microarray formats, from contact-printed sandwich assays to supported lipid bilayers, are presented. The reviewed technologies have important implications for in vitro characterization of toxin-ligand interactions, serotyping of bacteria, screening of potential biothreat inhibitors, and as core components of biosensors, among others, research and engineering applications.

  7. Microarray Inspector: tissue cross contamination detection tool for microarray data.

    PubMed

    Stępniak, Piotr; Maycock, Matthew; Wojdan, Konrad; Markowska, Monika; Perun, Serhiy; Srivastava, Aashish; Wyrwicz, Lucjan S; Świrski, Konrad

    2013-01-01

    Microarray technology changed the landscape of contemporary life sciences by providing vast amounts of expression data. Researchers are building up repositories of experiment results with various conditions and samples which serve the scientific community as a precious resource. Ensuring that the sample is of high quality is of utmost importance to this effort. The task is complicated by the fact that in many cases datasets lack information concerning pre-experimental quality assessment. Transcription profiling of tissue samples may be invalidated by an error caused by heterogeneity of the material. The risk of tissue cross contamination is especially high in oncological studies, where it is often difficult to extract the sample. Therefore, there is a need of developing a method detecting tissue contamination in a post-experimental phase. We propose Microarray Inspector: customizable, user-friendly software that enables easy detection of samples containing mixed tissue types. The advantage of the tool is that it uses raw expression data files and analyses each array independently. In addition, the system allows the user to adjust the criteria of the analysis to conform to individual needs and research requirements. The final output of the program contains comfortable to read reports about tissue contamination assessment with detailed information about the test parameters and results. Microarray Inspector provides a list of contaminant biomarkers needed in the analysis of adipose tissue contamination. Using real data (datasets from public repositories) and our tool, we confirmed high specificity of the software in detecting contamination. The results indicated the presence of adipose tissue admixture in a range from approximately 4% to 13% in several tested surgical samples.

  8. Coffee Shops, Classrooms and Conversations: public engagement and outreach in a large interdisciplinary research Hub

    NASA Astrophysics Data System (ADS)

    Holden, Jennifer A.

    2014-05-01

    Public engagement and outreach activities are increasingly using specialist staff for co-ordination, training and support for researchers, they are also becoming expected for large investments. Here, the experience of public engagement and outreach a large, interdisciplinary Research Hub is described. dot.rural, based at the University of Aberdeen UK, is a £11.8 million Research Councils UK Rural Digital Economy Hub, funded as part of the RCUK Digital Economy Theme (2009-2015). Digital Economy research aims to realise the transformational impact of digital technologies on aspects of the environment, community life, cultural experiences, future society, and the economy. The dot.rural Hub involves 92 researchers from 12 different disciplines, including Geography, Hydrology and Ecology. Public Engagement and Outreach is embedded in the dot.rural Digital Economy Hub via an Outreach Officer. Alongside this position, public engagement and outreach activities are compulsory part of PhD student contracts. Public Engagement and Outreach activities at the dot.rural Hub involve individuals and groups in both formal and informal settings organised by dot.rural and other organisations. Activities in the realms of Education, Public Engagement, Traditional and Social Media are determined by a set of Underlying Principles designed for the Hub by the Outreach Officer. The underlying Engagement and Outreach principles match funding agency requirements and expectations alongside researcher demands and the user-led nature of Digital Economy Research. All activities include researchers alongside the Outreach Officer are research informed and embedded into specific projects that form the Hub. Successful public engagement activities have included participation in Café Scientifique series, workshops in primary and secondary schools, and online activities such as I'm a Scientist Get Me Out of Here. From how to engage 8 year olds with making hydrographs more understandable to members of

  9. A novel approach to screening for familial hypercholesterolemia in a large public venue.

    PubMed

    Campbell, Megan; Humanki, Jessa; Zierhut, Heather

    2017-01-01

    The primary aim of this study was to test the feasibility of a public health screening program to identify individuals at high risk of familial hypercholesterolemia through a novel screening approach at a large public venue. A finger-prick, non-fasting lipid panel was obtained, and a survey which consisted of 44 open- and close-ended questions divided into four sections: medical and family history of FH, opinions of cascade genetic testing, patient activation, and demographics was completed. A total of 971 participants met criteria and completed a cholesterol screen. In total, five individuals met either the Simon Broome Register or the Dutch Lipid Clinic Network criteria for possible familial hypercholesterolemia. Participants were generally positive towards genetic testing, and the vast majority listed they had no barriers to communication of genetic testing information to family members. However, the most common barrier listed was lack of communication skills. Our results suggest that a public health screening program for FH is viable at a large public venue. We argue that further research is needed to expand this study to a fully operational screening program.

  10. Classroom management programs for deaf children in state residential and large public schools.

    PubMed

    Wenkus, M; Rittenhouse, B; Dancer, J

    1999-12-01

    Personnel in 4 randomly selected state residential schools for the deaf and 3 randomly selected large public schools with programs for the deaf were surveyed to assess the types of management or disciplinary programs and strategies currently in use with deaf students and the rated effectiveness of such programs. Several behavioral management programs were identified by respondents, with Assertive Discipline most often listed. Ratings of program effectiveness were generally above average on a number of qualitative criteria.

  11. Functional GPCR microarrays.

    PubMed

    Hong, Yulong; Webb, Brian L; Su, Hui; Mozdy, Eric J; Fang, Ye; Wu, Qi; Liu, Li; Beck, Jonathan; Ferrie, Ann M; Raghavan, Srikanth; Mauro, John; Carre, Alain; Müeller, Dirk; Lai, Fang; Rasnow, Brian; Johnson, Michael; Min, Hosung; Salon, John; Lahiri, Joydeep

    2005-11-09

    This paper describes G-protein-coupled receptor (GPCR) microarrays on porous glass substrates and functional assays based on the binding of a europium-labeled GTP analogue. The porous glass slides were made by casting a glass frit on impermeable glass slides and then coating with gamma-aminopropyl silane (GAPS). The emitted fluorescence was captured on an imager with a time-gated intensified CCD detector. Microarrays of the neurotensin receptor 1, the cholinergic receptor muscarinic 2, the opioid receptor mu, and the cannabinoid receptor 1 were fabricated by pin printing. The selective agonism of each of the receptors was observed. The screening of potential antagonists was demonstrated using a cocktail of agonists. The amount of activation observed was sufficient to permit determinations of EC50 and IC50. Such microarrays could potentially streamline drug discovery by helping integrate primary screening with selectivity and safety screening without compromising the essential functional information obtainable from cellular assays.

  12. Nanotechnologies in protein microarrays.

    PubMed

    Krizkova, Sona; Heger, Zbynek; Zalewska, Marta; Moulick, Amitava; Adam, Vojtech; Kizek, Rene

    2015-01-01

    Protein microarray technology became an important research tool for study and detection of proteins, protein-protein interactions and a number of other applications. The utilization of nanoparticle-based materials and nanotechnology-based techniques for immobilization allows us not only to extend the surface for biomolecule immobilization resulting in enhanced substrate binding properties, decreased background signals and enhanced reporter systems for more sensitive assays. Generally in contemporarily developed microarray systems, multiple nanotechnology-based techniques are combined. In this review, applications of nanoparticles and nanotechnologies in creating protein microarrays, proteins immobilization and detection are summarized. We anticipate that advanced nanotechnologies can be exploited to expand promising fields of proteins identification, monitoring of protein-protein or drug-protein interactions, or proteins structures.

  13. QA/QC issues to aid regulatory acceptance of microarray gene expression data.

    PubMed

    Fuscoe, James C; Tong, Weida; Shi, Leming

    2007-06-01

    The U.S. Food and Drug Administration is responsible for (1) promoting and protecting public health by assuring the safety and effectiveness of medicines and medical devices and (2) advancing public health by helping to speed innovations that make medicines and foods safer, more effective, and more affordable. The genomics revolution has dramatically increased our knowledge of basic biology but this has not resulted in the expected acceleration of new medical product development. The Agency's Critical Path to New Medical Products stresses that new tools are needed to address this pipeline problem. Microarray technology is one of these promising tools although questions have risen about the reproducibility of measurements. The Microarray Quality Control (MAQC) Project was initiated by FDA scientists to address this issue. This large project, which evaluated reference RNA samples on seven microarray platforms, found good intralaboratory repeatability and interlaboratory reproducibility. In addition, there was high cross-platform consistency. All data are available free of cost and the reference RNA samples are available for proficiency testing. Thus, current microarray technology appears to provide both reliability and consistency for regulatory submissions.

  14. Lessons learned: Infrastructure development and financial management for large, publically funded, international trials

    PubMed Central

    Larson, Gregg S; Carey, Cate; Grarup, Jesper; Hudson, Fleur; Sachi, Karen; Vjecha, Michael J; Gordin, Fred

    2015-01-01

    Background/Aims Randomized clinical trials are widely recognized as essential to address world-wide clinical and public health research questions. However, for many conditions, their size and duration can overwhelm available public and private resources. To remain competitive in international research settings, advocates and practitioners of clinical trials must implement practices that reduce their cost. We identify approaches and practices for large, publicly-funded, international trials that reduce cost without compromising data integrity, and recommend an approach to cost reporting that permits comparison of clinical trials. Methods We describe the organizational and financial characteristics of INSIGHT, an infectious disease research network that conducts multiple, large, long-term, international trials, and examine challenges associated with simple and streamlined governance and an infrastructure and financial management model that is based on performance, transparency, and accountability. Results It is possible to reduce costs of participant follow-up and not compromise clinical trial quality or integrity. The INSIGHT network has successfully completed four large HIV trials using cost-efficient practices that have not adversely affected investigator enthusiasm, accrual rates, loss-to-follow-up, adherence to the protocol, and completion of data collection. This experience is relevant to the conduct of large, publically funded trials in other disease areas, particularly trials dependent on international collaborations. Conclusion New approaches, or creative adaption of traditional clinical trial infrastructure and financial management tools, can render large, international clinical trials more cost-efficient by emphasizing structural simplicity; minimal up-front costs; payments for performance; and uniform algorithms and fees-for-service, irrespective of location. However, challenges remain. They include institutional resistance to financial change, growing

  15. Lessons learned: Infrastructure development and financial management for large, publicly funded, international trials.

    PubMed

    Larson, Gregg S; Carey, Cate; Grarup, Jesper; Hudson, Fleur; Sachi, Karen; Vjecha, Michael J; Gordin, Fred

    2016-04-01

    Randomized clinical trials are widely recognized as essential to address worldwide clinical and public health research questions. However, their size and duration can overwhelm available public and private resources. To remain competitive in international research settings, advocates and practitioners of clinical trials must implement practices that reduce their cost. We identify approaches and practices for large, publicly funded, international trials that reduce cost without compromising data integrity and recommend an approach to cost reporting that permits comparison of clinical trials. We describe the organizational and financial characteristics of The International Network for Strategic Initiatives in Global HIV Trials, an infectious disease research network that conducts multiple, large, long-term, international trials, and examine challenges associated with simple and streamlined governance and an infrastructure and financial management model that is based on performance, transparency, and accountability. It is possible to reduce costs of participants' follow-up and not compromise clinical trial quality or integrity. The International Network for Strategic Initiatives in Global HIV Trials network has successfully completed three large HIV trials using cost-efficient practices that have not adversely affected investigator enthusiasm, accrual rates, loss-to-follow-up, adherence to the protocol, and completion of data collection. This experience is relevant to the conduct of large, publicly funded trials in other disease areas, particularly trials dependent on international collaborations. New approaches, or creative adaption of traditional clinical trial infrastructure and financial management tools, can render large, international clinical trials more cost-efficient by emphasizing structural simplicity, minimal up-front costs, payments for performance, and uniform algorithms and fees-for-service, irrespective of location. However, challenges remain. They

  16. Large-scale virtual screening on public cloud resources with Apache Spark.

    PubMed

    Capuccini, Marco; Ahmed, Laeeq; Schaal, Wesley; Laure, Erwin; Spjuth, Ola

    2017-01-01

    Structure-based virtual screening is an in-silico method to screen a target receptor against a virtual molecular library. Applying docking-based screening to large molecular libraries can be computationally expensive, however it constitutes a trivially parallelizable task. Most of the available parallel implementations are based on message passing interface, relying on low failure rate hardware and fast network connection. Google's MapReduce revolutionized large-scale analysis, enabling the processing of massive datasets on commodity hardware and cloud resources, providing transparent scalability and fault tolerance at the software level. Open source implementations of MapReduce include Apache Hadoop and the more recent Apache Spark. We developed a method to run existing docking-based screening software on distributed cloud resources, utilizing the MapReduce approach. We benchmarked our method, which is implemented in Apache Spark, docking a publicly available target receptor against [Formula: see text]2.2 M compounds. The performance experiments show a good parallel efficiency (87%) when running in a public cloud environment. Our method enables parallel Structure-based virtual screening on public cloud resources or commodity computer clusters. The degree of scalability that we achieve allows for trying out our method on relatively small libraries first and then to scale to larger libraries. Our implementation is named Spark-VS and it is freely available as open source from GitHub (https://github.com/mcapuccini/spark-vs).Graphical abstract.

  17. Protein Microarray Technology

    PubMed Central

    Hall, David A.; Ptacek, Jason

    2007-01-01

    Protein chips have emerged as a promising approach for a wide variety of applications including the identification of protein-protein interactions, protein-phospholipid interactions, small molecule targets, and substrates of proteins kinases. They can also be used for clinical diagnostics and monitoring disease states. This article reviews current methods in the generation and applications of protein microarrays. PMID:17126887

  18. Life science-based neuroscience education at large Western Public Universities.

    PubMed

    Coskun, Volkan; Carpenter, Ellen M

    2016-12-01

    The last 40 years have seen a remarkable increase in the teaching of neuroscience at the undergraduate level. From its origins as a component of anatomy or physiology departments to its current status as an independent interdisciplinary field, neuroscience has become the chosen field of study for many undergraduate students, particularly for those interested in medical school or graduate school in neuroscience or related fields. We examined how life science-based neuroscience education is offered at large public universities in the Western United States. By examining publicly available materials posted online, we found that neuroscience education may be offered as an independent program, or as a component of biological or physiological sciences at many institutions. Neuroscience programs offer a course of study involving a core series of courses and a collection of topical electives. Many programs provide the opportunity for independent research, or for laboratory-based training in neuroscience. Features of neuroscience programs at Western universities closely matched those seen at the top 25 public universities, as identified by U.S. News & World Report. While neuroscience programs were identified in many Western states, there were several states in which public universities appeared not to provide opportunities to major in neuroscience. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

  19. Non-publication of large randomized clinical trials: cross sectional analysis

    PubMed Central

    Handler, Lara; Crowell, Karen E; Keil, Lukas G; Weaver, Mark A; Platts-Mills, Timothy F

    2013-01-01

    Objective To estimate the frequency with which results of large randomized clinical trials registered with ClinicalTrials.gov are not available to the public. Design Cross sectional analysis Setting Trials with at least 500 participants that were prospectively registered with ClinicalTrials.gov and completed prior to January 2009. Data sources PubMed, Google Scholar, and Embase were searched to identify published manuscripts containing trial results. The final literature search occurred in November 2012. Registry entries for unpublished trials were reviewed to determine whether results for these studies were available in the ClinicalTrials.gov results database. Main outcome measures The frequency of non-publication of trial results and, among unpublished studies, the frequency with which results are unavailable in the ClinicalTrials.gov database. Results Of 585 registered trials, 171 (29%) remained unpublished. These 171 unpublished trials had an estimated total enrollment of 299 763 study participants. The median time between study completion and the final literature search was 60 months for unpublished trials. Non-publication was more common among trials that received industry funding (150/468, 32%) than those that did not (21/117, 18%), P=0.003. Of the 171 unpublished trials, 133 (78%) had no results available in ClinicalTrials.gov. Conclusions Among this group of large clinical trials, non-publication of results was common and the availability of results in the ClinicalTrials.gov database was limited. A substantial number of study participants were exposed to the risks of trial participation without the societal benefits that accompany the dissemination of trial results. PMID:24169943

  20. The MicroArray Quality Control (MAQC) project shows inter- and intraplatform reproducibility of gene expression measurements

    EPA Science Inventory

    Over the last decade, the introduction of microarray technology has had a profound impact on gene expression research. The publication of studies with dissimilar or altogether contradictory results, obtained using different microarray platforms to analyze identical RNA samples, ...

  1. MICROARRAY QUALITY CONTROL PROJECT: A COMPREHENSIVE GENE EXPRESSION TECHNOLOGY SURVEY DEMONSTRATES MEASURABLE CONSISTENCY AND CONCORDANT RESULTS BETWEEN PLATFORMS

    EPA Science Inventory

    Over the last decade, the introduction of microarray technology has had a profound impact on gene expression research. The publication of studies with dissimilar or altogether contradictory results, obtained using different microarray platforms to analyze identical RNA samples, h...

  2. MICROARRAY QUALITY CONTROL PROJECT: A COMPREHENSIVE GENE EXPRESSION TECHNOLOGY SURVEY DEMONSTRATES MEASURABLE CONSISTENCY AND CONCORDANT RESULTS BETWEEN PLATFORMS

    EPA Science Inventory

    Over the last decade, the introduction of microarray technology has had a profound impact on gene expression research. The publication of studies with dissimilar or altogether contradictory results, obtained using different microarray platforms to analyze identical RNA samples, h...

  3. The MicroArray Quality Control (MAQC) project shows inter- and intraplatform reproducibility of gene expression measurements

    EPA Science Inventory

    Over the last decade, the introduction of microarray technology has had a profound impact on gene expression research. The publication of studies with dissimilar or altogether contradictory results, obtained using different microarray platforms to analyze identical RNA samples, ...

  4. Autocorrelation analysis reveals widespread spatial biases in microarray experiments

    PubMed Central

    Koren, Amnon; Tirosh, Itay; Barkai, Naama

    2007-01-01

    Background DNA microarrays provide the ability to interrogate multiple genes in a single experiment and have revolutionized genomic research. However, the microarray technology suffers from various forms of biases and relatively low reproducibility. A particular source of false data has been described, in which non-random placement of gene probes on the microarray surface is associated with spurious correlations between genes. Results In order to assess the prevalence of this effect and better understand its origins, we applied an autocorrelation analysis of the relationship between chromosomal position and expression level to a database of over 2000 individual yeast microarray experiments. We show that at least 60% of these experiments exhibit spurious chromosomal position-dependent gene correlations, which nonetheless appear in a stochastic manner within each experimental dataset. Using computer simulations, we show that large spatial biases caused in the microarray hybridization step and independently of printing procedures can exclusively account for the observed spurious correlations, in contrast to previous suggestions. Our data suggest that such biases may generate more than 15% false data per experiment. Importantly, spatial biases are expected to occur regardless of microarray design and over a wide range of microarray platforms, organisms and experimental procedures. Conclusions Spatial biases comprise a major source of noise in microarray studies; revision of routine experimental practices and normalizations to account for these biases may significantly and comprehensively improve the quality of new as well as existing DNA microarray data. PMID:17565680

  5. Autocorrelation analysis reveals widespread spatial biases in microarray experiments.

    PubMed

    Koren, Amnon; Tirosh, Itay; Barkai, Naama

    2007-06-12

    DNA microarrays provide the ability to interrogate multiple genes in a single experiment and have revolutionized genomic research. However, the microarray technology suffers from various forms of biases and relatively low reproducibility. A particular source of false data has been described, in which non-random placement of gene probes on the microarray surface is associated with spurious correlations between genes. In order to assess the prevalence of this effect and better understand its origins, we applied an autocorrelation analysis of the relationship between chromosomal position and expression level to a database of over 2000 individual yeast microarray experiments. We show that at least 60% of these experiments exhibit spurious chromosomal position-dependent gene correlations, which nonetheless appear in a stochastic manner within each experimental dataset. Using computer simulations, we show that large spatial biases caused in the microarray hybridization step and independently of printing procedures can exclusively account for the observed spurious correlations, in contrast to previous suggestions. Our data suggest that such biases may generate more than 15% false data per experiment. Importantly, spatial biases are expected to occur regardless of microarray design and over a wide range of microarray platforms, organisms and experimental procedures. Spatial biases comprise a major source of noise in microarray studies; revision of routine experimental practices and normalizations to account for these biases may significantly and comprehensively improve the quality of new as well as existing DNA microarray data.

  6. Public-private partnerships with large corporations: setting the ground rules for better health.

    PubMed

    Galea, Gauden; McKee, Martin

    2014-04-01

    Public-private partnerships with large corporations offer potential benefits to the health sector but many concerns have been raised, highlighting the need for appropriate safeguards. In this paper we propose five tests that public policy makers may wish to apply when considering engaging in such a public-private partnership. First, are the core products and services provided by the corporation health enhancing or health damaging? In some cases, such as tobacco, the answer is obvious but others, such as food and alcohol, are contested. In such cases, the burden of proof is on the potential partners to show that their activities are health enhancing. Second, do potential partners put their policies into practice in the settings where they can do so, their own workplaces? Third, are the corporate social responsibility activities of potential partners independently audited? Fourth, do potential partners make contributions to the commons rather than to narrow programmes of their choosing? Fifth, is the role of the partner confined to policy implementation rather than policy development, which is ultimately the responsibility of government alone?

  7. Performing custom microRNA microarray experiments.

    PubMed

    Zhang, Xiaoxiao; Zeng, Yan

    2011-10-28

    microRNAs (miRNAs) are a large family of ˜ 22 nucleotides (nt) long RNA molecules that are widely expressed in eukaryotes (1). Complex genomes encode at least hundreds of miRNAs, which primarily inhibit the expression of a vast number of target genes post-transcriptionally (2, 3). miRNAs control a broad range of biological processes (1). In addition, altered miRNA expression has been associated with human diseases such as cancers, and miRNAs may serve as biomarkers for diseases and prognosis (4, 5). It is important, therefore, to understand the expression and functions of miRNAs under many different conditions. Three major approaches have been employed to profile miRNA expression: real-time PCR, microarray, and deep sequencing. The technique of miRNA microarray has the advantage of being high-throughput, generally less expensive, and most of the experimental and analysis steps can be carried out in a molecular biology laboratory at most universities, medical schools and associated hospitals. Here, we describe a method for performing custom miRNA microarray experiments. A miRNA probe set will be printed on glass slides to produce miRNA microarrays. RNA is isolated using a method or reagent that preserves small RNA species, and then labeled with a fluorescence dye. As a control, reference DNA oligonucleotides corresponding to a subset of miRNAs are also labeled with a different fluorescence dye. The reference DNA will serve to demonstrate the quality of the slide and hybridization and will also be used for data normalization. The RNA and DNA are mixed and hybridized to a microarray slide containing probes for most of the miRNAs in the database. After washing, the slide is scanned to obtain images, and intensities of the individual spots quantified. These raw signals will be further processed and analyzed as the expression data of the corresponding miRNAs. Microarray slides can be stripped and regenerated to reduce the cost of microarrays and to enhance the

  8. ECplot: an online tool for making standardized plots from large datasets for bioinformatics publications.

    PubMed

    Fok, Alex Chun-Hong; Mok, Sunny Siu-Nam; Lee, Sau Dan; Yip, Kevin Y

    2014-05-15

    We have implemented ECplot, an online tool for plotting charts from large datasets. This tool supports a variety of chart types commonly used in bioinformatics publications. In our benchmarking, it was able to create a Box-and-Whisker plot with about 67 000 data points and 8 MB total file size within several seconds. The design of the tool makes common formatting operations easy to perform. It also allows more complex operations to be achieved by advanced XML (Extensible Markup Language) and programming options. Data and formatting styles are stored in separate files, such that style templates can be made and applied to new datasets. The text-based file formats based on XML facilitate efficient manipulation of formatting styles for a large number of data series. These file formats also provide a means to reproduce published figures from raw data, which complement parallel efforts in making the data and software involved in published analysis results accessible. We demonstrate this idea by using ECplot to replicate some complex figures from a previous publication. ECplot and its source code (under MIT license) are available at https://yiplab.cse.cuhk.edu.hk/ecplot/. kevinyip@cse.cuhk.edu.hk.

  9. Diagnostic variability for schizophrenia and major depression in a large public mental health care system dataset.

    PubMed

    Folsom, David P; Lindamer, Laurie; Montross, Lori P; Hawthorne, William; Golshan, Shahrokh; Hough, Richard; Shale, John; Jeste, Dilip V

    2006-11-15

    Administrative datasets can provide information about mental health treatment in real world settings; however, an important limitation in using these datasets is the uncertainty regarding psychiatric diagnosis. To better understand the psychiatric diagnoses, we investigated the diagnostic variability of schizophrenia and major depression in a large public mental health system. Using schizophrenia and major depression as the two comparison diagnoses, we compared the variability of diagnoses assigned to patients with one recorded diagnosis of schizophrenia or major depression. In addition, for both of these diagnoses, the diagnostic variability was compared across seven types of treatment settings. Statistical analyses were conducted using t tests for continuous data and chi-square tests for categorical data. We found that schizophrenia had greater diagnostic variability than major depression (31% vs. 43%). For both schizophrenia and major depression, variability was significantly higher in jail and the emergency psychiatric unit than in inpatient or outpatient settings. These findings demonstrate that the variability of psychiatric diagnoses recorded in the administrative dataset of a large public mental health system varies by diagnosis and by treatment setting. Further research is needed to clarify the relationship between psychiatric diagnosis, diagnostic variability and treatment setting.

  10. How Consistent are Publicly Reported Cytotoxicity Data? Large-Scale Statistical Analysis of the Concordance of Public Independent Cytotoxicity Measurements.

    PubMed

    Cortés-Ciriano, Isidro; Bender, Andreas

    2016-01-05

    While increased attention is being paid to the impact of data quality in cell-line sensitivity and toxicology modeling, to date, no systematic study has evaluated the comparability of independent cytotoxicity measurements on a large-scale. Here, we estimate the experimental uncertainty of public cytotoxicity data from ChEMBL version 19. We applied stringent filtering criteria to assemble a curated data set comprised of pIC50 data for compound-cell line systems measured in independent laboratories. The estimated experimental uncertainty calculated was a mean unsigned error (MUE) value of 0.61-0.76, a median unsigned error (MedUE) value of 0.51-0.58, and a standard deviation of 0.76-1.00 pIC50 units. The experimental uncertainty (σE) estimated from all pairs of cytotoxicity measurements with a ΔpIC50 value lower than 2.5 was found to be 0.59-0.77 pIC50 units, and thus 21-60% and 21-26% higher than that of pKi and pIC50 data for ligand-protein data (σE =0.47-0.48 pKi units and σE =0.57-0.61 pIC50 units, respectively). The estimated σE value from the pairs of pIC50 values measured with metabolic assays was 0.98, whereas the σE value was found to be 0.69 when using the 1388 pIC50 pairs measured using exactly the same experimental setup. The maximum achievable Pearson correlation coefficient (RPearsonmax.2) of in silico models trained on cytotoxicity data from different laboratories was estimated to be 0.51-0.85, which is considerably different from the value of 1 corresponding to perfect predictions, hinting at the maximum performance one can expect also from computational cytotoxicity predictions. The lowest concordance between pairs of measurements was found for the drugs paclitaxel, methotrexate, zidovudine, and docetaxel, and for the cell lines HepG2, NCI-H460, L1210, and CCRF-CEM, hinting at particular sensitivity of those systems to experimental setups. The highest concordance was estimated for the compound-cell line system HL-60-etoposide (σE =0

  11. Biolog phenotype microarrays.

    PubMed

    Shea, April; Wolcott, Mark; Daefler, Simon; Rozak, David A

    2012-01-01

    Phenotype microarrays nicely complement traditional genomic, transcriptomic, and proteomic analysis by offering opportunities for researchers to ground microbial systems analysis and modeling in a broad yet quantitative assessment of the organism's physiological response to different metabolites and environments. Biolog phenotype assays achieve this by coupling tetrazolium dyes with minimally defined nutrients to measure the impact of hundreds of carbon, nitrogen, phosphorous, and sulfur sources on redox reactions that result from compound-induced effects on the electron transport chain. Over the years, we have used Biolog's reproducible and highly sensitive assays to distinguish closely related bacterial isolates, to understand their metabolic differences, and to model their metabolic behavior using flux balance analysis. This chapter describes Biolog phenotype microarray system components, reagents, and methods, particularly as they apply to bacterial identification, characterization, and metabolic analysis.

  12. Analyzing Microarray Data.

    PubMed

    Hung, Jui-Hung; Weng, Zhiping

    2017-03-01

    Because there is no widely used software for analyzing RNA-seq data that has a graphical user interface, this protocol provides an example of analyzing microarray data using Babelomics. This analysis entails performing quantile normalization and then detecting differentially expressed genes associated with the transgenesis of a human oncogene c-Myc in mice. Finally, hierarchical clustering is performed on the differentially expressed genes using the Cluster program, and the results are visualized using TreeView.

  13. Membrane-based microarrays

    NASA Astrophysics Data System (ADS)

    Dawson, Elliott P.; Hudson, James; Steward, John; Donnell, Philip A.; Chan, Wing W.; Taylor, Richard F.

    1999-11-01

    Microarrays represent a new approach to the rapid detection and identification of analytes. Studies to date have shown that the immobilization of receptor molecules (such as DNA, oligonucleotides, antibodies, enzymes and binding proteins) onto silicon and polymeric substrates can result in arrays able to detect hundreds of analytes in a single step. The formation of the receptor/analyte complex can, itself, lead to detection, or the complex can be interrogated through the use of fluorescent, chemiluminescent or radioactive probes and ligands.

  14. MIMAS: an innovative tool for network-based high density oligonucleotide microarray data management and annotation

    PubMed Central

    Hermida, Leandro; Schaad, Olivier; Demougin, Philippe; Descombes, Patrick; Primig, Michael

    2006-01-01

    Background The high-density oligonucleotide microarray (GeneChip) is an important tool for molecular biological research aiming at large-scale detection of small nucleotide polymorphisms in DNA and genome-wide analysis of mRNA concentrations. Local array data management solutions are instrumental for efficient processing of the results and for subsequent uploading of data and annotations to a global certified data repository at the EBI (ArrayExpress) or the NCBI (GeneOmnibus). Description To facilitate and accelerate annotation of high-throughput expression profiling experiments, the Microarray Information Management and Annotation System (MIMAS) was developed. The system is fully compliant with the Minimal Information About a Microarray Experiment (MIAME) convention. MIMAS provides life scientists with a highly flexible and focused GeneChip data storage and annotation platform essential for subsequent analysis and interpretation of experimental results with clustering and mining tools. The system software can be downloaded for academic use upon request. Conclusion MIMAS implements a novel concept for nation-wide GeneChip data management whereby a network of facilities is centered on one data node directly connected to the European certified public microarray data repository located at the EBI. The solution proposed may serve as a prototype approach to array data management between research institutes organized in a consortium. PMID:16597336

  15. Automating dChip: toward reproducible sharing of microarray data analysis.

    PubMed

    Li, Cheng

    2008-05-08

    During the past decade, many software packages have been developed for analysis and visualization of various types of microarrays. We have developed and maintained the widely used dChip as a microarray analysis software package accessible to both biologist and data analysts. However, challenges arise when dChip users want to analyze large number of arrays automatically and share data analysis procedures and parameters. Improvement is also needed when the dChip user support team tries to identify the causes of reported analysis errors or bugs from users. We report here implementation and application of the dChip automation module. Through this module, dChip automation files can be created to include menu steps, parameters, and data viewpoints to run automatically. A data-packaging function allows convenient transfer from one user to another of the dChip software, microarray data, and analysis procedures, so that the second user can reproduce the entire analysis session of the first user. An analysis report file can also be generated during an automated run, including analysis logs, user comments, and viewpoint screenshots. The dChip automation module is a step toward reproducible research, and it can prompt a more convenient and reproducible mechanism for sharing microarray software, data, and analysis procedures and results. Automation data packages can also be used as publication supplements. Similar automation mechanisms could be valuable to the research community if implemented in other genomics and bioinformatics software packages.

  16. Raman-based microarray readout: a review.

    PubMed

    Haisch, Christoph

    2016-07-01

    For a quarter of a century, microarrays have been part of the routine analytical toolbox. Label-based fluorescence detection is still the commonest optical readout strategy. Since the 1990s, a continuously increasing number of label-based as well as label-free experiments on Raman-based microarray readout concepts have been reported. This review summarizes the possible concepts and methods and their advantages and challenges. A common label-based strategy is based on the binding of selective receptors as well as Raman reporter molecules to plasmonic nanoparticles in a sandwich immunoassay, which results in surface-enhanced Raman scattering signals of the reporter molecule. Alternatively, capture of the analytes can be performed by receptors on a microarray surface. Addition of plasmonic nanoparticles again leads to a surface-enhanced Raman scattering signal, not of a label but directly of the analyte. This approach is mostly proposed for bacteria and cell detection. However, although many promising readout strategies have been discussed in numerous publications, rarely have any of them made the step from proof of concept to a practical application, let alone routine use. Graphical Abstract Possible realization of a SERS (Surface-Enhanced Raman Scattering) system for microarray readout.

  17. PROPERTIES OF LARGE-AMPLITUDE VARIABLE STARS DETECTED WITH TWO MICRON ALL SKY SURVEY PUBLIC IMAGES

    SciTech Connect

    Kouzuma, Shinjirou; Yamaoka, Hitoshi

    2009-11-15

    We present a catalog of variable stars in the near-infrared wavelength detected with overlapping regions of the Two Micron All Sky Survey public images, and discuss their properties. The investigated region is in the direction of the Galactic center (-30 deg. {approx}< l {approx}< 20 deg., |b| {approx}< 20 deg.), which covers the entire bulge. We have detected 136 variable stars, of which six are already known and 118 are distributed in the |b| {<=} 5 deg. region. Additionally, 84 variable stars have optical counterparts in Digitized Sky Survey images. The three diagrams (color-magnitude, light variance, and color-color diagrams) indicate that most of the detected variable stars should be large-amplitude and long-period variables such as Mira variables or OH/IR stars. The number density distribution of the detected variable stars implies that they trace the bar structure of the Galactic bulge.

  18. Surface chemistries for antibody microarrays

    SciTech Connect

    Seurynck-Servoss, Shannon L.; Baird, Cheryl L.; Rodland, Karin D.; Zangar, Richard C.

    2007-05-01

    Enzyme-linked immunosorbent assay (ELISA) microarrays promise to be a powerful tool for the detection of disease biomarkers. The original technology for printing ELISA microarray chips and capturing antibodies on slides was derived from the DNA microarray field. However, due to the need to maintain antibody structure and function when immobilized, surface chemistries used for DNA microarrays are not always appropriate for ELISA microarrays. In order to identify better surface chemistries for antibody capture, a number of commercial companies and academic research groups have developed new slide types that could improve antibody function in microarray applications. In this review we compare and contrast the commercially available slide chemistries, as well as highlight some promising recent advances in the field.

  19. Shared probe design and existing microarray reanalysis using PICKY.

    PubMed

    Chou, Hui-Hsien

    2010-04-20

    Large genomes contain families of highly similar genes that cannot be individually identified by microarray probes. This limitation is due to thermodynamic restrictions and cannot be resolved by any computational method. Since gene annotations are updated more frequently than microarrays, another common issue facing microarray users is that existing microarrays must be routinely reanalyzed to determine probes that are still useful with respect to the updated annotations. PICKY 2.0 can design shared probes for sets of genes that cannot be individually identified using unique probes. PICKY 2.0 uses novel algorithms to track sharable regions among genes and to strictly distinguish them from other highly similar but nontarget regions during thermodynamic comparisons. Therefore, PICKY does not sacrifice the quality of shared probes when choosing them. The latest PICKY 2.1 includes the new capability to reanalyze existing microarray probes against updated gene sets to determine probes that are still valid to use. In addition, more precise nonlinear salt effect estimates and other improvements are added, making PICKY 2.1 more versatile to microarray users. Shared probes allow expressed gene family members to be detected; this capability is generally more desirable than not knowing anything about these genes. Shared probes also enable the design of cross-genome microarrays, which facilitate multiple species identification in environmental samples. The new nonlinear salt effect calculation significantly increases the precision of probes at a lower buffer salt concentration, and the probe reanalysis function improves existing microarray result interpretations.

  20. DNA microarrays for comparative genomic hybridization based on DOP-PCR amplification of BAC and PAC clones.

    PubMed

    Fiegler, Heike; Carr, Philippa; Douglas, Eleanor J; Burford, Deborah C; Hunt, Sarah; Scott, Carol E; Smith, James; Vetrie, David; Gorman, Patricia; Tomlinson, Ian P M; Carter, Nigel P

    2003-04-01

    We have designed DOP-PCR primers specifically for the amplification of large insert clones for use in the construction of DNA microarrays. A bioinformatic approach was used to construct primers that were efficient in the general amplification of human DNA but were poor at amplifying E. coli DNA, a common contaminant of DNA preparations from large insert clones. We chose the three most selective primers for use in printing DNA microarrays. DNA combined from the amplification of large insert clones by use of these three primers and spotted onto glass slides showed more than a sixfold increase in the human to E. coli hybridization ratio when compared to the standard DOP-PCR primer, 6MW. The microarrays reproducibly delineated previously characterized gains and deletions in a cancer cell line and identified a small gain not detected by use of conventional CGH. We also describe a method for the bulk testing of the hybridization characteristics of chromosome-specific clones spotted on microarrays by use of DNA amplified from flow-sorted chromosomes. Finally, we describe a set of clones selected from the publicly available Golden Path of the human genome at 1-Mb intervals and a view in the Ensembl genome browser from which data required for the use of these clones in array CGH and other experiments can be downloaded across the Internet.

  1. Lessons learned and unsolved public health problems after large-scale disasters.

    PubMed

    Koscheyev, V S; Leon, G R; Greaves, I A

    1997-01-01

    This paper examines the considerable medical and psychological problems that ensue after disasters in which massive populations are affected for extended and sometimes unknown time periods. The organization of disaster response teams after large-scale disasters is based on experiences as a medical specialist at Chernobyl immediately after this catastrophe. Optimal ways of dealing with the immediate medical and logistical demands as well as long-term public health problems are explored with a particular focus on radiation disasters. Other lessons learned from Chernobyl are explained. Current concerns involve the constant threat of a disaster posed by aging nuclear facilities and nuclear and chemical disarmament activities. The strategies that have been used by various groups in responding to a disaster and dealing with medical and psychological health effects at different disaster stages are evaluated. The emergence of specialized centers in the former Soviet Union to study long-term health effects after radiation accidents are described. Worldwide, there has been relatively little attention paid to mid- and long-term health effects, particularly the psychological stress effects. Problems in conducting longitudinal health research are explored. The use of a mobile diagnostic and continuously operating pre-hospital triage system for rapid health screening of large populations at different stages after a large-scale disaster is advisable. The functional systems of the body to be observed at different stages after a radiation disaster are specified. There is a particularly strong need for continued medical and psychosocial evaluation of radiation-exposed populations over an extended time and a need for international collaboration among investigators.

  2. 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.

  3. Ecotoxicogenomics: Microarray interlaboratory comparability.

    PubMed

    Vidal-Dorsch, Doris E; Bay, Steven M; Moore, Shelly; Layton, Blythe; Mehinto, Alvine C; Vulpe, Chris D; Brown-Augustine, Marianna; Loguinov, Alex; Poynton, Helen; Garcia-Reyero, Natàlia; Perkins, Edward J; Escalon, Lynn; Denslow, Nancy D; Cristina, Colli-Dula R; Doan, Tri; Shukradas, Shweta; Bruno, Joy; Brown, Lorraine; Van Agglen, Graham; Jackman, Paula; Bauer, Megan

    2016-02-01

    Transcriptomic analysis can complement traditional ecotoxicology data by providing mechanistic insight, and by identifying sub-lethal organismal responses and contaminant classes underlying observed toxicity. Before transcriptomic information can be used in monitoring and risk assessment, it is necessary to determine its reproducibility and detect key steps impacting the reliable identification of differentially expressed genes. A custom 15K-probe microarray was used to conduct transcriptomics analyses across six laboratories with estuarine amphipods exposed to cyfluthrin-spiked or control sediments (10 days). Two sample types were generated, one consisted of total RNA extracts (Ex) from exposed and control samples (extracted by one laboratory) and the other consisted of exposed and control whole body amphipods (WB) from which each laboratory extracted RNA. Our findings indicate that gene expression microarray results are repeatable. Differentially expressed data had a higher degree of repeatability across all laboratories in samples with similar RNA quality (Ex) when compared to WB samples with more variable RNA quality. Despite such variability a subset of genes were consistently identified as differentially expressed across all laboratories and sample types. We found that the differences among the individual laboratory results can be attributed to several factors including RNA quality and technical expertise, but the overall results can be improved by following consistent protocols and with appropriate training. Published by Elsevier Ltd.

  4. Applying the 15 Public Health Emergency Preparedness Capabilities to Support Large-Scale Tuberculosis Investigations in Complex Congregate Settings.

    PubMed

    Levy, Alison Jaffe; Toren, Katelynne Gardner; Elsenboss, Carina; Narita, Masahiro

    2017-09-01

    Public Health-Seattle and King County, a metropolitan health department in western Washington, experiences rates of tuberculosis (TB) that are 1.6 times higher than are state and national averages. The department's TB Control Program uses public health emergency management tools and capabilities sustained with Centers for Disease Control and Prevention grant funding to manage large-scale complex case investigations. We have described 3 contact investigations in large congregate settings that the TB Control Program conducted in 2015 and 2016. The program managed the investigations using public health emergency management tools, with support from the Preparedness Program. The 3 investigations encompassed medical evaluation of more than 1600 people, used more than 100 workers, identified nearly 30 individuals with latent TB infection, and prevented an estimated 3 cases of active disease. These incidents exemplify how investments in public health emergency preparedness can enhance health outcomes in traditional areas of public health.

  5. Applying the 15 Public Health Emergency Preparedness Capabilities to Support Large-Scale Tuberculosis Investigations in Complex Congregate Settings

    PubMed Central

    Toren, Katelynne Gardner; Elsenboss, Carina; Narita, Masahiro

    2017-01-01

    Public Health—Seattle and King County, a metropolitan health department in western Washington, experiences rates of tuberculosis (TB) that are 1.6 times higher than are state and national averages. The department’s TB Control Program uses public health emergency management tools and capabilities sustained with Centers for Disease Control and Prevention grant funding to manage large-scale complex case investigations. We have described 3 contact investigations in large congregate settings that the TB Control Program conducted in 2015 and 2016. The program managed the investigations using public health emergency management tools, with support from the Preparedness Program. The 3 investigations encompassed medical evaluation of more than 1600 people, used more than 100 workers, identified nearly 30 individuals with latent TB infection, and prevented an estimated 3 cases of active disease. These incidents exemplify how investments in public health emergency preparedness can enhance health outcomes in traditional areas of public health. PMID:28892445

  6. Annotating nonspecific SAGE tags with microarray data.

    PubMed

    Ge, Xijin; Jung, Yong-Chul; Wu, Qingfa; Kibbe, Warren A; Wang, San Ming

    2006-01-01

    SAGE (serial analysis of gene expression) detects transcripts by extracting short tags from the transcripts. Because of the limited length, many SAGE tags are shared by transcripts from different genes. Relying on sequence information in the general gene expression database has limited power to solve this problem due to the highly heterogeneous nature of the deposited sequences. Considering that the complexity of gene expression at a single tissue level should be much simpler than that in the general expression database, we reasoned that by restricting gene expression to tissue level, the accuracy of gene annotation for the nonspecific SAGE tags should be significantly improved. To test the idea, we developed a tissue-specific SAGE annotation database based on microarray data (). This database contains microarray expression information represented as UniGene clusters for 73 normal human tissues and 18 cancer tissues and cell lines. The nonspecific SAGE tag is first matched to the database by the same tissue type used by both SAGE and microarray analysis; then the multiple UniGene clusters assigned to the nonspecific SAGE tag are searched in the database under the matched tissue type. The UniGene cluster presented solely or at higher expression levels in the database is annotated to represent the specific gene for the nonspecific SAGE tags. The accuracy of gene annotation by this database was largely confirmed by experimental data. Our study shows that microarray data provide a useful source for annotating the nonspecific SAGE tags.

  7. Clustering of local group distances: publication bias or correlated measurements? I. The large Magellanic cloud

    SciTech Connect

    De Grijs, Richard; Wicker, James E.; Bono, Giuseppe

    2014-05-01

    The distance to the Large Magellanic Cloud (LMC) represents a key local rung of the extragalactic distance ladder yet the galaxy's distance modulus has long been an issue of contention, in particular in view of claims that most newly determined distance moduli cluster tightly—and with a small spread—around the 'canonical' distance modulus, (m – M){sub 0} = 18.50 mag. We compiled 233 separate LMC distance determinations published between 1990 and 2013. Our analysis of the individual distance moduli, as well as of their two-year means and standard deviations resulting from this largest data set of LMC distance moduli available to date, focuses specifically on Cepheid and RR Lyrae variable-star tracer populations, as well as on distance estimates based on features in the observational Hertzsprung-Russell diagram. We conclude that strong publication bias is unlikely to have been the main driver of the majority of published LMC distance moduli. However, for a given distance tracer, the body of publications leading to the tightly clustered distances is based on highly non-independent tracer samples and analysis methods, hence leading to significant correlations among the LMC distances reported in subsequent articles. Based on a careful, weighted combination, in a statistical sense, of the main stellar population tracers, we recommend that a slightly adjusted canonical distance modulus of (m – M){sub 0} = 18.49 ± 0.09 mag be used for all practical purposes that require a general distance scale without the need for accuracies of better than a few percent.

  8. Clustering of Local Group Distances: Publication Bias or Correlated Measurements? I. The Large Magellanic Cloud

    NASA Astrophysics Data System (ADS)

    de Grijs, Richard; Wicker, James E.; Bono, Giuseppe

    2014-05-01

    The distance to the Large Magellanic Cloud (LMC) represents a key local rung of the extragalactic distance ladder yet the galaxy's distance modulus has long been an issue of contention, in particular in view of claims that most newly determined distance moduli cluster tightly—and with a small spread—around the "canonical" distance modulus, (m - M)0 = 18.50 mag. We compiled 233 separate LMC distance determinations published between 1990 and 2013. Our analysis of the individual distance moduli, as well as of their two-year means and standard deviations resulting from this largest data set of LMC distance moduli available to date, focuses specifically on Cepheid and RR Lyrae variable-star tracer populations, as well as on distance estimates based on features in the observational Hertzsprung-Russell diagram. We conclude that strong publication bias is unlikely to have been the main driver of the majority of published LMC distance moduli. However, for a given distance tracer, the body of publications leading to the tightly clustered distances is based on highly non-independent tracer samples and analysis methods, hence leading to significant correlations among the LMC distances reported in subsequent articles. Based on a careful, weighted combination, in a statistical sense, of the main stellar population tracers, we recommend that a slightly adjusted canonical distance modulus of (m - M)0 = 18.49 ± 0.09 mag be used for all practical purposes that require a general distance scale without the need for accuracies of better than a few percent.

  9. The contribution of advisory committees and public involvement to large studies: case study

    PubMed Central

    2010-01-01

    Background Many large studies have complex advisory committee structures, yet there is no empirical evidence regarding their optimal composition, scope and contribution. The aim of this study was to inform the committee and advice infrastructure for future research studies. Methods In the context of a five-year study funded by the UK National Institute for Health Research, three advisory committees were formed. In addition, advice was obtained from individual experts. All recommendations received in the start-up phase (first seven months) of the study were recorded, along with the decision about implementation of the recommendation. A particular focus was on the impact of public involvement. Results A total of 172 recommendations were made, including 70 from 20 individual experts. The recommendations were grouped into five emergent themes: Scientific, Pragmatic, Resources, Committee and Collaboration. Most recommendations related to strengthening existing components or adding new components to the study protocol. Very few recommendations either proposed removing study components or contradicted other recommendations. Three 'implementation criteria' were identified: scientific value, pragmatic feasibility, and paradigmatic consistency. 103 (60%) of recommendations were implemented and 25 (15%) were not implemented. The benefits identified by the research team were improved quality and confidence, and the costs were increased cognitive demands, protocol revision time, and slower progress. Conclusions The findings are discussed in the context of the wider literature on public involvement in research. Six recommendations are identified. First, have a clear rationale for each advisory committee expressed as terms of reference, and consider the best balance between committees and individual consultation with experts. Second, an early concern of committees is inter-committee communication, so consider cross-representation and copying minutes between committees. Third

  10. Influence of large changes in public transportation (Transantiago) on the black carbon pollution near streets

    NASA Astrophysics Data System (ADS)

    Gramsch, E.; Le Nir, G.; Araya, M.; Rubio, M. A.; Moreno, F.; Oyola, P.

    2013-02-01

    In 2006 a large transformation was carried out on the public transportation system in Santiago de Chile. The original system (before 2006) had hundreds of bus owners with about 7000 diesel buses. The new system has only 13 firms with about 5900 buses which operate in different parts of the city with little overlap between them. In this work we evaluate the impact of the Transantiago system on the black carbon pollution along four roads directly affected by the modification to the transport system. Measurements were carried out during May-July of 2005 (before Transantiago) and June-July of 2007 (after Transantiago). We have used the Wilcoxon rank-sum test to evaluate black carbon concentration in four streets in year 2005 and 2007. The results show that a statistically significant reduction between year 2005 (before Transantiago) and year 2007 (after Transantiago) in Alameda street, which changed from a mean of 18.8 μg m-3 in 2005 to 11.9 μg m-3 in 2007. In this street there was a decrease in the number of buses as well as the number of private vehicles and an improvement in the technology of public transportation between those years. Other two streets (Usach and Departamental) did not change or experienced a small increase in the black carbon concentration in spite of having less flux of buses in 2007. Eliodoro Yañez Street, which did not have public transportation in 2005 or 2007 experienced a 15% increase in the black carbon concentration between those years. Analysis of the data indicates that the change is related to a decrease in the total number of vehicles or the number of other diesel vehicles in the street rather than a decrease in the number of buses only. These results are an indication that in order to decrease pollution near a street is not enough to reduce the number of buses or improve its quality, but to reduce the total number of vehicles.

  11. Mutational analysis using oligonucleotide microarrays

    PubMed Central

    Hacia, J.; Collins, F.

    1999-01-01

    The development of inexpensive high throughput methods to identify individual DNA sequence differences is important to the future growth of medical genetics. This has become increasingly apparent as epidemiologists, pathologists, and clinical geneticists focus more attention on the molecular basis of complex multifactorial diseases. Such undertakings will rely upon genetic maps based upon newly discovered, common, single nucleotide polymorphisms. Furthermore, candidate gene approaches used in identifying disease associated genes necessitate screening large sequence blocks for changes tracking with the disease state. Even after such genes are isolated, large scale mutational analyses will often be needed for risk assessment studies to define the likely medical consequences of carrying a mutated gene.
This review concentrates on the use of oligonucleotide arrays for hybridisation based comparative sequence analysis. Technological advances within the past decade have made it possible to apply this technology to many different aspects of medical genetics. These applications range from the detection and scoring of single nucleotide polymorphisms to mutational analysis of large genes. Although we discuss published scientific reports, unpublished work from the private sector12 could also significantly affect the future of this technology.


Keywords: mutational analysis; oligonucleotide microarrays; DNA chips PMID:10528850

  12. Deciphering the glycosaminoglycan code with the help of microarrays.

    PubMed

    de Paz, Jose L; Seeberger, Peter H

    2008-07-01

    Carbohydrate microarrays have become a powerful tool to elucidate the biological role of complex sugars. Microarrays are particularly useful for the study of glycosaminoglycans (GAGs), a key class of carbohydrates. The high-throughput chip format enables rapid screening of large numbers of potential GAG sequences produced via a complex biosynthesis while consuming very little sample. Here, we briefly highlight the most recent advances involving GAG microarrays built with synthetic or naturally derived oligosaccharides. These chips are powerful tools for characterizing GAG-protein interactions and determining structure-activity relationships for specific sequences. Thereby, they contribute to decoding the information contained in specific GAG sequences.

  13. Microarrays in cancer research.

    PubMed

    Grant, Geraldine M; Fortney, Amanda; Gorreta, Francesco; Estep, Michael; Del Giacco, Luca; Van Meter, Amy; Christensen, Alan; Appalla, Lakshmi; Naouar, Chahla; Jamison, Curtis; Al-Timimi, Ali; Donovan, Jean; Cooper, James; Garrett, Carleton; Chandhoke, Vikas

    2004-01-01

    Microarray technology has presented the scientific community with a compelling approach that allows for simultaneous evaluation of all cellular processes at once. Cancer, being one of the most challenging diseases due to its polygenic nature, presents itself as a perfect candidate for evaluation by this approach. Several recent articles have provided significant insight into the strengths and limitations of microarrays. Nevertheless, there are strong indications that this approach will provide new molecular markers that could be used in diagnosis and prognosis of cancers. To achieve these goals it is essential that there is a seamless integration of clinical and molecular biological data that allows us to elucidate genes and pathways involved in various cancers. To this effect we are currently evaluating gene expression profiles in human brain, ovarian, breast and hematopoetic, lung, colorectal, head and neck and biliary tract cancers. To address the issues we have a joint team of scientists, doctors and computer scientists from two Virginia Universities and a major healthcare provider. The study has been divided into several focus groups that include; Tissue Bank Clinical & Pathology Laboratory Data, Chip Fabrication, QA/QC, Tissue Devitalization, Database Design and Data Analysis, using multiple microarray platforms. Currently over 300 consenting patients have been enrolled in the study with the largest number being that of breast cancer patients. Clinical data on each patient is being compiled into a secure and interactive relational database and integration of these data elements will be accomplished by a common programming interface. This clinical database contains several key parameters on each patient including demographic (risk factors, nutrition, co-morbidity, familial history), histopathology (non genetic predictors), tumor, treatment and follow-up information. Gene expression data derived from the tissue samples will be linked to this database, which

  14. Assessing the Feasibility of Large-Scale Countercyclical Public Job-Creation. Final Report, Volume II. Activities Suitable for Public Job-Creation and Their Characteristics.

    ERIC Educational Resources Information Center

    Urban Inst., Washington, DC.

    This second of a three-volume report of a study done to assess the feasibility of large-scale, countercyclical public job creation contains chapter 2 of the report on the methods and findings with respect to job-creating activities, their job-creation potential, and related characteristics. (Volume 1, comprised of the report's first chapter,…

  15. Assessing the Feasibility of Large-Scale Countercyclical Public Job-Creation. Final Report, Volume III. Selected Implications of Public Job-Creation.

    ERIC Educational Resources Information Center

    Urban Inst., Washington, DC.

    This last of a three-volume report of a study done to assess the feasibility of large-scale, countercyclical public job creation covers the findings regarding the priorities among projects, indirect employment effects, skill imbalances, and administrative issues; and summarizes the overall findings, conclusions, and recommendations. (Volume 1,…

  16. Publications

    Cancer.gov

    Information about NCI publications including PDQ cancer information for patients and health professionals, patient-education publications, fact sheets, dictionaries, NCI blogs and newsletters and major reports.

  17. DNA Microarray-Based Diagnostics.

    PubMed

    Marzancola, Mahsa Gharibi; Sedighi, Abootaleb; Li, Paul C H

    2016-01-01

    The DNA microarray technology is currently a useful biomedical tool which has been developed for a variety of diagnostic applications. However, the development pathway has not been smooth and the technology has faced some challenges. The reliability of the microarray data and also the clinical utility of the results in the early days were criticized. These criticisms added to the severe competition from other techniques, such as next-generation sequencing (NGS), impacting the growth of microarray-based tests in the molecular diagnostic market.Thanks to the advances in the underlying technologies as well as the tremendous effort offered by the research community and commercial vendors, these challenges have mostly been addressed. Nowadays, the microarray platform has achieved sufficient standardization and method validation as well as efficient probe printing, liquid handling and signal visualization. Integration of various steps of the microarray assay into a harmonized and miniaturized handheld lab-on-a-chip (LOC) device has been a goal for the microarray community. In this respect, notable progress has been achieved in coupling the DNA microarray with the liquid manipulation microsystem as well as the supporting subsystem that will generate the stand-alone LOC device.In this chapter, we discuss the major challenges that microarray technology has faced in its almost two decades of development and also describe the solutions to overcome the challenges. In addition, we review the advancements of the technology, especially the progress toward developing the LOC devices for DNA diagnostic applications.

  18. Voluntary rewards mediate the evolution of pool punishment for maintaining public goods in large populations

    NASA Astrophysics Data System (ADS)

    Sasaki, Tatsuya; Uchida, Satoshi; Chen, Xiaojie

    2015-03-01

    Punishment is a popular tool when governing commons in situations where free riders would otherwise take over. It is well known that sanctioning systems, such as the police and courts, are costly and thus can suffer from those who free ride on other's efforts to maintain the sanctioning systems (second-order free riders). Previous game-theory studies showed that if populations are very large, pool punishment rarely emerges in public good games, even when participation is optional, because of second-order free riders. Here we show that a matching fund for rewarding cooperation leads to the emergence of pool punishment, despite the presence of second-order free riders. We demonstrate that reward funds can pave the way for a transition from a population of free riders to a population of pool punishers. A key factor in promoting the transition is also to reward those who contribute to pool punishment, yet not abstaining from participation. Reward funds eventually vanish in raising pool punishment, which is sustainable by punishing the second-order free riders. This suggests that considering the interdependence of reward and punishment may help to better understand the origins and transitions of social norms and institutions.

  19. Public attitudes regarding large-scale solar energy development in the U.S.

    DOE PAGES

    Carlisle, Juliet E.; Kane, Stephanie L.; Solan, David; ...

    2015-08-01

    Using data collected from both a National sample as well as an oversample in U.S. Southwest, we examine public attitudes toward the construction of utility-scale solar facilities in the U.S. as well as development in one’s own county. Our multivariate analyses assess demographic and sociopsychological factors as well as context in terms of proximity of proposed project by considering the effect of predictors for respondents living in the Southwest versus those from a National sample.We find that the predictors, and impact of the predictors, related to support and opposition to solar development vary in terms of psychological and physical distance.more » Overall, for respondents living in the U.S. Southwest we find that environmentalism, belief that developers receive too many incentives, and trust in project developers to be significantly related to support and opposition to solar development, in general. When Southwest respondents consider large-scale solar development in their county, the influence of these variables changes so that property value, race, and age only yield influence. Differential effects occur for respondents of our National sample.We believe our findings to be relevant for those outside the U.S. due to the considerable growth PV solar has experienced in the last decade, especially in China, Japan, Germany, and the U.S.« less

  20. Public attitudes regarding large-scale solar energy development in the U.S.

    SciTech Connect

    Carlisle, Juliet E.; Kane, Stephanie L.; Solan, David; Bowman, Madelaine; Joe, Jeffrey C.

    2015-08-01

    Using data collected from both a National sample as well as an oversample in U.S. Southwest, we examine public attitudes toward the construction of utility-scale solar facilities in the U.S. as well as development in one’s own county. Our multivariate analyses assess demographic and sociopsychological factors as well as context in terms of proximity of proposed project by considering the effect of predictors for respondents living in the Southwest versus those from a National sample.We find that the predictors, and impact of the predictors, related to support and opposition to solar development vary in terms of psychological and physical distance. Overall, for respondents living in the U.S. Southwest we find that environmentalism, belief that developers receive too many incentives, and trust in project developers to be significantly related to support and opposition to solar development, in general. When Southwest respondents consider large-scale solar development in their county, the influence of these variables changes so that property value, race, and age only yield influence. Differential effects occur for respondents of our National sample.We believe our findings to be relevant for those outside the U.S. due to the considerable growth PV solar has experienced in the last decade, especially in China, Japan, Germany, and the U.S.

  1. Voluntary rewards mediate the evolution of pool punishment for maintaining public goods in large populations.

    PubMed

    Sasaki, Tatsuya; Uchida, Satoshi; Chen, Xiaojie

    2015-03-10

    Punishment is a popular tool when governing commons in situations where free riders would otherwise take over. It is well known that sanctioning systems, such as the police and courts, are costly and thus can suffer from those who free ride on other's efforts to maintain the sanctioning systems (second-order free riders). Previous game-theory studies showed that if populations are very large, pool punishment rarely emerges in public good games, even when participation is optional, because of second-order free riders. Here we show that a matching fund for rewarding cooperation leads to the emergence of pool punishment, despite the presence of second-order free riders. We demonstrate that reward funds can pave the way for a transition from a population of free riders to a population of pool punishers. A key factor in promoting the transition is also to reward those who contribute to pool punishment, yet not abstaining from participation. Reward funds eventually vanish in raising pool punishment, which is sustainable by punishing the second-order free riders. This suggests that considering the interdependence of reward and punishment may help to better understand the origins and transitions of social norms and institutions.

  2. Voluntary rewards mediate the evolution of pool punishment for maintaining public goods in large populations

    PubMed Central

    Sasaki, Tatsuya; Uchida, Satoshi; Chen, Xiaojie

    2015-01-01

    Punishment is a popular tool when governing commons in situations where free riders would otherwise take over. It is well known that sanctioning systems, such as the police and courts, are costly and thus can suffer from those who free ride on other's efforts to maintain the sanctioning systems (second-order free riders). Previous game-theory studies showed that if populations are very large, pool punishment rarely emerges in public good games, even when participation is optional, because of second-order free riders. Here we show that a matching fund for rewarding cooperation leads to the emergence of pool punishment, despite the presence of second-order free riders. We demonstrate that reward funds can pave the way for a transition from a population of free riders to a population of pool punishers. A key factor in promoting the transition is also to reward those who contribute to pool punishment, yet not abstaining from participation. Reward funds eventually vanish in raising pool punishment, which is sustainable by punishing the second-order free riders. This suggests that considering the interdependence of reward and punishment may help to better understand the origins and transitions of social norms and institutions. PMID:25753335

  3. Characteristics of physicians receiving large payments from pharmaceutical companies and the accuracy of their disclosures in publications: an observational study.

    PubMed

    Norris, Susan L; Holmer, Haley K; Ogden, Lauren A; Burda, Brittany U; Fu, Rongwei

    2012-09-26

    Financial relationships between physicians and industry are extensive and public reporting of industry payments to physicians is now occurring. Our objectives were to describe physician recipients of large total payments from these seven companies, and to examine discrepancies between these payments and conflict of interest (COI) disclosures in authors' concurrent publications. The investigative journalism organization, ProPublica, compiled the Dollars for Docs database of payments to individuals from publically available data from seven US pharmaceutical companies during the period 2009 to 2010. We examined the cohort of 373 physicians in this database who each received USD $100,000 or more in the reporting period 2009 to 2010. These physicians received a total of $52,600,624 during this period (mean payment per physician $141,020). The predominant specialties were internal medicine and psychiatry. 147 of these physicians authored a total of 134 publications in the first quarter of 2011 and 77% (103) of these publications provided a COI disclosure. 69% of the 103 publications did not contain disclosures of the payment listed in the Dollars for Docs database. With increased public reporting of industry payments to physicians, it is apparent that large sums are being paid for services such as consulting and peer education. In over two-thirds of publications where COI disclosures were provided, the disclosures by physician authors did not include industry payments that were documented in the Dollars for Docs database.

  4. Characteristics of physicians receiving large payments from pharmaceutical companies and the accuracy of their disclosures in publications: an observational study

    PubMed Central

    2012-01-01

    Background Financial relationships between physicians and industry are extensive and public reporting of industry payments to physicians is now occurring. Our objectives were to describe physician recipients of large total payments from these seven companies, and to examine discrepancies between these payments and conflict of interest (COI) disclosures in authors’ concurrent publications. Methods The investigative journalism organization, ProPublica, compiled the Dollars for Docs database of payments to individuals from publically available data from seven US pharmaceutical companies during the period 2009 to 2010. We examined the cohort of 373 physicians in this database who each received USD $100,000 or more in the reporting period 2009 to 2010. Results These physicians received a total of $52,600,624 during this period (mean payment per physician $141,020). The predominant specialties were internal medicine and psychiatry. 147 of these physicians authored a total of 134 publications in the first quarter of 2011 and 77% (103) of these publications provided a COI disclosure. 69% of the 103 publications did not contain disclosures of the payment listed in the Dollars for Docs database. Conclusions With increased public reporting of industry payments to physicians, it is apparent that large sums are being paid for services such as consulting and peer education. In over two-thirds of publications where COI disclosures were provided, the disclosures by physician authors did not include industry payments that were documented in the Dollars for Docs database. PMID:23013260

  5. Identifying Fishes through DNA Barcodes and Microarrays

    PubMed Central

    Kochzius, Marc; Seidel, Christian; Antoniou, Aglaia; Botla, Sandeep Kumar; Campo, Daniel; Cariani, Alessia; Vazquez, Eva Garcia; Hauschild, Janet; Hervet, Caroline; Hjörleifsdottir, Sigridur; Hreggvidsson, Gudmundur; Kappel, Kristina; Landi, Monica; Magoulas, Antonios; Marteinsson, Viggo; Nölte, Manfred; Planes, Serge; Tinti, Fausto; Turan, Cemal; Venugopal, Moleyur N.; Weber, Hannes; Blohm, Dietmar

    2010-01-01

    Background International fish trade reached an import value of 62.8 billion Euro in 2006, of which 44.6% are covered by the European Union. Species identification is a key problem throughout the life cycle of fishes: from eggs and larvae to adults in fisheries research and control, as well as processed fish products in consumer protection. Methodology/Principal Findings This study aims to evaluate the applicability of the three mitochondrial genes 16S rRNA (16S), cytochrome b (cyt b), and cytochrome oxidase subunit I (COI) for the identification of 50 European marine fish species by combining techniques of “DNA barcoding” and microarrays. In a DNA barcoding approach, neighbour Joining (NJ) phylogenetic trees of 369 16S, 212 cyt b, and 447 COI sequences indicated that cyt b and COI are suitable for unambiguous identification, whereas 16S failed to discriminate closely related flatfish and gurnard species. In course of probe design for DNA microarray development, each of the markers yielded a high number of potentially species-specific probes in silico, although many of them were rejected based on microarray hybridisation experiments. None of the markers provided probes to discriminate the sibling flatfish and gurnard species. However, since 16S-probes were less negatively influenced by the “position of label” effect and showed the lowest rejection rate and the highest mean signal intensity, 16S is more suitable for DNA microarray probe design than cty b and COI. The large portion of rejected COI-probes after hybridisation experiments (>90%) renders the DNA barcoding marker as rather unsuitable for this high-throughput technology. Conclusions/Significance Based on these data, a DNA microarray containing 64 functional oligonucleotide probes for the identification of 30 out of the 50 fish species investigated was developed. It represents the next step towards an automated and easy-to-handle method to identify fish, ichthyoplankton, and fish products. PMID

  6. Analysis of Microarray and RNA-seq Expression Profiling Data.

    PubMed

    Hung, Jui-Hung; Weng, Zhiping

    2017-03-01

    Gene expression profiling refers to the simultaneous measurement of the expression levels of a large number of genes (often all genes in a genome), typically in multiple experiments spanning a variety of cell types, treatments, or environmental conditions. Expression profiling is accomplished by assaying mRNA levels with microarrays or next-generation sequencing technologies (RNA-seq). This introduction describes normalization and analysis of data generated from microarray or RNA-seq experiments.

  7. Integrating Microarray Data and GRNs.

    PubMed

    Koumakis, L; Potamias, G; Tsiknakis, M; Zervakis, M; Moustakis, V

    2016-01-01

    With the completion of the Human Genome Project and the emergence of high-throughput technologies, a vast amount of molecular and biological data are being produced. Two of the most important and significant data sources come from microarray gene-expression experiments and respective databanks (e,g., Gene Expression Omnibus-GEO (http://www.ncbi.nlm.nih.gov/geo)), and from molecular pathways and Gene Regulatory Networks (GRNs) stored and curated in public (e.g., Kyoto Encyclopedia of Genes and Genomes-KEGG (http://www.genome.jp/kegg/pathway.html), Reactome (http://www.reactome.org/ReactomeGWT/entrypoint.html)) as well as in commercial repositories (e.g., Ingenuity IPA (http://www.ingenuity.com/products/ipa)). The association of these two sources aims to give new insight in disease understanding and reveal new molecular targets in the treatment of specific phenotypes.Three major research lines and respective efforts that try to utilize and combine data from both of these sources could be identified, namely: (1) de novo reconstruction of GRNs, (2) identification of Gene-signatures, and (3) identification of differentially expressed GRN functional paths (i.e., sub-GRN paths that distinguish between different phenotypes). In this chapter, we give an overview of the existing methods that support the different types of gene-expression and GRN integration with a focus on methodologies that aim to identify phenotype-discriminant GRNs or subnetworks, and we also present our methodology.

  8. Microintaglio Printing for Soft Lithography-Based in Situ Microarrays.

    PubMed

    Biyani, Manish; Ichiki, Takanori

    2015-07-14

    Advances in lithographic approaches to fabricating bio-microarrays have been extensively explored over the last two decades. However, the need for pattern flexibility, a high density, a high resolution, affordability and on-demand fabrication is promoting the development of unconventional routes for microarray fabrication. This review highlights the development and uses of a new molecular lithography approach, called "microintaglio printing technology", for large-scale bio-microarray fabrication using a microreactor array (µRA)-based chip consisting of uniformly-arranged, femtoliter-size µRA molds. In this method, a single-molecule-amplified DNA microarray pattern is self-assembled onto a µRA mold and subsequently converted into a messenger RNA or protein microarray pattern by simultaneously producing and transferring (immobilizing) a messenger RNA or a protein from a µRA mold to a glass surface. Microintaglio printing allows the self-assembly and patterning of in situ-synthesized biomolecules into high-density (kilo-giga-density), ordered arrays on a chip surface with µm-order precision. This holistic aim, which is difficult to achieve using conventional printing and microarray approaches, is expected to revolutionize and reshape proteomics. This review is not written comprehensively, but rather substantively, highlighting the versatility of microintaglio printing for developing a prerequisite platform for microarray technology for the postgenomic era.

  9. Microintaglio Printing for Soft Lithography-Based in Situ Microarrays

    PubMed Central

    Biyani, Manish; Ichiki, Takanori

    2015-01-01

    Advances in lithographic approaches to fabricating bio-microarrays have been extensively explored over the last two decades. However, the need for pattern flexibility, a high density, a high resolution, affordability and on-demand fabrication is promoting the development of unconventional routes for microarray fabrication. This review highlights the development and uses of a new molecular lithography approach, called “microintaglio printing technology”, for large-scale bio-microarray fabrication using a microreactor array (µRA)-based chip consisting of uniformly-arranged, femtoliter-size µRA molds. In this method, a single-molecule-amplified DNA microarray pattern is self-assembled onto a µRA mold and subsequently converted into a messenger RNA or protein microarray pattern by simultaneously producing and transferring (immobilizing) a messenger RNA or a protein from a µRA mold to a glass surface. Microintaglio printing allows the self-assembly and patterning of in situ-synthesized biomolecules into high-density (kilo-giga-density), ordered arrays on a chip surface with µm-order precision. This holistic aim, which is difficult to achieve using conventional printing and microarray approaches, is expected to revolutionize and reshape proteomics. This review is not written comprehensively, but rather substantively, highlighting the versatility of microintaglio printing for developing a prerequisite platform for microarray technology for the postgenomic era. PMID:27600226

  10. Differences in STEM doctoral publication by ethnicity, gender and academic field at a large public research university.

    PubMed

    Mendoza-Denton, Rodolfo; Patt, Colette; Fisher, Aaron; Eppig, Andrew; Young, Ira; Smith, Andrew; Richards, Mark A

    2017-01-01

    Two independent surveys of PhD students in STEM fields at the University of California, Berkeley, indicate that underrepresented minorities (URMs) publish at significantly lower rates than non-URM males, placing the former at a significant disadvantage as they compete for postdoctoral and faculty positions. Differences as a function of gender reveal a similar, though less consistent, pattern. A conspicuous exception is Berkeley's College of Chemistry, where publication rates are tightly clustered as a function of ethnicity and gender, and where PhD students experience a highly structured program that includes early and systematic involvement in research, as well as clear expectations for publishing. Social science research supports the hypothesis that this more structured environment hastens the successful induction of diverse groups into the high-performance STEM academic track.

  11. Going Public: Who Leaves a Large, Longstanding, and Widely Available Urban Voucher Program?

    ERIC Educational Resources Information Center

    Cowen, Joshua M.; Fleming, David J.; Witte, John F.; Wolf, Patrick J.

    2012-01-01

    This article contributes to research concerning the determinants of student mobility between public and private schools. The authors analyze a unique set of data collected as part of a new evaluation of Milwaukee's citywide voucher program. The authors find several important patterns. Students who switch from the private to the public sector were…

  12. Reverse Phase Protein Microarrays.

    PubMed

    Baldelli, Elisa; Calvert, Valerie; Hodge, Alex; VanMeter, Amy; Petricoin, Emanuel F; Pierobon, Mariaelena

    2017-01-01

    While genes and RNA encode information about cellular status, proteins are considered the engine of the cellular machine, as they are the effective elements that drive all cellular functions including proliferation, migration, differentiation, and apoptosis. Consequently, investigations of the cellular protein network are considered a fundamental tool for understanding cellular functions.Alteration of the cellular homeostasis driven by elaborate intra- and extracellular interactions has become one of the most studied fields in the era of personalized medicine and targeted therapy. Increasing interest has been focused on developing and improving proteomic technologies that are suitable for analysis of clinical samples. In this context, reverse-phase protein microarrays (RPPA) is a sensitive, quantitative, high-throughput immunoassay for protein analyses of tissue samples, cells, and body fluids.RPPA is well suited for broad proteomic profiling and is capable of capturing protein activation as well as biochemical reactions such as phosphorylation, glycosylation, ubiquitination, protein cleavage, and conformational alterations across hundreds of samples using a limited amount of biological material. For these reasons, RPPA represents a valid tool for protein analyses and generates data that help elucidate the functional signaling architecture through protein-protein interaction and protein activation mapping for the identification of critical nodes for individualized or combinatorial targeted therapy.

  13. Emerging technology of in situ cell free expression protein microarrays.

    PubMed

    Nand, Amita; Gautam, Anju; Pérez, Javier Batista; Merino, Alejandro; Zhu, Jinsong

    2012-02-01

    Recently, in situ protein microarrays have been developed for large scale analysis and high throughput studies of proteins. In situ protein microarrays produce proteins directly on the solid surface from pre-arrayed DNA or RNA. The advances in in situ protein microarrays are exemplified by the ease of cDNA cloning and cell free protein expression. These technologies can evaluate, validate and monitor protein in a cost effective manner and address the issue of a high quality protein supply to use in the array. Here we review the importance of recently employed methods: PISA (protein in situ array), DAPA (DNA array to protein array), NAPPA (nucleic acid programmable protein array) and TUSTER microarrays and the role of these methods in proteomics.

  14. IgE Epitope Mapping Using Peptide Microarray Immunoassay.

    PubMed

    Lin, Jing; Sampson, Hugh A

    2017-01-01

    IgE epitope mapping has the potential to become an additional tool for food allergy diagnosis/prognosis and to lead to a better understanding of the pathogenesis and tolerance induction of food allergy. Due to its ability to screen thousands of targets in parallel using small volumes of sample, peptide microarray has greatly facilitated large-scale IgE epitope mapping. In the past 10 years, we have developed and optimized a reliable and sensitive peptide microarray immunoassay, which has been successfully applied for IgE epitope mapping of many food allergens in our lab. Here, we describe the method of performing the peptide microarray immunoassay for IgE epitope mapping. In addition, we have upgraded the microarray platform to measure antibody affinity by adding one additional competition step, which is also described in this chapter.

  15. Demystified...tissue microarray technology.

    PubMed

    Packeisen, J; Korsching, E; Herbst, H; Boecker, W; Buerger, H

    2003-08-01

    Several "high throughput methods" have been introduced into research and routine laboratories during the past decade. Providing a new approach to the analysis of genomic alterations and RNA or protein expression patterns, these new techniques generate a plethora of new data in a relatively short time, and promise to deliver clues to the diagnosis and treatment of human cancer. Along with these revolutionary developments, new tools for the interpretation of these large sets of data became necessary and are now widely available. Tissue microarray (TMA) technology is one of these new tools. It is based on the idea of applying miniaturisation and a high throughput approach to the analysis of intact tissues. The potential and the scientific value of TMAs in modern research have been demonstrated in a logarithmically increasing number of studies. The spectrum for additional applications is widening rapidly, and comprises quality control in histotechnology, longterm tissue banking, and the continuing education of pathologists. This review covers the basic technical aspects of TMA production and discusses the current and potential future applications of TMA technology.

  16. "Incentives for Managed Growth": A Case Study of Incentives-Based Planning and Budgeting in a Large Public Research University

    ERIC Educational Resources Information Center

    Hearn, James C.; Lewis, Darrell R.; Kallsen, Lincoln; Holdsworth, Janet M.; Jones, Lisa M.

    2006-01-01

    Implementing an incentives-based budget system at a large public research university significantly redirected internal funds while producing notable organizational and financial surprises. For example, units did not increase their "hoarding" of students, contrary to some expectations. The findings point to several issues for further…

  17. Perception of Business Studies Teachers on the Infuence of Large Class Size in Public Secondary Schools in Yobe State, Nigeria

    ERIC Educational Resources Information Center

    Mamman, Jummai; Chadi, Aishatu Mohammad; Jirgi, Ibrahim

    2015-01-01

    This is a survey study conducted to determine the perception of business studies teacher's on the influence of large class size in Yobe state public secondary school. Three research questions were raised to guide the study. The population comprised of one hundred and twenty (120) business studies teachers from one hundred and five (105) Secondary…

  18. Demography Is Not Destiny: Increasing the Graduation Rates of Low-Income College Students at Large Public Universities

    ERIC Educational Resources Information Center

    Engle, Jennifer; O'Brien, Colleen

    2007-01-01

    What accounts for the differences in retention and graduation rates among large public colleges and universities that serve high numbers of low-income students? To answer this question, the Pell Institute for the Study of Opportunity in Higher Education has conducted two studies to examine the institutional characteristics, practices, and policies…

  19. "Incentives for Managed Growth": A Case Study of Incentives-Based Planning and Budgeting in a Large Public Research University

    ERIC Educational Resources Information Center

    Hearn, James C.; Lewis, Darrell R.; Kallsen, Lincoln; Holdsworth, Janet M.; Jones, Lisa M.

    2006-01-01

    Implementing an incentives-based budget system at a large public research university significantly redirected internal funds while producing notable organizational and financial surprises. For example, units did not increase their "hoarding" of students, contrary to some expectations. The findings point to several issues for further…

  20. An Investigation of Leadership in a Professional Learning Community: A Case Study of a Large, Suburban, Public Middle School

    ERIC Educational Resources Information Center

    Liebman, Howard; Maldonado, Nancy; Lacey, Candace H.; Thompson, Steve

    2005-01-01

    This qualitative case study investigated a large, suburban, public middle school focusing on educators' perceptions of leadership within their professional learning community. Participants included the principal, administrative team, and key faculty members. Data were collected using semi-structured interviews and were analyzed by hand coding and…

  1. Detection of viruses in used ventilation filters from two large public buildings.

    PubMed

    Goyal, Sagar M; Anantharaman, Senthilvelan; Ramakrishnan, M A; Sajja, Suchitra; Kim, Seung Won; Stanley, Nicholas J; Farnsworth, James E; Kuehn, Thomas H; Raynor, Peter C

    2011-09-01

    Viral and bacterial pathogens may be present in the air after being released from infected individuals and animals. Filters are installed in the heating, ventilation, and air-conditioning (HVAC) systems of buildings to protect ventilation equipment and maintain healthy indoor air quality. These filters process enormous volumes of air. This study was undertaken to determine the utility of sampling used ventilation filters to assess the types and concentrations of virus aerosols present in buildings. The HVAC filters from 2 large public buildings in Minneapolis and Seattle were sampled to determine the presence of human respiratory viruses and viruses with bioterrorism potential. Four air-handling units were selected from each building, and a total of 64 prefilters and final filters were tested for the presence of influenza A, influenza B, respiratory syncytial, corona, parainfluenza 1-3, adeno, orthopox, entero, Ebola, Marburg, Lassa fever, Machupo, eastern equine encephalitis, western equine encephalitis, and Venezuelan equine encephalitis viruses. Representative pieces of each filter were cut and eluted with a buffer solution. Attempts were made to detect viruses by inoculation of these eluates in cell cultures (Vero, MDCK, and RK-13) and specific pathogen-free embryonated chicken eggs. Two passages of eluates in cell cultures or these eggs did not reveal the presence of any live virus. The eluates were also examined by polymerase chain reaction or reverse-transcription polymerase chain reaction to detect the presence of viral DNA or RNA, respectively. Nine of the 64 filters tested were positive for influenza A virus, 2 filters were positive for influenza B virus, and 1 filter was positive for parainfluenza virus 1. These findings indicate that existing building HVAC filters may be used as a method of detection for airborne viruses. As integrated long-term bioaerosol sampling devices, they may yield valuable information on the epidemiology and aerobiology of

  2. Assessing the Eventual Publication of Clinical Trial Abstracts Submitted to a Large Annual Oncology Meeting.

    PubMed

    Massey, Paul R; Wang, Ruibin; Prasad, Vinay; Bates, Susan E; Fojo, Tito

    2016-03-01

    Despite the ethical imperative to publish clinical trials when human subjects are involved, such data frequently remain unpublished. The objectives were to tabulate the rate and ascertain factors associated with eventual publication of clinical trial results reported as abstracts in the Proceedings of the American Society of Clinical Oncology (American Society of Clinical Oncology). Abstracts describing clinical trials for patients with breast, lung, colorectal, ovarian, and prostate cancer from 2009 to 2011 were identified by using a comprehensive online database (http://meetinglibrary.asco.org/abstracts). Abstracts included reported results of a treatment or intervention assessed in a discrete, prospective clinical trial. Publication status at 4-6 years was determined by using a standardized search of PubMed. Primary outcomes were the rate of publication for abstracts of randomized and nonrandomized clinical trials. Secondary outcomes included factors influencing the publication of results. A total of 1,075 abstracts describing 378 randomized and 697 nonrandomized clinical trials were evaluated. Across all years, 75% of randomized and 54% of nonrandomized trials were published, with an overall publication rate of 61%. Sample size was a statistically significant predictor of publication for both randomized and nonrandomized trials (odds ratio [OR] per increase of 100 participants = 1.23 [1.11-1.36], p < .001; and 1.64 [1.15-2.34], p = .006, respectively). Among randomized studies, an industry coauthor or involvement of a cooperative group increased the likelihood of publication (OR 2.37, p = .013; and 2.21, p = .01, respectively). Among nonrandomized studies, phase II trials were more likely to be published than phase I (p < .001). Use of an experimental agent was not a predictor of publication in randomized (OR 0.76 [0.38-1.52]; p = .441) or nonrandomized trials (OR 0.89 [0.61-1.29]; p = .532). This is the largest reported study examining why oncology trials are

  3. Public knowledge and preventive behavior during a large-scale Salmonella outbreak: results from an online survey in the Netherlands

    PubMed Central

    2014-01-01

    Background Food-borne Salmonella infections are a worldwide concern. During a large-scale outbreak, it is important that the public follows preventive advice. To increase compliance, insight in how the public gathers its knowledge and which factors determine whether or not an individual complies with preventive advice is crucial. Methods In 2012, contaminated salmon caused a large Salmonella Thompson outbreak in the Netherlands. During the outbreak, we conducted an online survey (n = 1,057) to assess the general public’s perceptions, knowledge, preventive behavior and sources of information. Results Respondents perceived Salmonella infections and the 2012 outbreak as severe (m = 4.21; five-point scale with 5 as severe). Their knowledge regarding common food sources, the incubation period and regular treatment of Salmonella (gastro-enteritis) was relatively low (e.g., only 28.7% knew that Salmonella is not normally treated with antibiotics). Preventive behavior differed widely, and the majority (64.7%) did not check for contaminated salmon at home. Most information about the outbreak was gathered through traditional media and news and newspaper websites. This was mostly determined by time spent on the medium. Social media played a marginal role. Wikipedia seemed a potentially important source of information. Conclusions To persuade the public to take preventive actions, public health organizations should deliver their message primarily through mass media. Wikipedia seems a promising instrument for educating the public about food-borne Salmonella. PMID:24479614

  4. Gene expression profiling in peanut using oligonucleotide microarrays

    USDA-ARS?s Scientific Manuscript database

    Transcriptome expression analysis in peanut to date has been limited to a relatively small set of genes and only recently have a moderately significant number of ESTs been released into the public domain. Utilization of these ESTs for the oligonucleotide microarrays provides a means to investigate l...

  5. Microarray Analysis Dataset

    EPA Pesticide Factsheets

    This file contains a link for Gene Expression Omnibus and the GSE designations for the publicly available gene expression data used in the study and reflected in Figures 6 and 7 for the Das et al., 2016 paper.This dataset is associated with the following publication:Das, K., C. Wood, M. Lin, A.A. Starkov, C. Lau, K.B. Wallace, C. Corton, and B. Abbott. Perfluoroalky acids-induced liver steatosis: Effects on genes controlling lipid homeostasis. TOXICOLOGY. Elsevier Science Ltd, New York, NY, USA, 378: 32-52, (2017).

  6. Skin cancer has a large impact on our public hospitals but prevention programs continue to demonstrate strong economic credentials.

    PubMed

    Shih, Sophy T F; Carter, Rob; Heward, Sue; Sinclair, Craig

    2017-08-01

    While skin cancer is still the most common cancer in Australia, important information gaps remain. This paper addresses two gaps: i) the cost impact on public hospitals; and ii) an up-to-date assessment of economic credentials for prevention. A prevalence-based cost approach was undertaken in public hospitals in Victoria. Costs were estimated for inpatient admissions, using State service statistics, and outpatient services based on attendance at three hospitals in 2012-13. Cost-effectiveness for prevention was estimated from 'observed vs expected' analysis, together with program expenditure data. Combining inpatient and outpatient costs, total annual costs for Victoria were $48 million to $56 million. The SunSmart program is estimated to have prevented more than 43,000 skin cancers between 1988 and 2010, a net cost saving of $92 million. Skin cancer treatment in public hospitals ($9.20∼$10.39 per head/year) was 30-times current public funding in skin cancer prevention ($0.37 per head/year). At about $50 million per year for hospitals in Victoria alone, the cost burden of a largely preventable disease is substantial. Skin cancer prevention remains highly cost-effective, yet underfunded. Implications for public health: Increased funding for skin cancer prevention must be kept high on the public health agenda. Hospitals would also benefit from being able to redirect resources to non-preventable conditions. © 2017 The Authors.

  7. Large-Scale Public Transcriptomic Data Mining Reveals a Tight Connection between the Transport of Nitrogen and Other Transport Processes in Arabidopsis.

    PubMed

    He, Fei; Karve, Abhijit A; Maslov, Sergei; Babst, Benjamin A

    2016-01-01

    Movement of nitrogen to the plant tissues where it is needed for growth is an important contribution to nitrogen use efficiency. However, we have very limited knowledge about the mechanisms of nitrogen transport. Loading of nitrogen into the xylem and/or phloem by transporter proteins is likely important, but there are several families of genes that encode transporters of nitrogenous molecules (collectively referred to as N transporters here), each comprised of many gene members. In this study, we leveraged publicly available microarray data of Arabidopsis to investigate the gene networks of N transporters to elucidate their possible biological roles. First, we showed that tissue-specificity of nitrogen (N) transporters was well reflected among the public microarray data. Then, we built coexpression networks of N transporters, which showed relationships between N transporters and particular aspects of plant metabolism, such as phenylpropanoid biosynthesis and carbohydrate metabolism. Furthermore, genes associated with several biological pathways were found to be tightly coexpressed with N transporters in different tissues. Our coexpression networks provide information at the systems-level that will serve as a resource for future investigation of nitrogen transport systems in plants, including candidate gene clusters that may work together in related biological roles.

  8. Large-Scale Public Transcriptomic Data Mining Reveals a Tight Connection between the Transport of Nitrogen and Other Transport Processes in Arabidopsis

    PubMed Central

    He, Fei; Karve, Abhijit A.; Maslov, Sergei; Babst, Benjamin A.

    2016-01-01

    Movement of nitrogen to the plant tissues where it is needed for growth is an important contribution to nitrogen use efficiency. However, we have very limited knowledge about the mechanisms of nitrogen transport. Loading of nitrogen into the xylem and/or phloem by transporter proteins is likely important, but there are several families of genes that encode transporters of nitrogenous molecules (collectively referred to as N transporters here), each comprised of many gene members. In this study, we leveraged publicly available microarray data of Arabidopsis to investigate the gene networks of N transporters to elucidate their possible biological roles. First, we showed that tissue-specificity of nitrogen (N) transporters was well reflected among the public microarray data. Then, we built coexpression networks of N transporters, which showed relationships between N transporters and particular aspects of plant metabolism, such as phenylpropanoid biosynthesis and carbohydrate metabolism. Furthermore, genes associated with several biological pathways were found to be tightly coexpressed with N transporters in different tissues. Our coexpression networks provide information at the systems-level that will serve as a resource for future investigation of nitrogen transport systems in plants, including candidate gene clusters that may work together in related biological roles. PMID:27563305

  9. Challenges for MicroRNA Microarray Data Analysis

    PubMed Central

    Wang, Bin; Xi, Yaguang

    2013-01-01

    Microarray is a high throughput discovery tool that has been broadly used for genomic research. Probe-target hybridization is the central concept of this technology to determine the relative abundance of nucleic acid sequences through fluorescence-based detection. In microarray experiments, variations of expression measurements can be attributed to many different sources that influence the stability and reproducibility of microarray platforms. Normalization is an essential step to reduce non-biological errors and to convert raw image data from multiple arrays (channels) to quality data for further analysis. In general, for the traditional microarray analysis, most established normalization methods are based on two assumptions: (1) the total number of target genes is large enough (>10,000); and (2) the expression level of the majority of genes is kept constant. However, microRNA (miRNA) arrays are usually spotted in low density, due to the fact that the total number of miRNAs is less than 2,000 and the majority of miRNAs are weakly or not expressed. As a result, normalization methods based on the above two assumptions are not applicable to miRNA profiling studies. In this review, we discuss a few representative microarray platforms on the market for miRNA profiling and compare the traditional methods with a few novel strategies specific for miRNA microarrays. PMID:24163754

  10. Large Scale Pedagogical Transformation as Widespread Cultural Change in Mexican Public Schools

    ERIC Educational Resources Information Center

    Rincón-Gallardo, Santiago

    2016-01-01

    This article examines how and under what conditions a new pedagogy can spread at scale using the Learning Community Project (LCP) in Mexico as a case study. Started as a small-scale, grassroots pedagogical change initiative in a handful of public schools, LCP evolved over an 8-year period into a national policy that spread its pedagogy of tutorial…

  11. [Nurses of large public hospitals in Rio de Janeiro: socio demographic and work related characteristics].

    PubMed

    Griep, Rosane Härter; da Fonseca, Maria de Jesus Mendes; Melo, Enirtes Caetano Prates; Portela, Luciana Fernandes; Rotenberg, Lucia

    2013-09-01

    The study aimed at analyzing socio-demographic and working characteristics of nurses from public hospitals. It was carried out a cross-sectional study, involving 3.229 nurses from the eighteen largest public hospitals of the city of Rio de Janeiro. It was observed a feminine predominance (87.3%), with mean age of 39.9 ± 10 years. Around 7% referred having master or doctorate degree, 58.5% got their degree from public institutions and 24.5% used to work at the health sector before becoming nurses. Half the group has thought of abandoning their career, and almost a quarter is unsatisfied with their profession. Around 10% searched for a job outside nursing area in the previous month and 30% searched for a job in the same working area. Night work, engagement in more than one job and long professional work hours were more frequently found among men. The study has pointed challengeable aspects of nurses' profession. Results can subsidize support strategies to improve the working conditions in public hospitals due to their comprehensiveness.

  12. Large Scale Pedagogical Transformation as Widespread Cultural Change in Mexican Public Schools

    ERIC Educational Resources Information Center

    Rincón-Gallardo, Santiago

    2016-01-01

    This article examines how and under what conditions a new pedagogy can spread at scale using the Learning Community Project (LCP) in Mexico as a case study. Started as a small-scale, grassroots pedagogical change initiative in a handful of public schools, LCP evolved over an 8-year period into a national policy that spread its pedagogy of tutorial…

  13. Residential Learning Outcomes: Analysis Using the College Student Experiences Questionnaire at a Large Public Research University

    ERIC Educational Resources Information Center

    Murphy, Cari

    2010-01-01

    The creation of learning outcomes inside and outside of the classroom on college campuses has been a growing trend based on a variety of publications which encouraged the fostering of diverse types learning and the measurement of student learning outside of the classroom (ACPA, 1994; Keeling, 2004). The creation of the learning outcomes is a…

  14. Assessing the Eventual Publication of Clinical Trial Abstracts Submitted to a Large Annual Oncology Meeting

    PubMed Central

    Wang, Ruibin; Prasad, Vinay; Bates, Susan E.; Fojo, Tito

    2016-01-01

    Background. Despite the ethical imperative to publish clinical trials when human subjects are involved, such data frequently remain unpublished. The objectives were to tabulate the rate and ascertain factors associated with eventual publication of clinical trial results reported as abstracts in the Proceedings of the American Society of Clinical Oncology (American Society of Clinical Oncology). Materials and Methods. Abstracts describing clinical trials for patients with breast, lung, colorectal, ovarian, and prostate cancer from 2009 to 2011 were identified by using a comprehensive online database (http://meetinglibrary.asco.org/abstracts). Abstracts included reported results of a treatment or intervention assessed in a discrete, prospective clinical trial. Publication status at 4−6 years was determined by using a standardized search of PubMed. Primary outcomes were the rate of publication for abstracts of randomized and nonrandomized clinical trials. Secondary outcomes included factors influencing the publication of results. Results. A total of 1,075 abstracts describing 378 randomized and 697 nonrandomized clinical trials were evaluated. Across all years, 75% of randomized and 54% of nonrandomized trials were published, with an overall publication rate of 61%. Sample size was a statistically significant predictor of publication for both randomized and nonrandomized trials (odds ratio [OR] per increase of 100 participants = 1.23 [1.11–1.36], p < .001; and 1.64 [1.15–2.34], p = .006, respectively). Among randomized studies, an industry coauthor or involvement of a cooperative group increased the likelihood of publication (OR 2.37, p = .013; and 2.21, p = .01, respectively). Among nonrandomized studies, phase II trials were more likely to be published than phase I (p < .001). Use of an experimental agent was not a predictor of publication in randomized (OR 0.76 [0.38–1.52]; p = .441) or nonrandomized trials (OR 0.89 [0.61–1.29]; p = .532). Conclusion

  15. Public knowledge of automatic external defibrillators in a large U.S. urban community.

    PubMed

    Gonzalez, Mariana; Leary, Marion; Blewer, Audrey L; Cinousis, Marisa; Sheak, Kelsey; Ward, Michael; Merchant, Raina M; Becker, Lance B; Abella, Benjamin S

    2015-07-01

    Sudden cardiac arrest (SCA) strikes over 40,000 people in the public environment annually in the U.S., but despite evidence-based interventions such as prompt CPR and defibrillation, less than 25% of patients survive public SCA events. Effective use of automated external defibrillators (AEDs), especially by lay bystanders, represents an important strategy to improve survival rates. Previous investigations in Europe and Asia have demonstrated variable public awareness of AEDs; layperson knowledge of AEDs in the U.S. is poorly characterized. To measure understanding of AEDs among the general public, at multiple sites within a busy urban transportation system. Surveys were administered at two high-volume train stations in Philadelphia, Pennsylvania between April and June, 2013. A total of 514 surveys were completed. Two thirds (66%) of respondents were able to correctly identify an AED and its purpose, and just over half (58%) of respondents reported willingness to use an AED in an emergency situation. Less than 10% of respondents presented with a hypothetical SCA scenario spontaneously mentioned using an AED when asked what actions they would take. In this cross-sectional survey, public knowledge about AEDs and their use was high; however, a smaller number of respondents expressed thoughts of using the device in an emergency situation and demonstrated willingness to serve as a responder. Increased education and training efforts, as well as potential interventions such as 911 dispatcher-assisted AED use may help improve bystander response in SCA events. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  16. Microarray Technologies in Fungal Diagnostics.

    PubMed

    Rupp, Steffen

    2017-01-01

    Microarray technologies have been a major research tool in the last decades. In addition they have been introduced into several fields of diagnostics including diagnostics of infectious diseases. Microarrays are highly parallelized assay systems that initially were developed for multiparametric nucleic acid detection. From there on they rapidly developed towards a tool for the detection of all kind of biological compounds (DNA, RNA, proteins, cells, nucleic acids, carbohydrates, etc.) or their modifications (methylation, phosphorylation, etc.). The combination of closed-tube systems and lab on chip devices with microarrays further enabled a higher automation degree with a reduced contamination risk. Microarray-based diagnostic applications currently complement and may in the future replace classical methods in clinical microbiology like blood cultures, resistance determination, microscopic and metabolic analyses as well as biochemical or immunohistochemical assays. In addition, novel diagnostic markers appear, like noncoding RNAs and miRNAs providing additional room for novel nucleic acid based biomarkers. Here I focus an microarray technologies in diagnostics and as research tools, based on nucleic acid-based arrays.

  17. Public Health Adaptation to Climate Change in Large Cities: A Global Baseline.

    PubMed

    Araos, Malcolm; Austin, Stephanie E; Berrang-Ford, Lea; Ford, James D

    2016-01-01

    Climate change will have significant impacts on human health, and urban populations are expected to be highly sensitive. The health risks from climate change in cities are compounded by rapid urbanization, high population density, and climate-sensitive built environments. Local governments are positioned to protect populations from climate health risks, but it is unclear whether municipalities are producing climate-adaptive policies. In this article, we develop and apply systematic methods to assess the state of public health adaptation in 401 urban areas globally with more than 1 million people, creating the first global baseline for urban public health adaptation. We find that only 10% of the sampled urban areas report any public health adaptation initiatives. The initiatives identified most frequently address risks posed by extreme weather events and involve direct changes in management or behavior rather than capacity building, research, or long-term investments in infrastructure. Based on our characterization of the current urban health adaptation landscape, we identify several gaps: limited evidence of reporting of institutional adaptation at the municipal level in urban areas in the Global South; lack of information-based adaptation initiatives; limited focus on initiatives addressing infectious disease risks; and absence of monitoring, reporting, and evaluation. © The Author(s) 2015.

  18. Implementation of GenePattern within the Stanford Microarray Database.

    PubMed

    Hubble, Jeremy; Demeter, Janos; Jin, Heng; Mao, Maria; Nitzberg, Michael; Reddy, T B K; Wymore, Farrell; Zachariah, Zachariah K; Sherlock, Gavin; Ball, Catherine A

    2009-01-01

    Hundreds of researchers across the world use the Stanford Microarray Database (SMD; http://smd.stanford.edu/) to store, annotate, view, analyze and share microarray data. In addition to providing registered users at Stanford access to their own data, SMD also provides access to public data, and tools with which to analyze those data, to any public user anywhere in the world. Previously, the addition of new microarray data analysis tools to SMD has been limited by available engineering resources, and in addition, the existing suite of tools did not provide a simple way to design, execute and share analysis pipelines, or to document such pipelines for the purposes of publication. To address this, we have incorporated the GenePattern software package directly into SMD, providing access to many new analysis tools, as well as a plug-in architecture that allows users to directly integrate and share additional tools through SMD. In this article, we describe our implementation of the GenePattern microarray analysis software package into the SMD code base. This extension is available with the SMD source code that is fully and freely available to others under an Open Source license, enabling other groups to create a local installation of SMD with an enriched data analysis capability.

  19. Medical applications of microarray technologies: a regulatory science perspective.

    PubMed

    Petricoin, Emanuel F; Hackett, Joseph L; Lesko, Lawrence J; Puri, Raj K; Gutman, Steven I; Chumakov, Konstantin; Woodcock, Janet; Feigal, David W; Zoon, Kathryn C; Sistare, Frank D

    2002-12-01

    The potential medical applications of microarrays have generated much excitement, and some skepticism, within the biomedical community. Some researchers have suggested that within the decade microarrays will be routinely used in the selection, assessment, and quality control of the best drugs for pharmaceutical development, as well as for disease diagnosis and for monitoring desired and adverse outcomes of therapeutic interventions. Realizing this potential will be a challenge for the whole scientific community, as breakthroughs that show great promise at the bench often fail to meet the requirements of clinicians and regulatory scientists. The development of a cooperative framework among regulators, product sponsors, and technology experts will be essential for realizing the revolutionary promise that microarrays hold for drug development, regulatory science, medical practice and public health.

  20. Transcriptional assessment by microarray analysis and large-scale meta-analysis of the metabolic capacity of cardiac and skeletal muscle tissues to cope with reduced nutrient availability in Gilthead Sea Bream (Sparus aurata L.).

    PubMed

    Calduch-Giner, Josep A; Echasseriau, Yann; Crespo, Diego; Baron, Daniel; Planas, Josep V; Prunet, Patrick; Pérez-Sánchez, Jaume

    2014-08-01

    The effects of nutrient availability on the transcriptome of cardiac and skeletal muscle tissues were assessed in juvenile gilthead sea bream fed with a standard diet at two feeding levels: (1) full ration size and (2) 70 % satiation followed by a finishing phase at the maintenance ration. Microarray analysis evidenced a characteristic transcriptomic profile for each muscle tissue following changes in oxidative capacity (heart > red skeletal muscle > white skeletal muscle). The transcriptome of heart and secondly that of red skeletal muscle were highly responsive to nutritional changes, whereas that of glycolytic white skeletal muscle showed less ability to respond. The highly expressed and nutritionally regulated genes of heart were mainly related to signal transduction and transcriptional regulation. In contrast, those of white muscle were enriched in gene ontology (GO) terms related to proteolysis and protein ubiquitination. Microarray meta-analysis using the bioinformatic tool Fish and Chips ( http://fishandchips.genouest.org/index.php ) showed the close association of a representative cluster of white skeletal muscle with some of cardiac and red skeletal muscle, and many GO terms related to mitochondrial function appeared to be common links between them. A second round of cluster comparisons revealed that mitochondria-related GOs also linked differentially expressed genes of heart with those of liver from cortisol-treated gilthead sea bream. These results show that mitochondria are among the first responders to environmental and nutritional stress stimuli in gilthead sea bream, and functional phenotyping of this cellular organelle is highly promising to obtain reliable markers of growth performance and well-being in this fish species.

  1. Molecular Interactions between the Specialist Herbivore Manduca sexta (Lepidoptera, Sphingidae) and Its Natural Host Nicotiana attenuata: V. Microarray Analysis and Further Characterization of Large-Scale Changes in Herbivore-Induced mRNAs1

    PubMed Central

    Hui, Dequan; Iqbal, Javeed; Lehmann, Katja; Gase, Klaus; Saluz, Hans Peter; Baldwin, Ian T.

    2003-01-01

    We extend our analysis of the transcriptional reorganization that occurs when the native tobacco, Nicotiana attenuata, is attacked by Manduca sexta larvae by cloning 115 transcripts by mRNA differential display reverse transcription-polymerase chain reaction and subtractive hybridization using magnetic beads (SHMB) from the M. sexta-responsive transcriptome. These transcripts were spotted as cDNA with eight others, previously confirmed to be differentially regulated by northern analysis on glass slide microarrays, and hybridized with Cy3- and Cy5-labeled probes derived from plants after 2, 6, 12, and 24 h of continuous attack. Microarray analysis proved to be a powerful means of verifying differential expression; 73 of the cloned genes (63%) were differentially regulated (in equal proportions from differential display reverse transcription-polymerase chain reaction and SHMB procedures), and of these, 24 (32%) had similarity to known genes or putative proteins (more from SHMB). The analysis provided insights into the signaling and transcriptional basis of direct and indirect defenses used against herbivores, suggesting simultaneous activation of salicylic acid-, ethylene-, cytokinin-, WRKY-, MYB-, and oxylipin-signaling pathways and implicating terpenoid-, pathogen-, and cell wall-related transcripts in defense responses. These defense responses require resources that could be made available by decreases in four photosynthetic-related transcripts, increases in transcripts associated with protein and nucleotide turnover, and increases in transcripts associated with carbohydrate metabolism. This putative up-regulation of defense-associated and down-regulation of growth-associated transcripts occur against a backdrop of altered transcripts for RNA-binding proteins, putative ATP/ADP translocators, chaperonins, histones, and water channel proteins, responses consistent with a major metabolic reconfiguration that underscores the complexity of response to herbivore attack

  2. Large regional differences in incidence of arthroscopic meniscal procedures in the public and private sector in Denmark

    PubMed Central

    Hare, Kristoffer Borbjerg; Vinther, Jesper Høeg; Lohmander, L Stefan; Thorlund, Jonas Bloch

    2015-01-01

    Objectives A recent study reported a large increase in the number of meniscal procedures from 2000 to 2011 in Denmark. We examined the nation-wide distribution of meniscal procedures performed in the private and public sector in Denmark since different incentives may be present and the use of these procedures may differ from region to region. Setting We included data on all patients who underwent an arthroscopic meniscal procedure performed in the public or private sector in Denmark. Participants Data were retrieved from the Danish National Patient Register on patients who underwent arthroscopic meniscus surgery as a primary or secondary procedure in the years 2000 to 2011. Hospital identification codes enabled linkage of performed procedures to specific hospitals. Primary and secondary outcome measures Yearly incidence of meniscal procedures per 100 000 inhabitants was calculated with 95% CIs for public and private procedures for each region. Results Incidence of meniscal procedures increased at private and at public hospitals. The private sector accounted for the largest relative and absolute increase, rising from an incidence of 1 in 2000 to 98 in 2011. In 2011, the incidence of meniscal procedures was three times higher in the Capital Region than in Region Zealand. Conclusions Our study identified a large increase in the use of meniscal procedures in the public and private sector in Denmark. The increase was particularly conspicuous in the private sector as its proportion of procedures performed increased from 1% to 32%. Substantial regional differences were present in the incidence and trend over time of meniscal procedures. PMID:25712820

  3. Curriculum: Integrating Team-Based Design across the Curriculum at a Large Public University

    ERIC Educational Resources Information Center

    Trenshaw, Kathryn F.; Henderson, Jerrod A.; Miletic, Marina; Seebauer, Edmund G.; Tillman, Ayesha S.; Vogel, Troy J.

    2014-01-01

    Despite high enrollments and budget cutbacks affecting many programs, students still need design experience which prepares them for a globally competitive workforce. We demonstrate that team design projects can be threaded across the curriculum even at large institutions with high departmental student to faculty ratios (~50:1). We assessed student…

  4. Influencing Public School Policy in the United States: The Role of Large-Scale Assessments

    ERIC Educational Resources Information Center

    Schmidt, William H.; Burroughs, Nathan A.

    2016-01-01

    The authors review the influence of state, national and international large-scale assessments (LSAs) on education policy and research. They distinguish between two main uses of LSAs: as a means for conducting research that informs educational reform and LSAs as a tool for implementing standards and enforcing accountability. The authors discuss the…

  5. Student Perceptions of General Education Requirements at a Large Public University: No Surprises?

    ERIC Educational Resources Information Center

    Thompson, Clarissa A.; Eodice, Michele; Tran, Phuoc

    2015-01-01

    The current study surveyed students' knowledge of and perceptions about general education requirements at a large research-intensive university. Findings revealed that students harbored misconceptions about general education requirements and illuminated the reasons why students were choosing to take required general education courses at other…

  6. Curriculum: Integrating Team-Based Design across the Curriculum at a Large Public University

    ERIC Educational Resources Information Center

    Trenshaw, Kathryn F.; Henderson, Jerrod A.; Miletic, Marina; Seebauer, Edmund G.; Tillman, Ayesha S.; Vogel, Troy J.

    2014-01-01

    Despite high enrollments and budget cutbacks affecting many programs, students still need design experience which prepares them for a globally competitive workforce. We demonstrate that team design projects can be threaded across the curriculum even at large institutions with high departmental student to faculty ratios (~50:1). We assessed student…

  7. Student Perceptions of General Education Requirements at a Large Public University: No Surprises?

    ERIC Educational Resources Information Center

    Thompson, Clarissa A.; Eodice, Michele; Tran, Phuoc

    2015-01-01

    The current study surveyed students' knowledge of and perceptions about general education requirements at a large research-intensive university. Findings revealed that students harbored misconceptions about general education requirements and illuminated the reasons why students were choosing to take required general education courses at other…

  8. Influencing Public School Policy in the United States: The Role of Large-Scale Assessments

    ERIC Educational Resources Information Center

    Schmidt, William H.; Burroughs, Nathan A.

    2016-01-01

    The authors review the influence of state, national and international large-scale assessments (LSAs) on education policy and research. They distinguish between two main uses of LSAs: as a means for conducting research that informs educational reform and LSAs as a tool for implementing standards and enforcing accountability. The authors discuss the…

  9. Public-Private Partnership: Joint recommendations to improve downloads of large Earth observation data

    NASA Astrophysics Data System (ADS)

    Ramachandran, R.; Murphy, K. J.; Baynes, K.; Lynnes, C.

    2016-12-01

    With the volume of Earth observation data expanding rapidly, cloud computing is quickly changing the way Earth observation data is processed, analyzed, and visualized. The cloud infrastructure provides the flexibility to scale up to large volumes of data and handle high velocity data streams efficiently. Having freely available Earth observation data collocated on a cloud infrastructure creates opportunities for innovation and value-added data re-use in ways unforeseen by the original data provider. These innovations spur new industries and applications and spawn new scientific pathways that were previously limited due to data volume and computational infrastructure issues. NASA, in collaboration with Amazon, Google, and Microsoft, have jointly developed a set of recommendations to enable efficient transfer of Earth observation data from existing data systems to a cloud computing infrastructure. The purpose of these recommendations is to provide guidelines against which all data providers can evaluate existing data systems and be used to improve any issues uncovered to enable efficient search, access, and use of large volumes of data. Additionally, these guidelines ensure that all cloud providers utilize a common methodology for bulk-downloading data from data providers thus preventing the data providers from building custom capabilities to meet the needs of individual cloud providers. The intent is to share these recommendations with other Federal agencies and organizations that serve Earth observation to enable efficient search, access, and use of large volumes of data. Additionally, the adoption of these recommendations will benefit data users interested in moving large volumes of data from data systems to any other location. These data users include the cloud providers, cloud users such as scientists, and other users working in a high performance computing environment who need to move large volumes of data.

  10. A Java-based tool for the design of classification microarrays.

    PubMed

    Meng, Da; Broschat, Shira L; Call, Douglas R

    2008-08-04

    analysis of subsequent experimental data. Additionally, PLASMID can be used to construct virtual microarrays with genomes from public databases, which can then be used to identify an optimal set of probes.

  11. Comprehensive Challenges for the Well Being of Young Children: A Population-Based Study of Publicly Monitored Risks in a Large Urban Center

    ERIC Educational Resources Information Center

    Rouse, Heather L.; Fantuzzo, John W.; LeBoeuf, Whitney

    2011-01-01

    This population-based study investigated the unique and cumulative relations between risks that are monitored by public surveillance systems and academic and behavioral outcomes for an entire cohort of third graders in a large, urban public school system. Using integrated, administrative records from child welfare, public health, housing, and…

  12. Comprehensive Challenges for the Well Being of Young Children: A Population-Based Study of Publicly Monitored Risks in a Large Urban Center

    ERIC Educational Resources Information Center

    Rouse, Heather L.; Fantuzzo, John W.; LeBoeuf, Whitney

    2011-01-01

    This population-based study investigated the unique and cumulative relations between risks that are monitored by public surveillance systems and academic and behavioral outcomes for an entire cohort of third graders in a large, urban public school system. Using integrated, administrative records from child welfare, public health, housing, and…

  13. PASE: a web-based platform for peptide/protein microarray experiments.

    PubMed

    Pamelard, Fabien; Even, Gael; Apostol, Costin; Preda, Cristian; Dhaenens, Clarisse; Fafeur, Vronique; Desmet, Rémi; Melnyk, Oleg

    2009-01-01

    Peptide microarray technology requires bioinformatics and statistical tools to manage, store, and analyze the large amount of data produced. To address these needs, we developed a system called protein array software environment (PASE) that provides an integrated framework to manage and analyze microarray information from polypeptide chip technologies.

  14. Large public display boards: a case study of an OR board and design implications.

    PubMed

    Lasome, C E; Xiao, Y

    2001-01-01

    A compelling reason for studying artifacts in collaborative work is to inform design. We present a case study of a public display board (12 ft by 4 ft) in a Level-I trauma center operating room (OR) unit. The board has evolved into a sophisticated coordination tool for clinicians and supporting personnel. This paper draws on study findings about how the OR board is used and organizes the findings into three areas: (1) visual and physical properties of the board that are exploited for collaboration, (2) purposes the board was configured to serve, and (3) types of physical and perceptual interaction with the board. Findings and implications related to layout, size, flexibility, task management, problem-solving, resourcing, shared awareness, and communication are discussed in an effort to propose guidelines to facilitate the design of electronic, computer driven display boards in the OR environment.

  15. From Peptidome to PRIDE: Public proteomics data migration at a large scale

    PubMed Central

    Csordas, Attila; Wang, Rui; Ríos, Daniel; Reisinger, Florian; Foster, Joseph M; Slotta, Douglas J; Vizcaíno, Juan Antonio; Hermjakob, Henning

    2013-01-01

    The PRIDE database, developed and maintained at the European Bioinformatics Institute (EBI), is one of the most prominent data repositories dedicated to high throughput MS-based proteomics data. Peptidome, developed by the National Center for Biotechnology Information (NCBI) as a sibling resource to PRIDE, was discontinued due to funding constraints in April 2011. A joint effort between the two teams was started soon after the Peptidome closure to ensure that data were not “lost” to the wider proteomics community by exporting it to PRIDE. As a result, data in the low terabyte range have been migrated from Peptidome to PRIDE and made publicly available under experiment accessions 17 900–18 271, representing 54 projects, ∼53 million mass spectra, ∼10 million peptide identifications, ∼650 000 protein identifications, ∼1.1 million biologically relevant protein modifications, and 28 species, from more than 30 different labs. PMID:23533138

  16. Large Outbreak of Cryptosporidium hominis Infection Transmitted through the Public Water Supply, Sweden

    PubMed Central

    Schönning, Caroline; Lilja, Mikael; Lebbad, Marianne; Ljung, Thomas; Allestam, Görel; Ferm, Martin; Björkholm, Britta; Hansen, Anette; Hiltula, Jari; Långmark, Jonas; Löfdahl, Margareta; Omberg, Maria; Reuterwall, Christina; Samuelsson, Eva; Widgren, Katarina; Wallensten, Anders; Lindh, Johan

    2014-01-01

    In November 2010, ≈27,000 (≈45%) inhabitants of Östersund, Sweden, were affected by a waterborne outbreak of cryptosporidiosis. The outbreak was characterized by a rapid onset and high attack rate, especially among young and middle-aged persons. Young age, number of infected family members, amount of water consumed daily, and gluten intolerance were identified as risk factors for acquiring cryptosporidiosis. Also, chronic intestinal disease and young age were significantly associated with prolonged diarrhea. Identification of Cryptosporidium hominis subtype IbA10G2 in human and environmental samples and consistently low numbers of oocysts in drinking water confirmed insufficient reduction of parasites by the municipal water treatment plant. The current outbreak shows that use of inadequate microbial barriers at water treatment plants can have serious consequences for public health. This risk can be minimized by optimizing control of raw water quality and employing multiple barriers that remove or inactivate all groups of pathogens. PMID:24655474

  17. Large public display boards: a case study of an OR board and design implications.

    PubMed Central

    Lasome, C. E.; Xiao, Y.

    2001-01-01

    A compelling reason for studying artifacts in collaborative work is to inform design. We present a case study of a public display board (12 ft by 4 ft) in a Level-I trauma center operating room (OR) unit. The board has evolved into a sophisticated coordination tool for clinicians and supporting personnel. This paper draws on study findings about how the OR board is used and organizes the findings into three areas: (1) visual and physical properties of the board that are exploited for collaboration, (2) purposes the board was configured to serve, and (3) types of physical and perceptual interaction with the board. Findings and implications related to layout, size, flexibility, task management, problem-solving, resourcing, shared awareness, and communication are discussed in an effort to propose guidelines to facilitate the design of electronic, computer driven display boards in the OR environment. PMID:11825209

  18. Large outbreak of Cryptosporidium hominis infection transmitted through the public water supply, Sweden.

    PubMed

    Widerström, Micael; Schönning, Caroline; Lilja, Mikael; Lebbad, Marianne; Ljung, Thomas; Allestam, Görel; Ferm, Martin; Björkholm, Britta; Hansen, Anette; Hiltula, Jari; Långmark, Jonas; Löfdahl, Margareta; Omberg, Maria; Reuterwall, Christina; Samuelsson, Eva; Widgren, Katarina; Wallensten, Anders; Lindh, Johan

    2014-04-01

    In November 2010, ≈27,000 (≈45%) inhabitants of Östersund, Sweden, were affected by a waterborne outbreak of cryptosporidiosis. The outbreak was characterized by a rapid onset and high attack rate, especially among young and middle-aged persons. Young age, number of infected family members, amount of water consumed daily, and gluten intolerance were identified as risk factors for acquiring cryptosporidiosis. Also, chronic intestinal disease and young age were significantly associated with prolonged diarrhea. Identification of Cryptosporidium hominis subtype IbA10G2 in human and environmental samples and consistently low numbers of oocysts in drinking water confirmed insufficient reduction of parasites by the municipal water treatment plant. The current outbreak shows that use of inadequate microbial barriers at water treatment plants can have serious consequences for public health. This risk can be minimized by optimizing control of raw water quality and employing multiple barriers that remove or inactivate all groups of pathogens.

  19. The State of Sleep among College Students at a Large Public University

    ERIC Educational Resources Information Center

    Orzech, Kathryn M.; Salafsky, David B.; Hamilton, Lee Ann

    2011-01-01

    Objective: Data about college student sleep were collected and used to develop an education campaign to improve sleep. Participants: On-campus residents at a large state university were surveyed on 4 occasions, October 2005 to April 2007. Sample size was 675 to 1,823 students. Fall 2005 mean age = 18.5 years, SD = 1.03 (range 18-30) years. Initial…

  20. The State of Sleep among College Students at a Large Public University

    ERIC Educational Resources Information Center

    Orzech, Kathryn M.; Salafsky, David B.; Hamilton, Lee Ann

    2011-01-01

    Objective: Data about college student sleep were collected and used to develop an education campaign to improve sleep. Participants: On-campus residents at a large state university were surveyed on 4 occasions, October 2005 to April 2007. Sample size was 675 to 1,823 students. Fall 2005 mean age = 18.5 years, SD = 1.03 (range 18-30) years. Initial…

  1. Inferring genetic networks from microarray data.

    SciTech Connect

    May, Elebeoba Eni; Davidson, George S.; Martin, Shawn Bryan; Werner-Washburne, Margaret C.; Faulon, Jean-Loup Michel

    2004-06-01

    In theory, it should be possible to infer realistic genetic networks from time series microarray data. In practice, however, network discovery has proved problematic. The three major challenges are: (1) inferring the network; (2) estimating the stability of the inferred network; and (3) making the network visually accessible to the user. Here we describe a method, tested on publicly available time series microarray data, which addresses these concerns. The inference of genetic networks from genome-wide experimental data is an important biological problem which has received much attention. Approaches to this problem have typically included application of clustering algorithms [6]; the use of Boolean networks [12, 1, 10]; the use of Bayesian networks [8, 11]; and the use of continuous models [21, 14, 19]. Overviews of the problem and general approaches to network inference can be found in [4, 3]. Our approach to network inference is similar to earlier methods in that we use both clustering and Boolean network inference. However, we have attempted to extend the process to better serve the end-user, the biologist. In particular, we have incorporated a system to assess the reliability of our network, and we have developed tools which allow interactive visualization of the proposed network.

  2. DNA microarray integromics analysis platform.

    PubMed

    Waller, Tomasz; Gubała, Tomasz; Sarapata, Krzysztof; Piwowar, Monika; Jurkowski, Wiktor

    2015-01-01

    The study of interactions between molecules belonging to different biochemical families (such as lipids and nucleic acids) requires specialized data analysis methods. This article describes the DNA Microarray Integromics Analysis Platform, a unique web application that focuses on computational integration and analysis of "multi-omics" data. Our tool supports a range of complex analyses, including - among others - low- and high-level analyses of DNA microarray data, integrated analysis of transcriptomics and lipidomics data and the ability to infer miRNA-mRNA interactions. We demonstrate the characteristics and benefits of the DNA Microarray Integromics Analysis Platform using two different test cases. The first test case involves the analysis of the nutrimouse dataset, which contains measurements of the expression of genes involved in nutritional problems and the concentrations of hepatic fatty acids. The second test case involves the analysis of miRNA-mRNA interactions in polysaccharide-stimulated human dermal fibroblasts infected with porcine endogenous retroviruses. The DNA Microarray Integromics Analysis Platform is a web-based graphical user interface for "multi-omics" data management and analysis. Its intuitive nature and wide range of available workflows make it an effective tool for molecular biology research. The platform is hosted at https://lifescience.plgrid.pl/.

  3. A Self-Directed Method for Cell-Type Identification and Separation of Gene Expression Microarrays

    PubMed Central

    Zuckerman, Neta S.; Noam, Yair; Goldsmith, Andrea J.; Lee, Peter P.

    2013-01-01

    Gene expression analysis is generally performed on heterogeneous tissue samples consisting of multiple cell types. Current methods developed to separate heterogeneous gene expression rely on prior knowledge of the cell-type composition and/or signatures - these are not available in most public datasets. We present a novel method to identify the cell-type composition, signatures and proportions per sample without need for a-priori information. The method was successfully tested on controlled and semi-controlled datasets and performed as accurately as current methods that do require additional information. As such, this method enables the analysis of cell-type specific gene expression using existing large pools of publically available microarray datasets. PMID:23990767

  4. Microfluidic microarray systems and methods thereof

    DOEpatents

    West, Jay A. A. [Castro Valley, CA; Hukari, Kyle W [San Ramon, CA; Hux, Gary A [Tracy, CA

    2009-04-28

    Disclosed are systems that include a manifold in fluid communication with a microfluidic chip having a microarray, an illuminator, and a detector in optical communication with the microarray. Methods for using these systems for biological detection are also disclosed.

  5. Microarray studies of psychostimulant-induced changes in gene expression.

    PubMed

    Yuferov, Vadim; Nielsen, David; Butelman, Eduardo; Kreek, Mary Jeanne

    2005-03-01

    Alterations in the expression of multiple genes in many brain regions are likely to contribute to psychostimulant-induced behaviours. Microarray technology provides a powerful tool for the simultaneous interrogation of gene expression levels of a large number of genes. Several recent experimental studies, reviewed here, demonstrate the power, limitations and progress of microarray technology in the field of psychostimulant addiction. These studies vary in the paradigms of cocaine or amphetamine administration, drug doses, route and also mode of administration, duration of treatment, animal species, brain regions studied and time of tissue collection after final drug administration. The studies also utilize different microarray platforms and statistical techniques for analysis of differentially expressed genes. These variables influence substantially the results of these studies. It is clear that current microarray techniques cannot detect small changes reliably in gene expression of genes with low expression levels, including functionally significant changes in components of major neurotransmission systems such as glutamate, dopamine, opioid and GABA receptors, especially those that may occur after chronic drug administration or drug withdrawal. However, the microarray studies reviewed here showed cocaine- or amphetamine-induced alterations in the expression of numerous genes involved in the modulation of neuronal growth, cytoskeletal structures, synaptogenesis, signal transduction, apoptosis and cell metabolism. Application of laser capture microdissection and single-cell cDNA amplification may greatly enhance microarray studies of gene expression profiling. The combination of rapidly evolving microarray technology with established methods of neuroscience, molecular biology and genetics, as well as appropriate behavioural models of drug reinforcement, may provide a productive approach for delineating the neurobiological underpinnings of drug responses that lead to

  6. The Automation of a Large Public Health Department - A Status Report

    PubMed Central

    Fiddleman, Richard H.; Follingstad, Marianne

    1985-01-01

    In January 1983, The MITRE Corporation, in collaboration with the Palm Beach Health Department, undertook the development of a powerful information system to support the medical, financial, and administrative activities performed by this large and complex health care delivery organization. The resulting system, jointly developed by both organizations, consists of enhanced COSTAR modules, as well as new modules programmed in MUMPS or based on the use of the File Manager software package. An overview of the system development process, a description of a new module that supports the health department's prepaid health plan program, and a review of the organizational problems created by the new system are discussed in this paper.

  7. [Managing the difficult balance between employment needs and public health in large industrial sites].

    PubMed

    Conversano, M

    2014-01-01

    Environmental pressures affecting Taranto area led institutional commitment to the local Health (LHA) and Environment Agency, which have helped to provide data in support of epidemiological and health impacts evidence.This is relevant in view of the issues related to the public health which led the Apulia Region to enact measures for environmental monitoring of dioxins (Regional Law 44/2008) and protection of food safety (Regional Council Deliberation 1442/2009). The LHA investigated three lines of development: monitoring of food matrices, studies of human biomonitoring and the establishment of local Cancer Registry. Same time to the actions of the Taranto Judiciary, Apulia Region has enacted the RL 24/12, integrating the legislative gap present into the Environmental Authorization procedures, which will allow the Health Damage Assessment, through the correlation between environmental monitoring data, biomonitoring and Cancer Registry. The next step will see the LHA involved in managing effective and feasible prevention initiatives. The Special Health and Environment Plan objective is to monitor the Taranto population health status, to screen the health determinants, to estimate the toxicologically relevant indicators of possible contamination and, if possible, to modify the correlations between risk factors, body burden, and specific diseases.

  8. A data management and publication workflow for a large-scale, heterogeneous sensor network.

    PubMed

    Jones, Amber Spackman; Horsburgh, Jeffery S; Reeder, Stephanie L; Ramírez, Maurier; Caraballo, Juan

    2015-06-01

    It is common for hydrology researchers to collect data using in situ sensors at high frequencies, for extended durations, and with spatial distributions that produce data volumes requiring infrastructure for data storage, management, and sharing. The availability and utility of these data in addressing scientific questions related to water availability, water quality, and natural disasters relies on effective cyberinfrastructure that facilitates transformation of raw sensor data into usable data products. It also depends on the ability of researchers to share and access the data in useable formats. In this paper, we describe a data management and publication workflow and software tools for research groups and sites conducting long-term monitoring using in situ sensors. Functionality includes the ability to track monitoring equipment inventory and events related to field maintenance. Linking this information to the observational data is imperative in ensuring the quality of sensor-based data products. We present these tools in the context of a case study for the innovative Urban Transitions and Aridregion Hydrosustainability (iUTAH) sensor network. The iUTAH monitoring network includes sensors at aquatic and terrestrial sites for continuous monitoring of common meteorological variables, snow accumulation and melt, soil moisture, surface water flow, and surface water quality. We present the overall workflow we have developed for effectively transferring data from field monitoring sites to ultimate end-users and describe the software tools we have deployed for storing, managing, and sharing the sensor data. These tools are all open source and available for others to use.

  9. Development of DNA Microarrays for Metabolic Pathway and Bioprocess Monitoring

    SciTech Connect

    Gregory Stephanopoulos

    2004-07-31

    Transcriptional profiling experiments utilizing DNA microarrays to study the intracellular accumulation of PHB in Synechocystis has proved difficult in large part because strains that show significant differences in PHB which would justify global analysis of gene expression have not been isolated.

  10. Photonics and microarray technology

    NASA Astrophysics Data System (ADS)

    Skovsen, E.; Duroux, M.; Neves-Petersen, M. T.; Duroux, L.; Petersen, S. B.

    2007-05-01

    Photonic induced immobilization of biosensor molecules is a novel technology that results in spatially oriented and spatially localized covalent coupling of a large variety of biomolecules onto thiol reactive surfaces, e.g. thiolated glass, quartz, gold or silicon. The reaction mechanism behind the reported new technology involves light-induced breakage of disulphide bridges in proteins upon UV illumination of nearby aromatic amino acids resulting in the formation of reactive molecules that will form covalent bonds with thiol reactive surfaces. This new technology has the potential of replacing present micro dispensing arraying technologies, where the size of the individual sensor spots are limited by the size of the dispensed droplets. Using light-induced immobilization the spatial resolution is defined by the area of the sensor surface that is illuminated by UV light and not by the physical size of the dispensed droplets of sensor molecules. This new technology allows for dense packing of different biomolecules on a surface, allowing the creation of multi-potent functionalized materials, such as biosensors with micrometer sized individual sensor spots. Thus, we have developed the necessary technology for preparing large protein arrays of enzymes and fragments of antibodies, with micrometer resolution, without the need for liquid micro dispensing.

  11. The Microarray Revolution: Perspectives from Educators

    ERIC Educational Resources Information Center

    Brewster, Jay L.; Beason, K. Beth; Eckdahl, Todd T.; Evans, Irene M.

    2004-01-01

    In recent years, microarray analysis has become a key experimental tool, enabling the analysis of genome-wide patterns of gene expression. This review approaches the microarray revolution with a focus upon four topics: 1) the early development of this technology and its application to cancer diagnostics; 2) a primer of microarray research,…

  12. The Microarray Revolution: Perspectives from Educators

    ERIC Educational Resources Information Center

    Brewster, Jay L.; Beason, K. Beth; Eckdahl, Todd T.; Evans, Irene M.

    2004-01-01

    In recent years, microarray analysis has become a key experimental tool, enabling the analysis of genome-wide patterns of gene expression. This review approaches the microarray revolution with a focus upon four topics: 1) the early development of this technology and its application to cancer diagnostics; 2) a primer of microarray research,…

  13. Public participation in Full dome digital visualisations of large datasets in a planetarium sky theater : An experiment in progress

    NASA Astrophysics Data System (ADS)

    Rathnasree, Nandivada

    2015-08-01

    A full dome digital planetarium system with a userfriendly content creation possibility can be used very effectively for communicating points of interest in large Astronomical datsets, to public and student visitors to a planetarium. Periodic public lectures by Astronomers, "Under the Stars", which use full dome visualisations of data sets, foster a regular interest group which becomes associated with the planetarium, ensuring a regular inflow of students (and a smaller number of non student visitors) willing to contribute to the entries in the full dome datasets.Regardless of whether or not completion is achieved for any of the data sets, the very process of this project is extremely rewarding in terms of generating a quickening of interest, for the casual visitor to a planetarium, in aspects related to intricacies of datasets. The casual visitor who gets interested, may just make one entry in the dataset, following instructions provided in the planetarium public interaction. For students who show sustained interest in this data entry project, it becomes a really fruitful learning process.Combining this purely data entry process with some interactions and discussions with Astronomers on the excitements in the areas related to specific data sets, allows a more organised enrichment possibility for student participants, nudging them towards exploring related possibilities of some "Hands on Astronomy" analysis oriented projects.Datasets like Gamma Ray bursts, variable stars, TGSS, and so on, are being entered within the planetarium production software at the New Delhi planetarium, by public and student visitors to the planetarium, as weekend activities.The Digital Universe data sets pre-existing in the planetarium system, allow preliminary discussions for weekend crowds related to Astronomical data sets, introduction of ever increasing multiwavelength data sets and onwwards to facilitating public participation in data entry within the planetarium software, for some

  14. Large-scale public-private partnership for improving TB-HIV services for high-risk groups in India.

    PubMed

    Kane, S; Dewan, P K; Gupta, D; Wi, T; Das, A; Singh, A; Bitra, G; Chauhan, L S; Dallabetta, G

    2010-08-01

    In India, the Revised National Tuberculosis Control Programme and a large-scale human immunodeficiency virus (HIV) prevention project partnered to deliver enhanced TB screening services for HIV high-risk groups. Between July 2007 and September 2008, 134 non-governmental organisations (NGOs) operating 412 clinics and community-based outreach services, screened 124 371 high-risk individuals and referred 3749 (3.01%) for TB diagnosis. Of these, 849 (23%) were diagnosed with TB. India has translated this model into national policy through a public-sector funded TB-HIV partnership scheme for NGOs serving high-risk groups.

  15. Experiments using microarray technology: limitations and standard operating procedures.

    PubMed

    Forster, T; Roy, D; Ghazal, P

    2003-08-01

    Microarrays are a powerful method for the global analysis of gene or protein content and expression, opening up new horizons in molecular and physiological systems. This review focuses on the critical aspects of acquiring meaningful data for analysis following fluorescence-based target hybridisation to arrays. Although microarray technology is adaptable to the analysis of a range of biomolecules (DNA, RNA, protein, carbohydrates and lipids), the scheme presented here is applicable primarily to customised DNA arrays fabricated using long oligomer or cDNA probes. Rather than provide a comprehensive review of microarray technology and analysis techniques, both of which are large and complex areas, the aim of this paper is to provide a restricted overview, highlighting salient features to provide initial guidance in terms of pitfalls in planning and executing array projects. We outline standard operating procedures, which help streamline the analysis of microarray data resulting from a diversity of array formats and biological systems. We hope that this overview will provide practical initial guidance for those embarking on microarray studies.

  16. Statistical approaches for the analysis of DNA methylation microarray data.

    PubMed

    Siegmund, Kimberly D

    2011-06-01

    Following the rapid development and adoption in DNA methylation microarray assays, we are now experiencing a growth in the number of statistical tools to analyze the resulting large-scale data sets. As is the case for other microarray applications, biases caused by technical issues are of concern. Some of these issues are old (e.g., two-color dye bias and probe- and array-specific effects), while others are new (e.g., fragment length bias and bisulfite conversion efficiency). Here, I highlight characteristics of DNA methylation that suggest standard statistical tools developed for other data types may not be directly suitable. I then describe the microarray technologies most commonly in use, along with the methods used for preprocessing and obtaining a summary measure. I finish with a section describing downstream analyses of the data, focusing on methods that model percentage DNA methylation as the outcome, and methods for integrating DNA methylation with gene expression or genotype data.

  17. A Versatile Microarray Platform for Capturing Rare Cells

    NASA Astrophysics Data System (ADS)

    Brinkmann, Falko; Hirtz, Michael; Haller, Anna; Gorges, Tobias M.; Vellekoop, Michael J.; Riethdorf, Sabine; Müller, Volkmar; Pantel, Klaus; Fuchs, Harald

    2015-10-01

    Analyses of rare events occurring at extremely low frequencies in body fluids are still challenging. We established a versatile microarray-based platform able to capture single target cells from large background populations. As use case we chose the challenging application of detecting circulating tumor cells (CTCs) - about one cell in a billion normal blood cells. After incubation with an antibody cocktail, targeted cells are extracted on a microarray in a microfluidic chip. The accessibility of our platform allows for subsequent recovery of targets for further analysis. The microarray facilitates exclusion of false positive capture events by co-localization allowing for detection without fluorescent labelling. Analyzing blood samples from cancer patients with our platform reached and partly outreached gold standard performance, demonstrating feasibility for clinical application. Clinical researchers free choice of antibody cocktail without need for altered chip manufacturing or incubation protocol, allows virtual arbitrary targeting of capture species and therefore wide spread applications in biomedical sciences.

  18. Software and tools for microarray data analysis.

    PubMed

    Mehta, Jai Prakash; Rani, Sweta

    2011-01-01

    A typical microarray experiment results in series of images, depending on the experimental design and number of samples. Software analyses the images to obtain the intensity at each spot and quantify the expression for each transcript. This is followed by normalization, and then various data analysis techniques are applied on the data. The whole analysis pipeline requires a large number of software to accurately handle the massive amount of data. Fortunately, there are large number of freely available and commercial software to churn the massive amount of data to manageable sets of differentially expressed genes, functions, and pathways. This chapter describes the software and tools which can be used to analyze the gene expression data right from the image analysis to gene list, ontology, and pathways.

  19. Caryoscope: an Open Source Java application for viewing microarray data in a genomic context.

    PubMed

    Awad, Ihab A B; Rees, Christian A; Hernandez-Boussard, Tina; Ball, Catherine A; Sherlock, Gavin

    2004-10-15

    Microarray-based comparative genome hybridization experiments generate data that can be mapped onto the genome. These data are interpreted more easily when represented graphically in a genomic context. We have developed Caryoscope, which is an open source Java application for visualizing microarray data from array comparative genome hybridization experiments in a genomic context. Caryoscope can read General Feature Format files (GFF files), as well as comma- and tab-delimited files, that define the genomic positions of the microarray reporters for which data are obtained. The microarray data can be browsed using an interactive, zoomable interface, which helps users identify regions of chromosomal deletion or amplification. The graphical representation of the data can be exported in a number of graphic formats, including publication-quality formats such as PostScript. Caryoscope is a useful tool that can aid in the visualization, exploration and interpretation of microarray data in a genomic context.

  20. [Analysis of the educational requirements and planning in a large public hospital].

    PubMed

    Degan, Mario; Bragato, Laura; Duminuco, Leonardo; Bagno, Carla; Genova, Valeria; Sansoni, Julita

    2007-01-01

    The educational needs in a large hospital in the Venice region were analysed in order to plan continuing education programs for 2005-2006. The reference model was the analysis of the educational waiting lists in both operative and managerial professions. Two identical questionnaires were used: the first was distributed to all the professional staff of the hospital with university qualifications and asked them to give their opinion regarding educational priorities. The second was given to staff with managerial roles, asking them to indicate the educational priorities for the staff under their direction. Analysis of the data collected focused on : the priority given to the various areas and topics of education; differences of opinion identified between the various working environments between professional groups and between staff/managers; influence of social and personal factors on the opinions expressed. The fact that the fields of interest indicated varied according to the role and working activities of staff involved, indicate the need to offer educational procedures tailored to the requirements of each group.

  1. STIDP: A US Department of Homeland Security program for countering explosives attacks at large public events and mass transit facilities

    SciTech Connect

    Knudson, Christa K.; Kemp, Michael C.; Lombardo, Nicholas J.

    2009-03-07

    The Department of Homeland Security’s Standoff Technology Integration and Demonstration Program is designed to accelerate the development and integration of technologies, concepts of operations, and training to prevent explosives attacks at large public events and mass transit facilities. The program will address threats posed by suicide bombers, vehicle-borne improvised explosive devices, and leave-behind bombs. The program is focused on developing and testing explosives countermeasure architectures using commercial off-the-shelf and near-commercial standoff and remotely operated detection technologies in prototypic operational environments. An important part of the program is the integration of multiple technologies and systems to protect against a wider range of threats, improve countermeasure performance, increase the distance from the venue at which screening is conducted, and reduce staffing requirements. The program will routinely conduct tests in public venues involving successively more advanced technology, higher levels of system integration, and more complex scenarios. This paper describes the initial field test of an integrated countermeasure system that included infrared, millimeter-wave, and video analytics technologies for detecting person-borne improvised explosive devices at a public arena. The test results are being used to develop a concept for the next generation of integrated countermeasures, to refine technical and operational requirements for architectures and technologies, and engage industry and academia in solution development.

  2. A genome-wide 20 K citrus microarray for gene expression analysis

    PubMed Central

    Martinez-Godoy, M Angeles; Mauri, Nuria; Juarez, Jose; Marques, M Carmen; Santiago, Julia; Forment, Javier; Gadea, Jose

    2008-01-01

    Background Understanding of genetic elements that contribute to key aspects of citrus biology will impact future improvements in this economically important crop. Global gene expression analysis demands microarray platforms with a high genome coverage. In the last years, genome-wide EST collections have been generated in citrus, opening the possibility to create new tools for functional genomics in this crop plant. Results We have designed and constructed a publicly available genome-wide cDNA microarray that include 21,081 putative unigenes of citrus. As a functional companion to the microarray, a web-browsable database [1] was created and populated with information about the unigenes represented in the microarray, including cDNA libraries, isolated clones, raw and processed nucleotide and protein sequences, and results of all the structural and functional annotation of the unigenes, like general description, BLAST hits, putative Arabidopsis orthologs, microsatellites, putative SNPs, GO classification and PFAM domains. We have performed a Gene Ontology comparison with the full set of Arabidopsis proteins to estimate the genome coverage of the microarray. We have also performed microarray hybridizations to check its usability. Conclusion This new cDNA microarray replaces the first 7K microarray generated two years ago and allows gene expression analysis at a more global scale. We have followed a rational design to minimize cross-hybridization while maintaining its utility for different citrus species. Furthermore, we also provide access to a website with full structural and functional annotation of the unigenes represented in the microarray, along with the ability to use this site to directly perform gene expression analysis using standard tools at different publicly available servers. Furthermore, we show how this microarray offers a good representation of the citrus genome and present the usefulness of this genomic tool for global studies in citrus by using it to

  3. A genome-wide 20 K citrus microarray for gene expression analysis.

    PubMed

    Martinez-Godoy, M Angeles; Mauri, Nuria; Juarez, Jose; Marques, M Carmen; Santiago, Julia; Forment, Javier; Gadea, Jose

    2008-07-03

    Understanding of genetic elements that contribute to key aspects of citrus biology will impact future improvements in this economically important crop. Global gene expression analysis demands microarray platforms with a high genome coverage. In the last years, genome-wide EST collections have been generated in citrus, opening the possibility to create new tools for functional genomics in this crop plant. We have designed and constructed a publicly available genome-wide cDNA microarray that include 21,081 putative unigenes of citrus. As a functional companion to the microarray, a web-browsable database 1 was created and populated with information about the unigenes represented in the microarray, including cDNA libraries, isolated clones, raw and processed nucleotide and protein sequences, and results of all the structural and functional annotation of the unigenes, like general description, BLAST hits, putative Arabidopsis orthologs, microsatellites, putative SNPs, GO classification and PFAM domains. We have performed a Gene Ontology comparison with the full set of Arabidopsis proteins to estimate the genome coverage of the microarray. We have also performed microarray hybridizations to check its usability. This new cDNA microarray replaces the first 7K microarray generated two years ago and allows gene expression analysis at a more global scale. We have followed a rational design to minimize cross-hybridization while maintaining its utility for different citrus species. Furthermore, we also provide access to a website with full structural and functional annotation of the unigenes represented in the microarray, along with the ability to use this site to directly perform gene expression analysis using standard tools at different publicly available servers. Furthermore, we show how this microarray offers a good representation of the citrus genome and present the usefulness of this genomic tool for global studies in citrus by using it to catalogue genes expressed in

  4. ParaSAM: a parallelized version of the significance analysis of microarrays algorithm

    PubMed Central

    Sharma, Ashok; Zhao, Jieping; Podolsky, Robert; McIndoe, Richard A.

    2010-01-01

    Motivation: Significance analysis of microarrays (SAM) is a widely used permutation-based approach to identifying differentially expressed genes in microarray datasets. While SAM is freely available as an Excel plug-in and as an R-package, analyses are often limited for large datasets due to very high memory requirements. Summary: We have developed a parallelized version of the SAM algorithm called ParaSAM to overcome the memory limitations. This high performance multithreaded application provides the scientific community with an easy and manageable client-server Windows application with graphical user interface and does not require programming experience to run. The parallel nature of the application comes from the use of web services to perform the permutations. Our results indicate that ParaSAM is not only faster than the serial version, but also can analyze extremely large datasets that cannot be performed using existing implementations. Availability:A web version open to the public is available at http://bioanalysis.genomics.mcg.edu/parasam. For local installations, both the windows and web implementations of ParaSAM are available for free at http://www.amdcc.org/bioinformatics/software/parasam.aspx Contact: rmcindoe@mail.mcg.edu Supplementary information: Supplementary Data is available at Bioinformatics online. PMID:20400455

  5. ParaSAM: a parallelized version of the significance analysis of microarrays algorithm.

    PubMed

    Sharma, Ashok; Zhao, Jieping; Podolsky, Robert; McIndoe, Richard A

    2010-06-01

    Significance analysis of microarrays (SAM) is a widely used permutation-based approach to identifying differentially expressed genes in microarray datasets. While SAM is freely available as an Excel plug-in and as an R-package, analyses are often limited for large datasets due to very high memory requirements. We have developed a parallelized version of the SAM algorithm called ParaSAM to overcome the memory limitations. This high performance multithreaded application provides the scientific community with an easy and manageable client-server Windows application with graphical user interface and does not require programming experience to run. The parallel nature of the application comes from the use of web services to perform the permutations. Our results indicate that ParaSAM is not only faster than the serial version, but also can analyze extremely large datasets that cannot be performed using existing implementations. A web version open to the public is available at http://bioanalysis.genomics.mcg.edu/parasam. For local installations, both the windows and web implementations of ParaSAM are available for free at http://www.amdcc.org/bioinformatics/software/parasam.aspx.

  6. Microarray analysis in pulmonary hypertension.

    PubMed

    Hoffmann, Julia; Wilhelm, Jochen; Olschewski, Andrea; Kwapiszewska, Grazyna

    2016-07-01

    Microarrays are a powerful and effective tool that allows the detection of genome-wide gene expression differences between controls and disease conditions. They have been broadly applied to investigate the pathobiology of diverse forms of pulmonary hypertension, namely group 1, including patients with idiopathic pulmonary arterial hypertension, and group 3, including pulmonary hypertension associated with chronic lung diseases such as chronic obstructive pulmonary disease and idiopathic pulmonary fibrosis. To date, numerous human microarray studies have been conducted to analyse global (lung homogenate samples), compartment-specific (laser capture microdissection), cell type-specific (isolated primary cells) and circulating cell (peripheral blood) expression profiles. Combined, they provide important information on development, progression and the end-stage disease. In the future, system biology approaches, expression of noncoding RNAs that regulate coding RNAs, and direct comparison between animal models and human disease might be of importance.

  7. Microarray analysis in pulmonary hypertension

    PubMed Central

    Hoffmann, Julia; Wilhelm, Jochen; Olschewski, Andrea

    2016-01-01

    Microarrays are a powerful and effective tool that allows the detection of genome-wide gene expression differences between controls and disease conditions. They have been broadly applied to investigate the pathobiology of diverse forms of pulmonary hypertension, namely group 1, including patients with idiopathic pulmonary arterial hypertension, and group 3, including pulmonary hypertension associated with chronic lung diseases such as chronic obstructive pulmonary disease and idiopathic pulmonary fibrosis. To date, numerous human microarray studies have been conducted to analyse global (lung homogenate samples), compartment-specific (laser capture microdissection), cell type-specific (isolated primary cells) and circulating cell (peripheral blood) expression profiles. Combined, they provide important information on development, progression and the end-stage disease. In the future, system biology approaches, expression of noncoding RNAs that regulate coding RNAs, and direct comparison between animal models and human disease might be of importance. PMID:27076594

  8. Using DNA Microarrays to Detect Multiple Pathogen Threats in Water.

    SciTech Connect

    Straub, Tim M.; Quinonez-Diaz, Maria D.; Valdez, Catherine O.; Call, Douglas R.; Chandler, Darrell P.

    2004-06-01

    Currently, there is no single method to collect, process, and analyze a water sample for all pathogenic microorganisms of interest. Some of the difficulties in developing a universal method include the physical differences between the major pathogen groups (viruses, bacteria, protozoa), efficiently concentrating large volume water samples to detect low target concentrations of certain pathogen groups, removing co-concentrated inhibitors from the sample, and standardizing a culture-independent endpoint detection method. Integrating the disparate technologies into a single, universal, simple method and detection system would represent a significant advance in public health and microbiological water quality analysis. Recent advances in sample collection, on-line sample processing and purification, and DNA microarray technologies may form the basis of a universal method to detect known and emerging waterborne pathogens. This review discusses some of the challenges in developing a universal pathogen detection method, current technology that may be employed to overcome these challenges, and the remaining needs for developing an integrated pathogen detection and monitoring system for source or finished water.

  9. New Sustainability Programs and Their Impact at a Large Public State University

    NASA Astrophysics Data System (ADS)

    Bralower, T. J.; Guertin, L. A.

    2016-12-01

    The Pennsylvania State University comprises 24 campuses across the state. Students who are admitted to any campus are automatically admitted to the University Park Campus once they meet the entrance requirements for their major. The University Park Campus has a Geoscience Department with over 30 faculty and several degree programs. Several of the campuses also have Geoscience faculty. Two of the campuses offer majors in geoscience fields with plans at other campuses to add Environmental Science degree programs. Campus faculty play an instrumental role in recruiting students into the geosciences and providing them with general and allied science education. However, these faculty have high teaching loads and often struggle to fulfill student demand for courses. Penn State is also home to the World Campus which offers courses solely online to students all around the world including a large number of Military personnel. Penn State has led the development of five introductory-level blended and online courses as part of the InTeGrate STEP center. These courses are Coastal Processes, Hazards and Society; Water Science and Society; Climate, Energy, and Our Future; the Future of Food; and Earth Modeling. They add to an existing blended and online course, Earth in the Future that has been taught at the University Park and World Campuses for four years. Combined, the courses include 70 weekly modules. The courses constitute the basis of a recently approved Minor and Certificate of Excellence in Earth Sustainability offered in online format through the World Campus and in blended format at all the campuses. We are in the process of establishing an e-Learning Cooperative so that faculty at a campus can teach any of the sustainability courses online to students throughout the Penn State system. This will enable students to receive a greater introduction to, and variety of, sustainability courses at the campuses, and enable faculty to tailor courses to local campus interests and

  10. Microarrays, antiobesity and the liver

    PubMed Central

    Castro-Chávez, Fernando

    2013-01-01

    In this review, the microarray technology and especially oligonucleotide arrays are exemplified with a practical example taken from the perilipin−/− mice and using the dChip software, available for non-lucrative purposes. It was found that the liver of perilipin−/− mice was healthy and normal, even under high-fat diet when compared with the results published for the scd1−/− mice, which under high-fat diets had a darker liver, suggestive of hepatic steatosis. Scd1 is required for the biosynthesis of monounsaturated fatty acids and plays a key role in the hepatic synthesis of triglycerides and of very-low-density lipoproteins. Both models of obesity resistance share many similar phenotypic antiobesity features, however, the perilipin−/− mice had a significant downregulation of stearoyl CoA desaturases scd1 and scd2 in its white adipose tissue, but a normal level of both genes inside the liver, even under high-fat diet. Here, different microarray methodologies are discussed, and also some of the most recent discoveries and perspectives regarding the use of microarrays, with an emphasis on obesity gene expression, and a personal remark on my findings of increased expression for hemoglobin transcripts and other hemo related genes (hemo-like), and for leukocyte like (leuko-like) genes inside the white adipose tissue of the perilipin−/− mice. In conclusion, microarrays have much to offer in comparative studies such as those in antiobesity, and also they are methodologies adequate for new astounding molecular discoveries [free full text of this article PMID:15657555

  11. Comparison of gene coverage of mouse oligonucleotide microarray platforms

    PubMed Central

    Verdugo, Ricardo A; Medrano, Juan F

    2006-01-01

    Background The increasing use of DNA microarrays for genetical genomics studies generates a need for platforms with complete coverage of the genome. We have compared the effective gene coverage in the mouse genome of different commercial and noncommercial oligonucleotide microarray platforms by performing an in-house gene annotation of probes. We only used information about probes that is available from vendors and followed a process that any researcher may take to find the gene targeted by a given probe. In order to make consistent comparisons between platforms, probes in each microarray were annotated with an Entrez Gene id and the chromosomal position for each gene was obtained from the UCSC Genome Browser Database. Gene coverage was estimated as the percentage of Entrez Genes with a unique position in the UCSC Genome database that is tested by a given microarray platform. Results A MySQL relational database was created to store the mapping information for 25,416 mouse genes and for the probes in five microarray platforms (gene coverage level in parenthesis): Affymetrix430 2.0 (75.6%), ABI Genome Survey (81.24%), Agilent (79.33%), Codelink (78.09%), Sentrix (90.47%); and four array-ready oligosets: Sigma (47.95%), Operon v.3 (69.89%), Operon v.4 (84.03%), and MEEBO (84.03%). The differences in coverage between platforms were highly conserved across chromosomes. Differences in the number of redundant and unspecific probes were also found among arrays. The database can be queried to compare specific genomic regions using a web interface. The software used to create, update and query the database is freely available as a toolbox named ArrayGene. Conclusion The software developed here allows researchers to create updated custom databases by using public or proprietary information on genes for any organisms. ArrayGene allows easy comparisons of gene coverage between microarray platforms for any region of the genome. The comparison presented here reveals that the

  12. The more the merrier: comparative analysis of microarray studies on cell cycle-regulated genes in fission yeast.

    PubMed

    Marguerat, Samuel; Jensen, Thomas S; de Lichtenberg, Ulrik; Wilhelm, Brian T; Jensen, Lars J; Bähler, Jürg

    2006-03-01

    The last two years have seen the publication of three genome-wide gene expression studies of the fission yeast cell cycle. While these microarray papers largely agree on the main patterns of cell cycle-regulated transcription and its control, there are discrepancies with regard to the identity and numbers of periodically expressed genes. We present benchmark and reproducibility analyses showing that the main discrepancies do not reflect differences in the data themselves (microarray or synchronization methods seem to lead only to minor biases) but rather in the interpretation of the data. Our reanalysis of the three datasets reveals that combining all independent information leads to an improved identification of periodically expressed genes. These evaluations suggest that the available microarray data do not allow reliable identification of more than about 500 cell cycle-regulated genes. The temporal expression pattern of the top 500 periodically expressed genes is generally consistent across experiments and the three studies, together with our integrated analysis, provide a coherent and rich source of information on cell cycle-regulated gene expression in Schizosaccharomyces pombe. The reanalysed datasets and other supplementary information are available from an accompanying website: http://www.cbs.dtu.dk/cellcycle/. We hope that this paper will resolve the apparent discrepancies between the previous studies and be useful both for wet-lab biologists and for theoretical scientists who wish to take advantage of the data for follow-up work. Copyright 2006 John Wiley & Sons, Ltd.

  13. Genomic and microarray approaches to coral reef conservation biology

    NASA Astrophysics Data System (ADS)

    Forêt, S.; Kassahn, K. S.; Grasso, L. C.; Hayward, D. C.; Iguchi, A.; Ball, E. E.; Miller, D. J.

    2007-09-01

    New technologies based on DNA microarrays and comparative genomics hold great promise for providing the background biological information necessary for effective coral reef conservation and management. Microarray analysis has been used in a wide range of applications across the biological sciences, most frequently to examine simultaneous changes in the expression of large numbers of genes in response to experimental manipulation or environmental variation. Other applications of microarray methods include the assessment of divergence in gene sequences between species and the identification of fast-evolving genes. Arrays are presently available for only a limited range of species, but with appropriate controls they can be used for related species, thus avoiding the considerable costs associated with development of a system de novo. Arrays are in use or preparation to study stress responses, early development, and symbiosis in Acropora and Montastraea. Ongoing projects on several corals are making available large numbers of expressed gene sequences, enabling the identification of candidate genes for studies on gamete specificity, allorecognition and symbiont interactions. Over the next few years, microarray and comparative genomic approaches are likely to assume increasingly important and widespread use to study many aspects of the biology of coral reef organisms. Application of these genomic approaches to enhance our understanding of genetic and physiological correlates during stress, environmental disturbance and disease bears direct relevance to the conservation of coral reef ecosystems.

  14. How do you assign persistent identifiers to extracts from large, complex, dynamic data sets that underpin scholarly publications?

    NASA Astrophysics Data System (ADS)

    Wyborn, Lesley; Car, Nicholas; Evans, Benjamin; Klump, Jens

    2016-04-01

    Persistent identifiers in the form of a Digital Object Identifier (DOI) are becoming more mainstream, assigned at both the collection and dataset level. For static datasets, this is a relatively straight-forward matter. However, many new data collections are dynamic, with new data being appended, models and derivative products being revised with new data, or the data itself revised as processing methods are improved. Further, because data collections are becoming accessible as services, researchers can log in and dynamically create user-defined subsets for specific research projects: they also can easily mix and match data from multiple collections, each of which can have a complex history. Inevitably extracts from such dynamic data sets underpin scholarly publications, and this presents new challenges. The National Computational Infrastructure (NCI) has been experiencing and making progress towards addressing these issues. The NCI is large node of the Research Data Services initiative (RDS) of the Australian Government's research infrastructure, which currently makes available over 10 PBytes of priority research collections, ranging from geosciences, geophysics, environment, and climate, through to astronomy, bioinformatics, and social sciences. Data are replicated to, or are produced at, NCI and then processed there to higher-level data products or directly analysed. Individual datasets range from multi-petabyte computational models and large volume raster arrays, down to gigabyte size, ultra-high resolution datasets. To facilitate access, maximise reuse and enable integration across the disciplines, datasets have been organized on a platform called the National Environmental Research Data Interoperability Platform (NERDIP). Combined, the NERDIP data collections form a rich and diverse asset for researchers: their co-location and standardization optimises the value of existing data, and forms a new resource to underpin data-intensive Science. New publication

  15. Retention and risk factors for attrition in a large public health ART program in Myanmar: a retrospective cohort analysis.

    PubMed

    Thida, Aye; Tun, Sai Thein Than; Zaw, Sai Ko Ko; Lover, Andrew A; Cavailler, Philippe; Chunn, Jennifer; Aye, Mar Mar; Par, Par; Naing, Kyaw Win; Zan, Kaung Nyunt; Shwe, Myint; Kyaw, Thar Tun; Waing, Zaw Htoon; Clevenbergh, Philippe

    2014-01-01

    The outcomes from an antiretroviral treatment (ART) program within the public sector in Myanmar have not been reported. This study documents retention and the risk factors for attrition in a large ART public health program in Myanmar. A retrospective analysis of a cohort of adult patients enrolled in the Integrated HIV Care (IHC) Program between June 2005 and October 2011 and followed up until April 2012 is presented. The primary outcome was attrition (death or loss-follow up); a total of 10,223 patients were included in the 5-year cumulative survival analysis. Overall 5,718 patients were analyzed for the risk factors for attrition using both logistic regression and flexible parametric survival models. The mean age was 36 years, 61% of patients were male, and the median follow up was 13.7 months. Overall 8,564 (84%) patients were retained in ART program: 750 (7%) were lost to follow-up and 909 (9%) died. During the 3 years follow-up, 1,542 attritions occurred over 17,524 person years at risk, giving an incidence density of 8.8% per year. The retention rates of participants at 12, 24, 36, 48 and 60 months were 86, 82, 80, 77 and 74% respectively. In multivariate analysis, being male, having high WHO staging, a low CD4 count, being anaemic or having low BMI at baseline were independent risk factors for attrition; tuberculosis (TB) treatment at ART initiation, a prior ART course before program enrollment and literacy were predictors for retention in the program. High retention rate of IHC program was documented within the public sector in Myanmar. Early diagnosis of HIV, nutritional support, proper investigation and treatment for patients with low CD4 counts and for those presenting with anaemia are crucial issues towards improvement of HIV program outcomes in resource-limited settings.

  16. Retention and Risk Factors for Attrition in a Large Public Health ART Program in Myanmar: A Retrospective Cohort Analysis

    PubMed Central

    Thida, Aye; Tun, Sai Thein Than; Zaw, Sai Ko Ko; Lover, Andrew A.; Cavailler, Philippe; Chunn, Jennifer; Aye, Mar Mar; Par, Par; Naing, Kyaw Win; Zan, Kaung Nyunt; Shwe, Myint; Kyaw, Thar Tun; Waing, Zaw Htoon; Clevenbergh, Philippe

    2014-01-01

    Background The outcomes from an antiretroviral treatment (ART) program within the public sector in Myanmar have not been reported. This study documents retention and the risk factors for attrition in a large ART public health program in Myanmar. Methods A retrospective analysis of a cohort of adult patients enrolled in the Integrated HIV Care (IHC) Program between June 2005 and October 2011 and followed up until April 2012 is presented. The primary outcome was attrition (death or loss-follow up); a total of 10,223 patients were included in the 5-year cumulative survival analysis. Overall 5,718 patients were analyzed for the risk factors for attrition using both logistic regression and flexible parametric survival models. Result The mean age was 36 years, 61% of patients were male, and the median follow up was 13.7 months. Overall 8,564 (84%) patients were retained in ART program: 750 (7%) were lost to follow-up and 909 (9%) died. During the 3 years follow-up, 1,542 attritions occurred over 17,524 person years at risk, giving an incidence density of 8.8% per year. The retention rates of participants at 12, 24, 36, 48 and 60 months were 86, 82, 80, 77 and 74% respectively. In multivariate analysis, being male, having high WHO staging, a low CD4 count, being anaemic or having low BMI at baseline were independent risk factors for attrition; tuberculosis (TB) treatment at ART initiation, a prior ART course before program enrollment and literacy were predictors for retention in the program. Conclusion High retention rate of IHC program was documented within the public sector in Myanmar. Early diagnosis of HIV, nutritional support, proper investigation and treatment for patients with low CD4 counts and for those presenting with anaemia are crucial issues towards improvement of HIV program outcomes in resource-limited settings. PMID:25268903

  17. ArrayNinja: An Open Source Platform for Unified Planning and Analysis of Microarray Experiments

    PubMed Central

    Dickson, B.M.; Cornett, E.M.; Ramjan, Z.; Rothbart, S.B.

    2017-01-01

    Microarray-based proteomic platforms have emerged as valuable tools for studying various aspects of protein function, particularly in the field of chromatin biochemistry. Microarray technology itself is largely unrestricted in regard to printable material and platform design, and efficient multidimensional optimization of assay parameters requires fluidity in the design and analysis of custom print layouts. This motivates the need for streamlined software infrastructure that facilitates the combined planning and analysis of custom microarray experiments. To this end, we have developed ArrayNinja as a portable, open source, and interactive application that unifies the planning and visualization of microarray experiments and provides maximum flexibility to end users. Array experiments can be planned, stored to a private database, and merged with the imaged results for a level of data interaction and centralization that is not currently attainable with available microarray informatics tools. PMID:27423857

  18. [DNA microarrays and their application in detecting and identifying intestinal pathogens].

    PubMed

    Jin, Da-Zhi; Wen, Si-Yuan; Wang, Sheng-Qi

    2006-06-01

    DNA microarrays offer many advantages of high throughout, automation, rapid detection, and so on. Therefore, this technology had been used in many fields such as molecular epidemiology of bacteria, microbial gene identification, disease mechanism, gene mutation, gene expression identification, DNA sequencing and medicine screening etc. The assays for identifying pathogens using DNA microarrays reported aboard recently are introduced. The application of DNA microarrays in detecting and identifying intestinal pathogens mainly includes three aspects: the identification of toxin and characteristic genes of pathogens, the identification of bacterial DNA or RNA directly, the simultaneous detection of a large number of intestinal pathogens with the target - gene of ribosomal RNA. Because of its high efficiency, DNA microarrays is superior to other biological method. Obviously DNA microarrays technology may be useful in identifying intestinal pathogens and have a wide prospect.

  19. CEM-designer: design of custom expression microarrays in the post-ENCODE Era.

    PubMed

    Arnold, Christian; Externbrink, Fabian; Hackermüller, Jörg; Reiche, Kristin

    2014-11-10

    Microarrays are widely used in gene expression studies, and custom expression microarrays are popular to monitor expression changes of a customer-defined set of genes. However, the complexity of transcriptomes uncovered recently make custom expression microarray design a non-trivial task. Pervasive transcription and alternative processing of transcripts generate a wealth of interweaved transcripts that requires well-considered probe design strategies and is largely neglected in existing approaches. We developed the web server CEM-Designer that facilitates microarray platform independent design of custom expression microarrays for complex transcriptomes. CEM-Designer covers (i) the collection and generation of a set of unique target sequences from different sources and (ii) the selection of a set of sensitive and specific probes that optimally represents the target sequences. Probe design itself is left to third party software to ensure that probes meet provider-specific constraints. CEM-Designer is available at http://designpipeline.bioinf.uni-leipzig.de.

  20. The Evolution Of 21 cm Structure (EOS): public, large-scale simulations of Cosmic Dawn and reionization

    NASA Astrophysics Data System (ADS)

    Mesinger, Andrei; Greig, Bradley; Sobacchi, Emanuele

    2016-07-01

    We introduce the Evolution Of 21 cm Structure (EOS) project: providing periodic, public releases of the latest cosmological 21 cm simulations. 21 cm interferometry is set to revolutionize studies of the Cosmic Dawn (CD) and Epoch of Reionization (EoR). Progress will depend on sophisticated data analysis pipelines, initially tested on large-scale mock observations. Here we present the 2016 EOS release: 10243, 1.6 Gpc, 21 cm simulations of the CD and EoR, calibrated to the Planck 2015 measurements. We include calibrated, sub-grid prescriptions for inhomogeneous recombinations and photoheating suppression of star formation in small-mass galaxies. Leaving the efficiency of supernovae feedback as a free parameter, we present two runs which bracket the contribution from faint unseen galaxies. From these two extremes, we predict that the duration of reionization (defined as a change in the mean neutral fraction from 0.9 to 0.1) should be between 2.7 ≲ Δzre ≲ 5.7. The large-scale 21 cm power during the advanced EoR stages can be different by up to a factor of ˜10, depending on the model. This difference has a comparable contribution from (i) the typical bias of sources and (ii) a more efficient negative feedback in models with an extended EoR driven by faint galaxies. We also present detectability forecasts. With a 1000 h integration, Hydrogen Epoch of Reionization Array and (Square Kilometre Array phase 1) SKA1 should achieve a signal-to-noise of ˜few to hundreds throughout the EoR/CD. We caution that our ability to clean foregrounds determines the relative performance of narrow/deep versus wide/shallow surveys expected with SKA1. Our 21-cm power spectra, simulation outputs and visualizations are publicly available.

  1. The Porcelain Crab Transcriptome and PCAD, the Porcelain Crab Microarray and Sequence Database

    SciTech Connect

    Tagmount, Abderrahmane; Wang, Mei; Lindquist, Erika; Tanaka, Yoshihiro; Teranishi, Kristen S.; Sunagawa, Shinichi; Wong, Mike; Stillman, Jonathon H.

    2010-01-27

    Background: With the emergence of a completed genome sequence of the freshwater crustacean Daphnia pulex, construction of genomic-scale sequence databases for additional crustacean sequences are important for comparative genomics and annotation. Porcelain crabs, genus Petrolisthes, have been powerful crustacean models for environmental and evolutionary physiology with respect to thermal adaptation and understanding responses of marine organisms to climate change. Here, we present a large-scale EST sequencing and cDNA microarray database project for the porcelain crab Petrolisthes cinctipes. Methodology/Principal Findings: A set of ~;;30K unique sequences (UniSeqs) representing ~;;19K clusters were generated from ~;;98K high quality ESTs from a set of tissue specific non-normalized and mixed-tissue normalized cDNA libraries from the porcelain crab Petrolisthes cinctipes. Homology for each UniSeq was assessed using BLAST, InterProScan, GO and KEGG database searches. Approximately 66percent of the UniSeqs had homology in at least one of the databases. All EST and UniSeq sequences along with annotation results and coordinated cDNA microarray datasets have been made publicly accessible at the Porcelain Crab Array Database (PCAD), a feature-enriched version of the Stanford and Longhorn Array Databases.Conclusions/Significance: The EST project presented here represents the third largest sequencing effort for any crustacean, and the largest effort for any crab species. Our assembly and clustering results suggest that our porcelain crab EST data set is equally diverse to the much larger EST set generated in the Daphnia pulex genome sequencing project, and thus will be an important resource to the Daphnia research community. Our homology results support the pancrustacea hypothesis and suggest that Malacostraca may be ancestral to Branchiopoda and Hexapoda. Our results also suggest that our cDNA microarrays cover as much of the transcriptome as can reasonably be captured in

  2. Surface characterization of carbohydrate microarrays.

    PubMed

    Scurr, David J; Horlacher, Tim; Oberli, Matthias A; Werz, Daniel B; Kroeck, Lenz; Bufali, Simone; Seeberger, Peter H; Shard, Alexander G; Alexander, Morgan R

    2010-11-16

    Carbohydrate microarrays are essential tools to determine the biological function of glycans. Here, we analyze a glycan array by time-of-flight secondary ion mass spectrometry (ToF-SIMS) to gain a better understanding of the physicochemical properties of the individual spots and to improve carbohydrate microarray quality. The carbohydrate microarray is prepared by piezo printing of thiol-terminated sugars onto a maleimide functionalized glass slide. The hyperspectral ToF-SIMS imaging data are analyzed by multivariate curve resolution (MCR) to discern secondary ions from regions of the array containing saccharide, linker, salts from the printing buffer, and the background linker chemistry. Analysis of secondary ions from the linker common to all of the sugar molecules employed reveals a relatively uniform distribution of the sugars within the spots formed from solutions with saccharide concentration of 0.4 mM and less, whereas a doughnut shape is often formed at higher-concentration solutions. A detailed analysis of individual spots reveals that in the larger spots the phosphate buffered saline (PBS) salts are heterogeneously distributed, apparently resulting in saccharide concentrated at the rim of the spots. A model of spot formation from the evaporating sessile drop is proposed to explain these observations. Saccharide spot diameters increase with saccharide concentration due to a reduction in surface tension of the saccharide solution compared to PBS. The multivariate analytical partial least squares (PLS) technique identifies ions from the sugars that in the complex ToF-SIMS spectra correlate with the binding of galectin proteins.

  3. MicroArray Facility: a laboratory information management system with extended support for Nylon based technologies

    PubMed Central

    Honoré, Paul; Granjeaud, Samuel; Tagett, Rebecca; Deraco, Stéphane; Beaudoing, Emmanuel; Rougemont, Jacques; Debono, Stéphane; Hingamp, Pascal

    2006-01-01

    Background High throughput gene expression profiling (GEP) is becoming a routine technique in life science laboratories. With experimental designs that repeatedly span thousands of genes and hundreds of samples, relying on a dedicated database infrastructure is no longer an option. GEP technology is a fast moving target, with new approaches constantly broadening the field diversity. This technology heterogeneity, compounded by the informatics complexity of GEP databases, means that software developments have so far focused on mainstream techniques, leaving less typical yet established techniques such as Nylon microarrays at best partially supported. Results MAF (MicroArray Facility) is the laboratory database system we have developed for managing the design, production and hybridization of spotted microarrays. Although it can support the widely used glass microarrays and oligo-chips, MAF was designed with the specific idiosyncrasies of Nylon based microarrays in mind. Notably single channel radioactive probes, microarray stripping and reuse, vector control hybridizations and spike-in controls are all natively supported by the software suite. MicroArray Facility is MIAME supportive and dynamically provides feedback on missing annotations to help users estimate effective MIAME compliance. Genomic data such as clone identifiers and gene symbols are also directly annotated by MAF software using standard public resources. The MAGE-ML data format is implemented for full data export. Journalized database operations (audit tracking), data anonymization, material traceability and user/project level confidentiality policies are also managed by MAF. Conclusion MicroArray Facility is a complete data management system for microarray producers and end-users. Particular care has been devoted to adequately model Nylon based microarrays. The MAF system, developed and implemented in both private and academic environments, has proved a robust solution for shared facilities and

  4. Making a New Technology Work: The Standardization and Regulation of Microarrays

    PubMed Central

    Rogers, Susan; Cambrosio, Alberto

    2008-01-01

    The translation of laboratory innovations into clinical tools is dependent upon the development of regulatory arrangements designed to ensure that the new technology will be used reliably and consistently. A case study of a key post-genomic technology, gene chips or microarrays, exemplifies this claim. The number of microarray publications and patents has increased exponentially during the last decade and diagnostic microarray tests already are making their way into the clinic. Yet starting in the mid-1990s, scientific journals were overrun with criticism concerning the ambiguities involved in interpreting most of the assumptions of a microarray experiment. Questions concerning platform comparability and statistical calculations were and continue to be raised, in spite of the emergence by 2001 of an initial set of standards concerning several components of a microarray experiment. This article probes the history and ongoing efforts aimed at turning microarray experimentation into a viable, meaningful, and consensual technology by focusing on two related elements: 1) The history of the development of the Microarray Gene Expression Data Society (MGED), a remarkable bottom-up initiative that brings together different kinds of specialists from academic, commercial, and hybrid settings to produce, maintain, and update microarray standards; and 2) The unusual mix of skills and expertise involved in the development and use of microarrays. The production, accumulation, storage, and mining of microarray data remain multi-skilled endeavors bridging together different types of scientists who embody a diversity of scientific traditions. Beyond standardization, the interfacing of these different skills has become a key issue for further development of the field. PMID:18449388

  5. Versatile High Resolution Oligosaccharide Microarrays for Plant Glycobiology and Cell Wall Research*

    PubMed Central

    Pedersen, Henriette L.; Fangel, Jonatan U.; McCleary, Barry; Ruzanski, Christian; Rydahl, Maja G.; Ralet, Marie-Christine; Farkas, Vladimir; von Schantz, Laura; Marcus, Susan E.; Andersen, Mathias C. F.; Field, Rob; Ohlin, Mats; Knox, J. Paul; Clausen, Mads H.; Willats, William G. T.

    2012-01-01

    Microarrays are powerful tools for high throughput analysis, and hundreds or thousands of molecular interactions can be assessed simultaneously using very small amounts of analytes. Nucleotide microarrays are well established in plant research, but carbohydrate microarrays are much less established, and one reason for this is a lack of suitable glycans with which to populate arrays. Polysaccharide microarrays are relatively easy to produce because of the ease of immobilizing large polymers noncovalently onto a variety of microarray surfaces, but they lack analytical resolution because polysaccharides often contain multiple distinct carbohydrate substructures. Microarrays of defined oligosaccharides potentially overcome this problem but are harder to produce because oligosaccharides usually require coupling prior to immobilization. We have assembled a library of well characterized plant oligosaccharides produced either by partial hydrolysis from polysaccharides or by de novo chemical synthesis. Once coupled to protein, these neoglycoconjugates are versatile reagents that can be printed as microarrays onto a variety of slide types and membranes. We show that these microarrays are suitable for the high throughput characterization of the recognition capabilities of monoclonal antibodies, carbohydrate-binding modules, and other oligosaccharide-binding proteins of biological significance and also that they have potential for the characterization of carbohydrate-active enzymes. PMID:22988248

  6. Spotting effect in microarray experiments

    PubMed Central

    Mary-Huard, Tristan; Daudin, Jean-Jacques; Robin, Stéphane; Bitton, Frédérique; Cabannes, Eric; Hilson, Pierre

    2004-01-01

    Background Microarray data must be normalized because they suffer from multiple biases. We have identified a source of spatial experimental variability that significantly affects data obtained with Cy3/Cy5 spotted glass arrays. It yields a periodic pattern altering both signal (Cy3/Cy5 ratio) and intensity across the array. Results Using the variogram, a geostatistical tool, we characterized the observed variability, called here the spotting effect because it most probably arises during steps in the array printing procedure. Conclusions The spotting effect is not appropriately corrected by current normalization methods, even by those addressing spatial variability. Importantly, the spotting effect may alter differential and clustering analysis. PMID:15151695

  7. Very Important Pool (VIP) genes – an application for microarray-based molecular signatures

    PubMed Central

    Su, Zhenqiang; Hong, Huixiao; Fang, Hong; Shi, Leming; Perkins, Roger; Tong, Weida

    2008-01-01

    Background Advances in DNA microarray technology portend that molecular signatures from which microarray will eventually be used in clinical environments and personalized medicine. Derivation of biomarkers is a large step beyond hypothesis generation and imposes considerably more stringency for accuracy in identifying informative gene subsets to differentiate phenotypes. The inherent nature of microarray data, with fewer samples and replicates compared to the large number of genes, requires identifying informative genes prior to classifier construction. However, improving the ability to identify differentiating genes remains a challenge in bioinformatics. Results A new hybrid gene selection approach was investigated and tested with nine publicly available microarray datasets. The new method identifies a Very Important Pool (VIP) of genes from the broad patterns of gene expression data. The method uses a bagging sampling principle, where the re-sampled arrays are used to identify the most informative genes. Frequency of selection is used in a repetitive process to identify the VIP genes. The putative informative genes are selected using two methods, t-statistic and discriminatory analysis. In the t-statistic, the informative genes are identified based on p-values. In the discriminatory analysis, disjoint Principal Component Analyses (PCAs) are conducted for each class of samples, and genes with high discrimination power (DP) are identified. The VIP gene selection approach was compared with the p-value ranking approach. The genes identified by the VIP method but not by the p-value ranking approach are also related to the disease investigated. More importantly, these genes are part of the pathways derived from the common genes shared by both the VIP and p-ranking methods. Moreover, the binary classifiers built from these genes are statistically equivalent to those built from the top 50 p-value ranked genes in distinguishing different types of samples. Conclusion The

  8. Diagnostic challenges for multiplexed protein microarrays.

    PubMed

    Master, Stephen R; Bierl, Charlene; Kricka, Larry J

    2006-11-01

    Multiplexed protein analysis using planar microarrays or microbeads is growing in popularity for simultaneous assays of antibodies, cytokines, allergens, drugs and hormones. However, this new assay format presents several new operational issues for the clinical laboratory, such as the quality control of protein-microarray-based assays, the release of unrequested test data and the use of diagnostic algorithms to transform microarray data into diagnostic results.

  9. Automated Microarray Image Analysis Toolbox for MATLAB

    SciTech Connect

    White, Amanda M.; Daly, Don S.; Willse, Alan R.; Protic, Miroslava; Chandler, Darrell P.

    2005-09-01

    The Automated Microarray Image Analysis (AMIA) Toolbox for MATLAB is a flexible, open-source microarray image analysis tool that allows the user to customize analysis of sets of microarray images. This tool provides several methods of identifying and quantify spot statistics, as well as extensive diagnostic statistics and images to identify poor data quality or processing. The open nature of this software allows researchers to understand the algorithms used to provide intensity estimates and to modify them easily if desired.

  10. Delivering Science to Large Audiences: Experiments in Active Learning and Public Lectures at the University of Michigan

    NASA Astrophysics Data System (ADS)

    McKay, T.

    1999-12-01

    The problem of disseminating scientific knowledge to the broader community in an effective and efficient way is always with us. At the University of Michigan we have been addressing this problem in several ways. Every year we teach introductory physics to about 3000 students. We believe that, in addition to a pedagogical responsibility, this is an important opportunity for outreach. We report on a variety of approaches to active learning in large lecture classes which are aimed at aiding student comprehension of conceptual material. These have the side affect of improving their general impression of science. In addition to the traditional classroom, we have also engaged in a broader outreach program through the Saturday Morning Physics lecture series, which through a combination of programming and advertising draws audiences of 250 a week to 15 weeks of lectures on topics of current research. We conclude with some general observations about the relation between the success of these public lectures and our large lecture classes. This work is supported by a CAREER award from the National Science Foundation, the University of Michigan, and the Ted Annis Foundation.

  11. THE ABRF MARG MICROARRAY SURVEY 2005: TAKING THE PULSE ON THE MICROARRAY FIELD

    EPA Science Inventory

    Over the past several years microarray technology has evolved into a critical component of any discovery based program. Since 1999, the Association of Biomolecular Resource Facilities (ABRF) Microarray Research Group (MARG) has conducted biennial surveys designed to generate a pr...

  12. THE ABRF MARG MICROARRAY SURVEY 2005: TAKING THE PULSE ON THE MICROARRAY FIELD

    EPA Science Inventory

    Over the past several years microarray technology has evolved into a critical component of any discovery based program. Since 1999, the Association of Biomolecular Resource Facilities (ABRF) Microarray Research Group (MARG) has conducted biennial surveys designed to generate a pr...

  13. Clustering Short Time-Series Microarray

    NASA Astrophysics Data System (ADS)

    Ping, Loh Wei; Hasan, Yahya Abu

    2008-01-01

    Most microarray analyses are carried out on static gene expressions. However, the dynamical study of microarrays has lately gained more attention. Most researches on time-series microarray emphasize on the bioscience and medical aspects but few from the numerical aspect. This study attempts to analyze short time-series microarray mathematically using STEM clustering tool which formally preprocess data followed by clustering. We next introduce the Circular Mould Distance (CMD) algorithm with combinations of both preprocessing and clustering analysis. Both methods are subsequently compared in terms of efficiencies.

  14. Living Cell Microarrays: An Overview of Concepts

    PubMed Central

    Jonczyk, Rebecca; Kurth, Tracy; Lavrentieva, Antonina; Walter, Johanna-Gabriela; Scheper, Thomas; Stahl, Frank

    2016-01-01

    Living cell microarrays are a highly efficient cellular screening system. Due to the low number of cells required per spot, cell microarrays enable the use of primary and stem cells and provide resolution close to the single-cell level. Apart from a variety of conventional static designs, microfluidic microarray systems have also been established. An alternative format is a microarray consisting of three-dimensional cell constructs ranging from cell spheroids to cells encapsulated in hydrogel. These systems provide an in vivo-like microenvironment and are preferably used for the investigation of cellular physiology, cytotoxicity, and drug screening. Thus, many different high-tech microarray platforms are currently available. Disadvantages of many systems include their high cost, the requirement of specialized equipment for their manufacture, and the poor comparability of results between different platforms. In this article, we provide an overview of static, microfluidic, and 3D cell microarrays. In addition, we describe a simple method for the printing of living cell microarrays on modified microscope glass slides using standard DNA microarray equipment available in most laboratories. Applications in research and diagnostics are discussed, e.g., the selective and sensitive detection of biomarkers. Finally, we highlight current limitations and the future prospects of living cell microarrays. PMID:27600077

  15. Cross-platform normalization of microarray and RNA-seq data for machine learning applications.

    PubMed

    Thompson, Jeffrey A; Tan, Jie; Greene, Casey S

    2016-01-01

    Large, publicly available gene expression datasets are often analyzed with the aid of machine learning algorithms. Although RNA-seq is increasingly the technology of choice, a wealth of expression data already exist in the form of microarray data. If machine learning models built from legacy data can be applied to RNA-seq data, larger, more diverse training datasets can be created and validation can be performed on newly generated data. We developed Training Distribution Matching (TDM), which transforms RNA-seq data for use with models constructed from legacy platforms. We evaluated TDM, as well as quantile normalization, nonparanormal transformation, and a simple log 2 transformation, on both simulated and biological datasets of gene expression. Our evaluation included both supervised and unsupervised machine learning approaches. We found that TDM exhibited consistently strong performance across settings and that quantile normalization also performed well in many circumstances. We also provide a TDM package for the R programming language.

  16. "Harshlighting" small blemishes on microarrays

    PubMed Central

    Suárez-Fariñas, Mayte; Haider, Asifa; Wittkowski, Knut M

    2005-01-01

    Background Microscopists are familiar with many blemishes that fluorescence images can have due to dust and debris, glass flaws, uneven distribution of fluids or surface coatings, etc. Microarray scans show similar artefacts, which affect the analysis, particularly when one tries to detect subtle changes. However, most blemishes are hard to find by the unaided eye, particularly in high-density oligonucleotide arrays (HDONAs). Results We present a method that harnesses the statistical power provided by having several HDONAs available, which are obtained under similar conditions except for the experimental factor. This method "harshlights" blemishes and renders them evident. We find empirically that about 25% of our chips are blemished, and we analyze the impact of masking them on screening for differentially expressed genes. Conclusion Experiments attempting to assess subtle expression changes should be carefully screened for blemishes on the chips. The proposed method provides investigators with a novel robust approach to improve the sensitivity of microarray analyses. By utilizing topological information to identify and mask blemishes prior to model based analyses, the method prevents artefacts from confounding the process of background correction, normalization, and summarization. PMID:15784152

  17. "Harshlighting" small blemishes on microarrays.

    PubMed

    Suárez-Fariñas, Mayte; Haider, Asifa; Wittkowski, Knut M

    2005-03-22

    Microscopists are familiar with many blemishes that fluorescence images can have due to dust and debris, glass flaws, uneven distribution of fluids or surface coatings, etc. Microarray scans show similar artefacts, which affect the analysis, particularly when one tries to detect subtle changes. However, most blemishes are hard to find by the unaided eye, particularly in high-density oligonucleotide arrays (HDONAs). We present a method that harnesses the statistical power provided by having several HDONAs available, which are obtained under similar conditions except for the experimental factor. This method "harshlights" blemishes and renders them evident. We find empirically that about 25% of our chips are blemished, and we analyze the impact of masking them on screening for differentially expressed genes. Experiments attempting to assess subtle expression changes should be carefully screened for blemishes on the chips. The proposed method provides investigators with a novel robust approach to improve the sensitivity of microarray analyses. By utilizing topological information to identify and mask blemishes prior to model based analyses, the method prevents artefacts from confounding the process of background correction, normalization, and summarization.

  18. A Customized DNA Microarray for Microbial Source Tracking ...

    EPA Pesticide Factsheets

    It is estimated that more than 160, 000 miles of rivers and streams in the United States are impaired due to the presence of waterborne pathogens. These pathogens typically originate from human and other animal fecal pollution sources; therefore, a rapid microbial source tracking (MST) method is needed to facilitate water quality assessment and impaired water remediation. We report a novel qualitative DNA microarray technology consisting of 453 probes for the detection of general fecal and host-associated bacteria, viruses, antibiotic resistance, and other environmentally relevant genetic indicators. A novel data normalization and reduction approach is also presented to help alleviate false positives often associated with high-density microarray applications. To evaluate the performance of the approach, DNA and cDNA was isolated from swine, cattle, duck, goose and gull fecal reference samples, as well as soiled poultry liter and raw municipal sewage. Based on nonmetric multidimensional scaling analysis of results, findings suggest that the novel microarray approach may be useful for pathogen detection and identification of fecal contamination in recreational waters. The ability to simultaneously detect a large collection of environmentally important genetic indicators in a single test has the potential to provide water quality managers with a wide range of information in a short period of time. Future research is warranted to measure microarray performance i

  19. A Customized DNA Microarray for Microbial Source Tracking ...

    EPA Pesticide Factsheets

    It is estimated that more than 160, 000 miles of rivers and streams in the United States are impaired due to the presence of waterborne pathogens. These pathogens typically originate from human and other animal fecal pollution sources; therefore, a rapid microbial source tracking (MST) method is needed to facilitate water quality assessment and impaired water remediation. We report a novel qualitative DNA microarray technology consisting of 453 probes for the detection of general fecal and host-associated bacteria, viruses, antibiotic resistance, and other environmentally relevant genetic indicators. A novel data normalization and reduction approach is also presented to help alleviate false positives often associated with high-density microarray applications. To evaluate the performance of the approach, DNA and cDNA was isolated from swine, cattle, duck, goose and gull fecal reference samples, as well as soiled poultry liter and raw municipal sewage. Based on nonmetric multidimensional scaling analysis of results, findings suggest that the novel microarray approach may be useful for pathogen detection and identification of fecal contamination in recreational waters. The ability to simultaneously detect a large collection of environmentally important genetic indicators in a single test has the potential to provide water quality managers with a wide range of information in a short period of time. Future research is warranted to measure microarray performance i

  20. Mining pathway signatures from microarray data and relevant biological knowledge.

    PubMed

    Panteris, Eleftherios; Swift, Stephen; Payne, Annette; Liu, Xiaohui

    2007-12-01

    High-throughput technologies such as DNA microarray are in the process of revolutionizing the way modern biological research is being done. Bioinformatics tools are becoming increasingly important to assist biomedical scientists in their quest in understanding complex biological processes. Gene expression analysis has attracted a large amount of attention over the last few years mostly in the form of algorithms, exploring cluster and regulatory relationships among genes of interest, and programs that try to display the multidimensional microarray data in appropriate formats so that they make biological sense. To reduce the dimensionality of microarray data and make the corresponding analysis more biologically relevant, in this paper we propose a biologically-led approach to biochemical pathway analysis using microarray data and relevant biological knowledge. The method selects a subset of genes for each pathway that describes the behaviour of the pathway at a given experimental condition, and transforms them into pathway signatures. The metabolic pathways of Escherichia coli are used as a case study.

  1. 2008 Microarray Research Group (MARG Survey): Sensing the State of Microarray Technology

    EPA Science Inventory

    Over the past several years, the field of microarrays has grown and evolved drastically. In its continued efforts to track this evolution and transformation, the ABRF-MARG has once again conducted a survey of international microarray facilities and individual microarray users. Th...

  2. THE ABRF-MARG MICROARRAY SURVEY 2004: TAKING THE PULSE OF THE MICROARRAY FIELD

    EPA Science Inventory

    Over the past several years, the field of microarrays has grown and evolved drastically. In its continued efforts to track this evolution, the ABRF-MARG has once again conducted a survey of international microarray facilities and individual microarray users. The goal of the surve...

  3. THE ABRF-MARG MICROARRAY SURVEY 2004: TAKING THE PULSE OF THE MICROARRAY FIELD

    EPA Science Inventory

    Over the past several years, the field of microarrays has grown and evolved drastically. In its continued efforts to track this evolution, the ABRF-MARG has once again conducted a survey of international microarray facilities and individual microarray users. The goal of the surve...

  4. Polymer microarray technology for stem cell engineering.

    PubMed

    Coyle, Robert; Jia, Jia; Mei, Ying

    2016-04-01

    Stem cells hold remarkable promise for applications in tissue engineering and disease modeling. During the past decade, significant progress has been made in developing soluble factors (e.g., small molecules and growth factors) to direct stem cells into a desired phenotype. However, the current lack of suitable synthetic materials to regulate stem cell activity has limited the realization of the enormous potential of stem cells. This can be attributed to a large number of materials properties (e.g., chemical structures and physical properties of materials) that can affect stem cell fate. This makes it challenging to design biomaterials to direct stem cell behavior. To address this, polymer microarray technology has been developed to rapidly identify materials for a variety of stem cell applications. In this article, we summarize recent developments in polymer array technology and their applications in stem cell engineering. Stem cells hold remarkable promise for applications in tissue engineering and disease modeling. In the last decade, significant progress has been made in developing chemically defined media to direct stem cells into a desired phenotype. However, the current lack of the suitable synthetic materials to regulate stem cell activities has been limiting the realization of the potential of stem cells. This can be attributed to the number of variables in material properties (e.g., chemical structures and physical properties) that can affect stem cells. Polymer microarray technology has shown to be a powerful tool to rapidly identify materials for a variety of stem cell applications. Here we summarize recent developments in polymer array technology and their applications in stem cell engineering. Copyright © 2015 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

  5. Building the PHARAOH framework using scenario-based design: a set of pandemic decision-making scenarios for continuity of operations in a large municipal public health agency.

    PubMed

    Reeder, Blaine; Demiris, George

    2010-08-01

    Continuity of Operations Planning (COOP) is actions taken before, during and after a disaster to maintain the delivery of an organization's essential services. The application of COOP in public health is necessary to save lives and protect population health when disaster strikes. However, COOP decision-making and COOP decision support technology are under-explored in the public health domain. This work approaches the problem of designing a COOP decision support system for a large municipal public health agency using scenario-based design. Through a series of meetings and informal interviews, we developed a set of 12 scenarios of use for public health decision-making roles during a pandemic. These scenarios were validated as reliable, useful and acceptable by professional public health COOP planners. The results of this work show scenario-based design can be a powerful tool in designing decision support systems for public health leadership information needs during a crisis.

  6. Automatic and robust system for correcting microarray images' rotations and isolating spots.

    PubMed

    Wang, Anlei; Kaabouch, Naima; Hu, Wen-Chen

    2011-01-01

    Microarray images contain a large volume of genetic data in the form of thousands of spots that need to be extracted and analyzed using digital image processing. Automatic extraction, gridding, is therefore necessary to save time, to remove user-dependent variations, and, hence, to obtain repeatable results. In this research paper, an algorithm that involves four steps is proposed to efficiently grid microarray images. A set of real and synthetic microarray images of different sizes and degrees of rotations is used to assess the proposed algorithm, and its efficiency is compared with the efficiencies of other methods from the literature.

  7. From single gene to integrative molecular concept MAPS: pitfalls and potentials of microarray technology.

    PubMed

    Chiorino, G; Mello Grand, M; Scatolini, M; Ostano, P

    2008-01-01

    Microarray experiments have a large variety of applications and several important achievements have been obtained by means of this technology, especially within the field of whole genome expression profiling, which undoubtedly is the most diffused world-wide. Nevertheless, care must be taken in unconditionally applying such high-throughput techniques and in extracting/interpreting their results. Both the validity and the reproducibility of microarray-based clinical research have recently been challenged. Pitfalls and potentials of the microarray technology for gene expression profiling are critically reviewed in this paper.

  8. Evaluation of the awareness and effectiveness of IT security programs in a large publicly funded health care system.

    PubMed

    Hepp, Shelanne L; Tarraf, Rima C; Birney, Arden; Arain, Mubashir Aslam

    2017-01-01

    Electronic health records are becoming increasingly common in the health care industry. Although information technology (IT) poses many benefits to improving health care and ease of access to information, there are also security and privacy risks. Educating health care providers is necessary to ensure proper use of health information systems and IT and reduce undesirable outcomes. This study evaluated employees' awareness and perceptions of the effectiveness of two IT educational training modules within a large publicly funded health care system in Canada. Semi-structured interviews and focus groups included a variety of professional roles within the organisation. Participants also completed a brief demographic data sheet. With the consent of participants, all interviews and focus groups were audio recorded. Thematic analysis and descriptive statistics were used to evaluate the effectiveness of the IT security training modules. Five main themes emerged: (i) awareness of the IT training modules, (ii) the content of modules, (iii) staff perceptions about differences between IT security and privacy issues, (iv) common breaches of IT security and privacy, and (v) challenges and barriers to completing the training program. Overall, nonclinical staff were more likely to be aware of the training modules than were clinical staff. We found e-learning was a feasible way to educate a large number of employees. However, health care providers required a module on IT security and privacy that was relatable and applicable to their specific roles. Strategies to improve staff education and mitigate against IT security and privacy risks are discussed. Future research should focus on integrating health IT competencies into the educational programs for health care professionals.

  9. Microarrays Made Simple: "DNA Chips" Paper Activity

    ERIC Educational Resources Information Center

    Barnard, Betsy

    2006-01-01

    DNA microarray technology is revolutionizing biological science. DNA microarrays (also called DNA chips) allow simultaneous screening of many genes for changes in expression between different cells. Now researchers can obtain information about genes in days or weeks that used to take months or years. The paper activity described in this article…

  10. Microarrays Made Simple: "DNA Chips" Paper Activity

    ERIC Educational Resources Information Center

    Barnard, Betsy

    2006-01-01

    DNA microarray technology is revolutionizing biological science. DNA microarrays (also called DNA chips) allow simultaneous screening of many genes for changes in expression between different cells. Now researchers can obtain information about genes in days or weeks that used to take months or years. The paper activity described in this article…

  11. Caught you: threats to confidentiality due to the public release of large-scale genetic data sets

    PubMed Central

    2010-01-01

    Background Large-scale genetic data sets are frequently shared with other research groups and even released on the Internet to allow for secondary analysis. Study participants are usually not informed about such data sharing because data sets are assumed to be anonymous after stripping off personal identifiers. Discussion The assumption of anonymity of genetic data sets, however, is tenuous because genetic data are intrinsically self-identifying. Two types of re-identification are possible: the "Netflix" type and the "profiling" type. The "Netflix" type needs another small genetic data set, usually with less than 100 SNPs but including a personal identifier. This second data set might originate from another clinical examination, a study of leftover samples or forensic testing. When merged to the primary, unidentified set it will re-identify all samples of that individual. Even with no second data set at hand, a "profiling" strategy can be developed to extract as much information as possible from a sample collection. Starting with the identification of ethnic subgroups along with predictions of body characteristics and diseases, the asthma kids case as a real-life example is used to illustrate that approach. Summary Depending on the degree of supplemental information, there is a good chance that at least a few individuals can be identified from an anonymized data set. Any re-identification, however, may potentially harm study participants because it will release individual genetic disease risks to the public. PMID:21190545

  12. Caught you: threats to confidentiality due to the public release of large-scale genetic data sets.

    PubMed

    Wjst, Matthias

    2010-12-29

    Large-scale genetic data sets are frequently shared with other research groups and even released on the Internet to allow for secondary analysis. Study participants are usually not informed about such data sharing because data sets are assumed to be anonymous after stripping off personal identifiers. The assumption of anonymity of genetic data sets, however, is tenuous because genetic data are intrinsically self-identifying. Two types of re-identification are possible: the "Netflix" type and the "profiling" type. The "Netflix" type needs another small genetic data set, usually with less than 100 SNPs but including a personal identifier. This second data set might originate from another clinical examination, a study of leftover samples or forensic testing. When merged to the primary, unidentified set it will re-identify all samples of that individual. Even with no second data set at hand, a "profiling" strategy can be developed to extract as much information as possible from a sample collection. Starting with the identification of ethnic subgroups along with predictions of body characteristics and diseases, the asthma kids case as a real-life example is used to illustrate that approach. Depending on the degree of supplemental information, there is a good chance that at least a few individuals can be identified from an anonymized data set. Any re-identification, however, may potentially harm study participants because it will release individual genetic disease risks to the public.

  13. QuickMap: a public tool for large-scale gene therapy vector insertion site mapping and analysis.

    PubMed

    Appelt, J-U; Giordano, F A; Ecker, M; Roeder, I; Grund, N; Hotz-Wagenblatt, A; Opelz, G; Zeller, W J; Allgayer, H; Fruehauf, S; Laufs, S

    2009-07-01

    Several events of insertional mutagenesis in pre-clinical and clinical gene therapy studies have created intense interest in assessing the genomic insertion profiles of gene therapy vectors. For the construction of such profiles, vector-flanking sequences detected by inverse PCR, linear amplification-mediated-PCR or ligation-mediated-PCR need to be mapped to the host cell's genome and compared to a reference set. Although remarkable progress has been achieved in mapping gene therapy vector insertion sites, public reference sets are lacking, as are the possibilities to quickly detect non-random patterns in experimental data. We developed a tool termed QuickMap, which uniformly maps and analyzes human and murine vector-flanking sequences within seconds (available at www.gtsg.org). Besides information about hits in chromosomes and fragile sites, QuickMap automatically determines insertion frequencies in +/- 250 kb adjacency to genes, cancer genes, pseudogenes, transcription factor and (post-transcriptional) miRNA binding sites, CpG islands and repetitive elements (short interspersed nuclear elements (SINE), long interspersed nuclear elements (LINE), Type II elements and LTR elements). Additionally, all experimental frequencies are compared with the data obtained from a reference set, containing 1 000 000 random integrations ('random set'). Thus, for the first time a tool allowing high-throughput profiling of gene therapy vector insertion sites is available. It provides a basis for large-scale insertion site analyses, which is now urgently needed to discover novel gene therapy vectors with 'safe' insertion profiles.

  14. Washing scaling of GeneChip microarray expression

    PubMed Central

    2010-01-01

    Background Post-hybridization washing is an essential part of microarray experiments. Both the quality of the experimental washing protocol and adequate consideration of washing in intensity calibration ultimately affect the quality of the expression estimates extracted from the microarray intensities. Results We conducted experiments on GeneChip microarrays with altered protocols for washing, scanning and staining to study the probe-level intensity changes as a function of the number of washing cycles. For calibration and analysis of the intensity data we make use of the 'hook' method which allows intensity contributions due to non-specific and specific hybridization of perfect match (PM) and mismatch (MM) probes to be disentangled in a sequence specific manner. On average, washing according to the standard protocol removes about 90% of the non-specific background and about 30-50% and less than 10% of the specific targets from the MM and PM, respectively. Analysis of the washing kinetics shows that the signal-to-noise ratio doubles roughly every ten stringent washing cycles. Washing can be characterized by time-dependent rate constants which reflect the heterogeneous character of target binding to microarray probes. We propose an empirical washing function which estimates the survival of probe bound targets. It depends on the intensity contribution due to specific and non-specific hybridization per probe which can be estimated for each probe using existing methods. The washing function allows probe intensities to be calibrated for the effect of washing. On a relative scale, proper calibration for washing markedly increases expression measures, especially in the limit of small and large values. Conclusions Washing is among the factors which potentially distort expression measures. The proposed first-order correction method allows direct implementation in existing calibration algorithms for microarray data. We provide an experimental 'washing data set' which might

  15. Tissue Microarrays in Clinical Oncology

    PubMed Central

    Voduc, David; Kenney, Challayne; Nielsen, Torsten O.

    2008-01-01

    The tissue microarray is a recently-implemented, high-throughput technology for the analysis of molecular markers in oncology. This research tool permits the rapid assessment of a biomarker in thousands of tumor samples, using commonly available laboratory assays such as immunohistochemistry and in-situ hybridization. Although introduced less than a decade ago, the TMA has proven to be invaluable in the study of tumor biology, the development of diagnostic tests, and the investigation of oncological biomarkers. This review describes the impact of TMA-based research in clinical oncology and its potential future applications. Technical aspects of TMA construction, and the advantages and disadvantages inherent to this technology are also discussed. PMID:18314063

  16. ArrayPipe: a flexible processing pipeline for microarray data

    PubMed Central

    Hokamp, Karsten; Roche, Fiona M.; Acab, Michael; Rousseau, Marc-Etienne; Kuo, Byron; Goode, David; Aeschliman, Dana; Bryan, Jenny; Babiuk, Lorne A.; Hancock, Robert E. W.; Brinkman, Fiona S. L.

    2004-01-01

    A number of microarray analysis software packages exist already; however, none combines the user-friendly features of a web-based interface with potential ability to analyse multiple arrays at once using flexible analysis steps. The ArrayPipe web server (freely available at www.pathogenomics.ca/arraypipe) allows the automated application of complex analyses to microarray data which can range from single slides to large data sets including replicates and dye-swaps. It handles output from most commonly used quantification software packages for dual-labelled arrays. Application features range from quality assessment of slides through various data visualizations to multi-step analyses including normalization, detection of differentially expressed genes, andcomparison and highlighting of gene lists. A highly customizable action set-up facilitates unrestricted arrangement of functions, which can be stored as action profiles. A unique combination of web-based and command-line functionality enables comfortable configuration of processes that can be repeatedly applied to large data sets in high throughput. The output consists of reports formatted as standard web pages and tab-delimited lists of calculated values that can be inserted into other analysis programs. Additional features, such as web-based spreadsheet functionality, auto-parallelization and password protection make this a powerful tool in microarray research for individuals and large groups alike. PMID:15215429

  17. High quality protein microarray using in situ protein purification

    PubMed Central

    Kwon, Keehwan; Grose, Carissa; Pieper, Rembert; Pandya, Gagan A; Fleischmann, Robert D; Peterson, Scott N

    2009-01-01

    Background In the postgenomic era, high throughput protein expression and protein microarray technologies have progressed markedly permitting screening of therapeutic reagents and discovery of novel protein functions. Hexa-histidine is one of the most commonly used fusion tags for protein expression due to its small size and convenient purification via immobilized metal ion affinity chromatography (IMAC). This purification process has been adapted to the protein microarray format, but the quality of in situ His-tagged protein purification on slides has not been systematically evaluated. We established methods to determine the level of purification of such proteins on metal chelate-modified slide surfaces. Optimized in situ purification of His-tagged recombinant proteins has the potential to become the new gold standard for cost-effective generation of high-quality and high-density protein microarrays. Results Two slide surfaces were examined, chelated Cu2+ slides suspended on a polyethylene glycol (PEG) coating and chelated Ni2+ slides immobilized on a support without PEG coating. Using PEG-coated chelated Cu2+ slides, consistently higher purities of recombinant proteins were measured. An optimized wash buffer (PBST) composed of 10 mM phosphate buffer, 2.7 mM KCl, 140 mM NaCl and 0.05% Tween 20, pH 7.4, further improved protein purity levels. Using Escherichia coli cell lysates expressing 90 recombinant Streptococcus pneumoniae proteins, 73 proteins were successfully immobilized, and 66 proteins were in situ purified with greater than 90% purity. We identified several antigens among the in situ-purified proteins via assays with anti-S. pneumoniae rabbit antibodies and a human patient antiserum, as a demonstration project of large scale microarray-based immunoproteomics profiling. The methodology is compatible with higher throughput formats of in vivo protein expression, eliminates the need for resin-based purification and circumvents protein solubility and

  18. In control: systematic assessment of microarray performance.

    PubMed

    van Bakel, Harm; Holstege, Frank C P

    2004-10-01

    Expression profiling using DNA microarrays is a powerful technique that is widely used in the life sciences. How reliable are microarray-derived measurements? The assessment of performance is challenging because of the complicated nature of microarray experiments and the many different technology platforms. There is a mounting call for standards to be introduced, and this review addresses some of the issues that are involved. Two important characteristics of performance are accuracy and precision. The assessment of these factors can be either for the purpose of technology optimization or for the evaluation of individual microarray hybridizations. Microarray performance has been evaluated by at least four approaches in the past. Here, we argue that external RNA controls offer the most versatile system for determining performance and describe how such standards could be implemented. Other uses of external controls are discussed, along with the importance of probe sequence availability and the quantification of labelled material.

  19. Microarray Applications in Microbial Ecology Research.

    SciTech Connect

    Gentry, T.; Schadt, C.; Zhou, J.

    2006-04-06

    Microarray technology has the unparalleled potential tosimultaneously determine the dynamics and/or activities of most, if notall, of the microbial populations in complex environments such as soilsand sediments. Researchers have developed several types of arrays thatcharacterize the microbial populations in these samples based on theirphylogenetic relatedness or functional genomic content. Several recentstudies have used these microarrays to investigate ecological issues;however, most have only analyzed a limited number of samples withrelatively few experiments utilizing the full high-throughput potentialof microarray analysis. This is due in part to the unique analyticalchallenges that these samples present with regard to sensitivity,specificity, quantitation, and data analysis. This review discussesspecific applications of microarrays to microbial ecology research alongwith some of the latest studies addressing the difficulties encounteredduring analysis of complex microbial communities within environmentalsamples. With continued development, microarray technology may ultimatelyachieve its potential for comprehensive, high-throughput characterizationof microbial populations in near real-time.

  20. Chaotic mixer improves microarray hybridization.

    PubMed

    McQuain, Mark K; Seale, Kevin; Peek, Joel; Fisher, Timothy S; Levy, Shawn; Stremler, Mark A; Haselton, Frederick R

    2004-02-15

    Hybridization is an important aspect of microarray experimental design which influences array signal levels and the repeatability of data within an array and across different arrays. Current methods typically require 24h and use target inefficiently. In these studies, we compare hybridization signals obtained in conventional static hybridization, which depends on diffusional target delivery, with signals obtained in a dynamic hybridization chamber, which employs a fluid mixer based on chaotic advection theory to deliver targets across a conventional glass slide array. Microarrays were printed with a pattern of 102 identical probe spots containing a 65-mer oligonucleotide capture probe. Hybridization of a 725-bp fluorescently labeled target was used to measure average target hybridization levels, local signal-to-noise ratios, and array hybridization uniformity. Dynamic hybridization for 1h with 1 or 10ng of target DNA increased hybridization signal intensities approximately threefold over a 24-h static hybridization. Similarly, a 10- or 60-min dynamic hybridization of 10ng of target DNA increased hybridization signal intensities fourfold over a 24h static hybridization. In time course studies, static hybridization reached a maximum within 8 to 12h using either 1 or 10ng of target. In time course studies using the dynamic hybridization chamber, hybridization using 1ng of target increased to a maximum at 4h and that using 10ng of target did not vary over the time points tested. In comparison to static hybridization, dynamic hybridization reduced the signal-to-noise ratios threefold and reduced spot-to-spot variation twofold. Therefore, we conclude that dynamic hybridization based on a chaotic mixer design improves both the speed of hybridization and the maximum level of hybridization while increasing signal-to-noise ratios and reducing spot-to-spot variation.

  1. Probe Region Expression Estimation for RNA-Seq Data for Improved Microarray Comparability

    PubMed Central

    Uziela, Karolis; Honkela, Antti

    2015-01-01

    Rapidly growing public gene expression databases contain a wealth of data for building an unprecedentedly detailed picture of human biology and disease. This data comes from many diverse measurement platforms that make integrating it all difficult. Although RNA-sequencing (RNA-seq) is attracting the most attention, at present, the rate of new microarray studies submitted to public databases far exceeds the rate of new RNA-seq studies. There is clearly a need for methods that make it easier to combine data from different technologies. In this paper, we propose a new method for processing RNA-seq data that yields gene expression estimates that are much more similar to corresponding estimates from microarray data, hence greatly improving cross-platform comparability. The method we call PREBS is based on estimating the expression from RNA-seq reads overlapping the microarray probe regions, and processing these estimates with standard microarray summarisation algorithms. Using paired microarray and RNA-seq samples from TCGA LAML data set we show that PREBS expression estimates derived from RNA-seq are more similar to microarray-based expression estimates than those from other RNA-seq processing methods. In an experiment to retrieve paired microarray samples from a database using an RNA-seq query sample, gene signatures defined based on PREBS expression estimates were found to be much more accurate than those from other methods. PREBS also allows new ways of using RNA-seq data, such as expression estimation for microarray probe sets. An implementation of the proposed method is available in the Bioconductor package “prebs.” PMID:25966034

  2. Probe Region Expression Estimation for RNA-Seq Data for Improved Microarray Comparability.

    PubMed

    Uziela, Karolis; Honkela, Antti

    2015-01-01

    Rapidly growing public gene expression databases contain a wealth of data for building an unprecedentedly detailed picture of human biology and disease. This data comes from many diverse measurement platforms that make integrating it all difficult. Although RNA-sequencing (RNA-seq) is attracting the most attention, at present, the rate of new microarray studies submitted to public databases far exceeds the rate of new RNA-seq studies. There is clearly a need for methods that make it easier to combine data from different technologies. In this paper, we propose a new method for processing RNA-seq data that yields gene expression estimates that are much more similar to corresponding estimates from microarray data, hence greatly improving cross-platform comparability. The method we call PREBS is based on estimating the expression from RNA-seq reads overlapping the microarray probe regions, and processing these estimates with standard microarray summarisation algorithms. Using paired microarray and RNA-seq samples from TCGA LAML data set we show that PREBS expression estimates derived from RNA-seq are more similar to microarray-based expression estimates than those from other RNA-seq processing methods. In an experiment to retrieve paired microarray samples from a database using an RNA-seq query sample, gene signatures defined based on PREBS expression estimates were found to be much more accurate than those from other methods. PREBS also allows new ways of using RNA-seq data, such as expression estimation for microarray probe sets. An implementation of the proposed method is available in the Bioconductor package "prebs."

  3. Ultrasensitive microarray bioassays using cyanine5 dye-doped silica nanoparticles

    NASA Astrophysics Data System (ADS)

    Flynn, S. P.; Kelleher, S. M.; Acorn, J. N.; Kurzbuch, D.; Daniels, S.; McDonagh, C.; Clancy, E.; Smith, T. J.; Nooney, R.

    2016-11-01

    Herein we report the use of high brightness Cyanine5-doped silica nanoparticles (NPs) for the detection of antibodies or DNA in microarray bioassays. NP labels showed negligible non-specific binding, greater sensitivity and lower limits of detection when compared to free dye-labelled biomolecules. Moreover, the spotted microarrays used in this study required low NP and antibody concentrations to generate large data sets with improved statistical accuracy. These NPs have significant potential for use in biosensing for disease detection.

  4. Individual and organizational factors related to community clinicians’ use of therapy techniques in a large public mental health system

    PubMed Central

    Marcus, Steven; Aarons, Gregory A.; Hoagwood, Kimberly E.; Schoenwald, Sonja; Evans, Arthur C.; Hurford, Matthew O.; Hadley, Trevor; Barg, Frances K.; Walsh, Lucia M.; Adams, Danielle R.; Mandell, David S.

    2015-01-01

    Importance Few studies have examined the effects of both clinician and organizational characteristics on the use of evidence-based practices in mental healthcare. Improved understanding of these factors could guide future implementation efforts to ensure effective adoption, implementation, and sustainment of evidence-based practices. Objective To estimate the relative contribution of clinician and organizational factors on clinician self-reported use of cognitive-behavioral, family, and psychodynamic techniques within the context of a large-scale effort to increase use of evidence-based practices in an urban public mental health system serving youth and families. Design Observational and cross-sectional. Data collected in 2013. Setting Twenty-three organizations. Participants We used purposive sampling to recruit the 29 largest child-serving agencies, which together serve approximately 80% of youth receiving publically funded mental health care. The final sample included 19 agencies with 23 sites, 130 therapists, 36 supervisors, and 22 executive administrators. Main Outcome Measures Clinician self-reported use of cognitive-behavioral, family, and psychodynamic techniques, as measured by the Therapist Procedures Checklist – Family Revised. Results Linear mixed-effects regression models were used; models included random intercepts for organization to account for nesting of clinicians within organization. Clinician factors accounted for the following percentage of the overall variation: cognitive-behavioral (16%), family (7%), psychodynamic (20%). Organizational factors accounted for the following percentage of the overall variation: cognitive-behavioral (23%), family (19%), psychodynamic (7%). Older clinicians and clinicians with more open attitudes were more likely to endorse use of cognitive behavioral techniques, as were those in organizations that had spent fewer years participating in evidence-based practice initiatives, had more resistant cultures, and had

  5. A large-scale study of bacterial contamination of drinking water and its public health impact in Nepal.

    PubMed

    Rai, S K; Ono, K; Yanagida, J I; Ishiyama-Imura, S; Kurokawa, M; Rai, C K

    2012-09-01

    Bacterial contamination of drinking water is a major public health in Nepal. A large scale study on contamination of drinking water was done covering all three ecological belts (mountain, hill and Terai) in all five (eastern, central, western, mid-western and far-western) development regions of Nepal during 2009-2011. Of the total 506 water samples studied, one-forth (25.1%; 127/506) were visually turbid. Bacteriologically, 88.5% (448/506) samples were positive for total coliform (TC) whereas 56.5% (286/506) were positive for fecal coliform (FC) (Esch. coli). The TC positive rate ranged from 53.8% in Damak (Jhapa) to 100.0% in different districts. The FC positive rate varied more widely ranging from 10.0% in Bharatpur City (Chitawan) to 100.0% in Baglung Township (Baglung) with over 50.0% in most of the districts (over 75.0% in eight districts). Both TC and FC positive rate were highest in Far-western Development Region (DR). High TC positive rate (96.7%) in Far-western DR was followed by Western DR (93.9%), Eastern DR (89.2%), Central DR (87.0%) and Mid-western DR (74.6%). Highest FC positive rate (65.5%) in Far-western DR was followed by Med-western DR (63.5%), Western DR (55.9%), Central DR (53.2%) and Eastern DR (52.0%). TC positive was highest (90.7%) in hills followed by mountain (89.7%) and Terai (plain) (84.1%) belt. In contrast, FC positive rate was highest (66.2%) in mountain, followed by hills (58.0%) and Terai (49.7%). Of the total 506, 335 were piped tap water, 129 were boring water, 16 natural tap (spout), 16 were well (sallow/deep well) and 10 were mineral/uroguard treated water. TC positive rate was very high (81.2% to 100.0%) in different type water samples (piped tap: 90.1%; boring water: 85.2%; natural spout/tap: 81.2%; well water 100.0% and mineral water/uroguard treated water: 80.0%). FC positive rate ranged from 0.0% in mineral water/uroguard treated water to 93.7% in well water samples. These findings are of serious public health concern with

  6. Estrogen receptor biomarker genes and microarray accession numbers used in Ryan et al.

    EPA Pesticide Factsheets

    List of biomarker genes used to predict estrogen receptor activity in MCF-7 cells; list of microarray accession numbers used in the study.This dataset is associated with the following publication:Vanduyn, N., B. Chorley , R. Tice, R. Judson , and C. Corton. Moving Toward Integrating Gene Expression Profiling into High-throughput Testing:A Gene Expression Biomarker Accurately Predicts Estrogen Receptor α Modulation in a Microarray Compendium. PLoS ONE. Public Library of Science, San Francisco, CA, USA, 151(1): 88-103, (2016).

  7. Microarray-integrated optoelectrofluidic immunoassay system.

    PubMed

    Han, Dongsik; Park, Je-Kyun

    2016-05-01

    A microarray-based analytical platform has been utilized as a powerful tool in biological assay fields. However, an analyte depletion problem due to the slow mass transport based on molecular diffusion causes low reaction efficiency, resulting in a limitation for practical applications. This paper presents a novel method to improve the efficiency of microarray-based immunoassay via an optically induced electrokinetic phenomenon by integrating an optoelectrofluidic device with a conventional glass slide-based microarray format. A sample droplet was loaded between the microarray slide and the optoelectrofluidic device on which a photoconductive layer was deposited. Under the application of an AC voltage, optically induced AC electroosmotic flows caused by a microarray-patterned light actively enhanced the mass transport of target molecules at the multiple assay spots of the microarray simultaneously, which reduced tedious reaction time from more than 30 min to 10 min. Based on this enhancing effect, a heterogeneous immunoassay with a tiny volume of sample (5 μl) was successfully performed in the microarray-integrated optoelectrofluidic system using immunoglobulin G (IgG) and anti-IgG, resulting in improved efficiency compared to the static environment. Furthermore, the application of multiplex assays was also demonstrated by multiple protein detection.

  8. Oligonucleotide microarray for the identification of potential mycotoxigenic fungi

    PubMed Central

    2010-01-01

    Background Mycotoxins are secondary metabolites which are produced by numerous fungi and pose a continuous challenge to the safety and quality of food commodities in South Africa. These toxins have toxicologically relevant effects on humans and animals that eat contaminated foods. In this study, a diagnostic DNA microarray was developed for the identification of the most common food-borne fungi, as well as the genes leading to toxin production. Results A total of 40 potentially mycotoxigenic fungi isolated from different food commodities, as well as the genes that are involved in the mycotoxin synthetic pathways, were analyzed. For fungal identification, oligonucleotide probes were designed by exploiting the sequence variations of the elongation factor 1-alpha (EF-1 α) coding regions and the internal transcribed spacer (ITS) regions of the rRNA gene cassette. For the detection of fungi able to produce mycotoxins, oligonucleotide probes directed towards genes leading to toxin production from different fungal strains were identified in data available in the public domain. The probes selected for fungal identification and the probes specific for toxin producing genes were spotted onto microarray slides. Conclusions The diagnostic microarray developed can be used to identify single pure strains or cultures of potentially mycotoxigenic fungi as well as genes leading to toxin production in both laboratory samples and maize-derived foods offering an interesting potential for microbiological laboratories. PMID:20307326

  9. Chemical microarray: a new tool for drug screening and discovery.

    PubMed

    Ma, Haiching; Horiuchi, Kurumi Y

    2006-07-01

    HTS with microtiter plates has been the major tool used in the pharmaceutical industry to explore chemical diversity space and to identify active compounds and pharmacophores for specific biological targets. However, HTS faces a daunting challenge regarding the fast-growing numbers of drug targets arising from genomic and proteomic research, and large chemical libraries generated from high-throughput synthesis. There is an urgent need to find new ways to profile the activity of large numbers of chemicals against hundreds of biological targets in a fast, low-cost fashion. Chemical microarray can rise to this challenge because it has the capability of identifying and evaluating small molecules as potential therapeutic reagents. During the past few years, chemical microarray technology, with different surface chemistries and activation strategies, has generated many successes in the evaluation of chemical-protein interactions, enzyme activity inhibition, target identification, signal pathway elucidation and cell-based functional analysis. The success of chemical microarray technology will provide unprecedented possibilities and capabilities for parallel functional analysis of tremendous amounts of chemical compounds.

  10. Bioinformatics and Microarray Data Analysis on the Cloud.

    PubMed

    Calabrese, Barbara; Cannataro, Mario

    2016-01-01

    High-throughput platforms such as microarray, mass spectrometry, and next-generation sequencing are producing an increasing volume of omics data that needs large data storage and computing power. Cloud computing offers massive scalable computing and storage, data sharing, on-demand anytime and anywhere access to resources and applications, and thus, it may represent the key technology for facing those issues. In fact, in the recent years it has been adopted for the deployment of different bioinformatics solutions and services both in academia and in the industry. Although this, cloud computing presents several issues regarding the security and privacy of data, that are particularly important when analyzing patients data, such as in personalized medicine. This chapter reviews main academic and industrial cloud-based bioinformatics solutions; with a special focus on microarray data analysis solutions and underlines main issues and problems related to the use of such platforms for the storage and analysis of patients data.

  11. Progress in the application of DNA microarrays.

    PubMed Central

    Lobenhofer, E K; Bushel, P R; Afshari, C A; Hamadeh, H K

    2001-01-01

    Microarray technology has been applied to a variety of different fields to address fundamental research questions. The use of microarrays, or DNA chips, to study the gene expression profiles of biologic samples began in 1995. Since that time, the fundamental concepts behind the chip, the technology required for making and using these chips, and the multitude of statistical tools for analyzing the data have been extensively reviewed. For this reason, the focus of this review will be not on the technology itself but on the application of microarrays as a research tool and the future challenges of the field. PMID:11673116

  12. Metric learning for DNA microarray data analysis

    NASA Astrophysics Data System (ADS)

    Takeuchi, Ichiro; Nakagawa, Masao; Seto, Masao

    2009-12-01

    In many microarray studies, gene set selection is an important preliminary step for subsequent main task such as tumor classification, cancer subtype identification, etc. In this paper, we investigate the possibility of using metric learning as an alternative to gene set selection. We develop a simple metric learning algorithm aiming to use it for microarray data analysis. Exploiting a property of the algorithm, we introduce a novel approach for extending the metric learning to be adaptive. We apply the algorithm to previously studied microarray data on malignant lymphoma subtype identification.

  13. DNA Microarrays in Herbal Drug Research

    PubMed Central

    Chavan, Preeti; Joshi, Kalpana; Patwardhan, Bhushan

    2006-01-01

    Natural products are gaining increased applications in drug discovery and development. Being chemically diverse they are able to modulate several targets simultaneously in a complex system. Analysis of gene expression becomes necessary for better understanding of molecular mechanisms. Conventional strategies for expression profiling are optimized for single gene analysis. DNA microarrays serve as suitable high throughput tool for simultaneous analysis of multiple genes. Major practical applicability of DNA microarrays remains in DNA mutation and polymorphism analysis. This review highlights applications of DNA microarrays in pharmacodynamics, pharmacogenomics, toxicogenomics and quality control of herbal drugs and extracts. PMID:17173108

  14. Assessing differential expression in two-color microarrays: a resampling-based empirical Bayes approach.

    PubMed

    Li, Dongmei; Le Pape, Marc A; Parikh, Nisha I; Chen, Will X; Dye, Timothy D

    2013-01-01

    Microarrays are widely used for examining differential gene expression, identifying single nucleotide polymorphisms, and detecting methylation loci. Multiple testing methods in microarray data analysis aim at controlling both Type I and Type II error rates; however, real microarray data do not always fit their distribution assumptions. Smyth's ubiquitous parametric method, for example, inadequately accommodates violations of normality assumptions, resulting in inflated Type I error rates. The Significance Analysis of Microarrays, another widely used microarray data analysis method, is based on a permutation test and is robust to non-normally distributed data; however, the Significance Analysis of Microarrays method fold change criteria are problematic, and can critically alter the conclusion of a study, as a result of compositional changes of the control data set in the analysis. We propose a novel approach, combining resampling with empirical Bayes methods: the Resampling-based empirical Bayes Methods. This approach not only reduces false discovery rates for non-normally distributed microarray data, but it is also impervious to fold change threshold since no control data set selection is needed. Through simulation studies, sensitivities, specificities, total rejections, and false discovery rates are compared across the Smyth's parametric method, the Significance Analysis of Microarrays, and the Resampling-based empirical Bayes Methods. Differences in false discovery rates controls between each approach are illustrated through a preterm delivery methylation study. The results show that the Resampling-based empirical Bayes Methods offer significantly higher specificity and lower false discovery rates compared to Smyth's parametric method when data are not normally distributed. The Resampling-based empirical Bayes Methods also offers higher statistical power than the Significance Analysis of Microarrays method when the proportion of significantly differentially

  15. Striptease on glass: validation of an improved stripping procedure for in situ microarrays.

    PubMed

    Hahnke, Karin; Jacobsen, Marc; Gruetzkau, Andreas; Gruen, Joachim R; Koch, Markus; Emoto, Masashi; Meyer, Thomas F; Walduck, Anna; Kaufmann, Stefan H E; Mollenkopf, Hans-Joachim

    2007-01-30

    Microarrays have rapidly become an indispensable tool for gene analysis. Microarray experiments can be cost prohibitive, however, largely due to the price of the arrays themselves. Whilst different methods for stripping filter arrays on membranes have been established, only very few protocols are published for thermal and chemical stripping of microarrays on glass. Most of these protocols for stripping microarrays on glass were developed in combination with specific surface chemistry and different coatings for covalently immobilizing presynthesized DNA in a deposition process. We have developed a method for stripping commercial in situ microarrays using a multi-step procedure. We present a method that uses mild chemical degradation complemented by enzymatic treatment. We took advantage of the differences in biochemical properties of covalently linked DNA oligonucleotides on in situ synthesized microarrays and the antisense cRNA hybridization probes. The success of stripping protocols for microarrays on glass was critically dependent on the type of arrays, the nature of sample used for hybridization, as well as hybridization and washing conditions. The protocol employs alkali hydrolysis of the cRNA, several enzymatic degradation steps using RNAses and Proteinase K, combined with appropriate washing steps. Stripped arrays were rehybridized using the same protocols as for new microarrays. The stripping method was validated with microarrays from different suppliers and rehybridization of stripped in situ arrays yielded comparable results to hybridizations done on unused, new arrays with no significant loss in precision or accuracy. We show that stripping of commercial in situ arrays is feasible and that reuse of stripped arrays gave similar results compared to unused ones. This was true even for biological samples that show only slight differences in their expression profiles. Our analyses indicate that the stripping procedure does not significantly influence data

  16. A versatile approach to high-throughput microarrays using thiol-ene chemistry

    NASA Astrophysics Data System (ADS)

    Gupta, Nalini; Lin, Brian F.; Campos, Luis M.; Dimitriou, Michael D.; Hikita, Sherry T.; Treat, Neil D.; Tirrell, Matthew V.; Clegg, Dennis O.; Kramer, Edward J.; Hawker, Craig J.

    2010-02-01

    Microarray technology has become extremely useful in expediting the investigation of large libraries of materials in a variety of biomedical applications, such as in DNA chips, protein and cellular microarrays. In the development of cellular microarrays, traditional high-throughput printing strategies on stiff, glass substrates and non-covalent attachment methods are limiting. We have developed a facile strategy to fabricate multifunctional high-throughput microarrays embedded at the surface of a hydrogel substrate using thiol-ene chemistry. This user-friendly method provides a platform for the immobilization of a combination of bioactive and diagnostic molecules, such as peptides and dyes, at the surface of poly(ethylene glycol)-based hydrogels. The robust and orthogonal nature of thiol-ene chemistry allows for a range of covalent attachment strategies in a fast and reliable manner, and two complementary strategies for the attachment of active molecules are demonstrated.

  17. Tissue Microarray Analysis Applied to Bone Diagenesis

    PubMed Central

    Mello, Rafael Barrios; Silva, Maria Regina Regis; Alves, Maria Teresa Seixas; Evison, Martin Paul; Guimarães, Marco Aurelio; Francisco, Rafaella Arrabaca; Astolphi, Rafael Dias; Iwamura, Edna Sadayo Miazato

    2017-01-01

    Taphonomic processes affecting bone post mortem are important in forensic, archaeological and palaeontological investigations. In this study, the application of tissue microarray (TMA) analysis to a sample of femoral bone specimens from 20 exhumed individuals of known period of burial and age at death is described. TMA allows multiplexing of subsamples, permitting standardized comparative analysis of adjacent sections in 3-D and of representative cross-sections of a large number of specimens. Standard hematoxylin and eosin, periodic acid-Schiff and silver methenamine, and picrosirius red staining, and CD31 and CD34 immunohistochemistry were applied to TMA sections. Osteocyte and osteocyte lacuna counts, percent bone matrix loss, and fungal spheroid element counts could be measured and collagen fibre bundles observed in all specimens. Decalcification with 7% nitric acid proceeded more rapidly than with 0.5 M EDTA and may offer better preservation of histological and cellular structure. No endothelial cells could be detected using CD31 and CD34 immunohistochemistry. Correlation between osteocytes per lacuna and age at death may reflect reported age-related responses to microdamage. Methodological limitations and caveats, and results of the TMA analysis of post mortem diagenesis in bone are discussed, and implications for DNA survival and recovery considered. PMID:28051148

  18. Ontology-Based Analysis of Microarray Data.

    PubMed

    Giuseppe, Agapito; Milano, Marianna

    2016-01-01

    The importance of semantic-based methods and algorithms for the analysis and management of biological data is growing for two main reasons. From a biological side, knowledge contained in ontologies is more and more accurate and complete, from a computational side, recent algorithms are using in a valuable way such knowledge. Here we focus on semantic-based management and analysis of protein interaction networks referring to all the approaches of analysis of protein-protein interaction data that uses knowledge encoded into biological ontologies. Semantic approaches for studying high-throughput data have been largely used in the past to mine genomic and expression data. Recently, the emergence of network approaches for investigating molecular machineries has stimulated in a parallel way the introduction of semantic-based techniques for analysis and management of network data. The application of these computational approaches to the study of microarray data can broad the application scenario of them and simultaneously can help the understanding of disease development and progress.

  19. Tissue microarray profiling in human heart failure.

    PubMed

    Lal, Sean; Nguyen, Lisa; Tezone, Rhenan; Ponten, Fredrik; Odeberg, Jacob; Li, Amy; Dos Remedios, Cristobal

    2016-09-01

    Tissue MicroArrays (TMAs) are a versatile tool for high-throughput protein screening, allowing qualitative analysis of a large number of samples on a single slide. We have developed a customizable TMA system that uniquely utilizes cryopreserved human cardiac samples from both heart failure and donor patients to produce formalin-fixed paraffin-embedded sections. Confirmatory upstream or downstream molecular studies can then be performed on the same (biobanked) cryopreserved tissue. In a pilot study, we applied our TMAs to screen for the expression of four-and-a-half LIM-domain 2 (FHL2), a member of the four-and-a-half LIM family. This protein has been implicated in the pathogenesis of heart failure in a variety of animal models. While FHL2 is abundant in the heart, not much is known about its expression in human heart failure. For this purpose, we generated an affinity-purified rabbit polyclonal anti-human FHL2 antibody. Our TMAs allowed high-throughput profiling of FHL2 protein using qualitative and semiquantitative immunohistochemistry that proved complementary to Western blot analysis. We demonstrated a significant relative reduction in FHL2 protein expression across different forms of human heart failure. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  20. Multi-platform microarray integration research

    NASA Astrophysics Data System (ADS)

    Wu, Ronghui; Lu, Lei

    2017-08-01

    There are more and more tumor data from different laboratories and different technology platforms. Data from independent laboratory is often difficult to explain and unreliable. So there comes a challenging task which is to develop robust integration algorithms to integrate microarray data from various experiments and platforms. We studied the traditional integration algorithm, and found that it was effective to use Combat to integrate the data. Combat is characterized not only in the integration of small samples, but also in the case of large samples. It is comparable with other integration algorithms and performs well on various evaluation indicators. But we find that Combat is a combination of mean and merging variance for several batches, and integrate directly without fully considering the information from sample data, which we believe will ignore a single Batch characteristics and parameters are estimated to be biased. So an improved algorithm is proposed to find the mean and variance for a single batch, and when integrating, consider the first principal component of a single batch and segment the sample using the first principal component, and then integrated. In the experimental part, we first evaluate our algorithm with the commonly used evaluation index.

  1. The emergence and diffusion of DNA microarray technology

    PubMed Central

    Lenoir, Tim; Giannella, Eric

    2006-01-01

    The network model of innovation widely adopted among researchers in the economics of science and technology posits relatively porous boundaries between firms and academic research programs and a bi-directional flow of inventions, personnel, and tacit knowledge between sites of university and industry innovation. Moreover, the model suggests that these bi-directional flows should be considered as mutual stimulation of research and invention in both industry and academe, operating as a positive feedback loop. One side of this bi-directional flow – namely; the flow of inventions into industry through the licensing of university-based technologies – has been well studied; but the reverse phenomenon of the stimulation of university research through the absorption of new directions emanating from industry has yet to be investigated in much detail. We discuss the role of federal funding of academic research in the microarray field, and the multiple pathways through which federally supported development of commercial microarray technologies have transformed core academic research fields. Our study confirms the picture put forward by several scholars that the open character of networked economies is what makes them truly innovative. In an open system innovations emerge from the network. The emergence and diffusion of microarray technologies we have traced here provides an excellent example of an open system of innovation in action. Whether they originated in a startup company environment that operated like a think-tank, such as Affymax, the research labs of a large firm, such as Agilent, or within a research university, the inventors we have followed drew heavily on knowledge resources from all parts of the network in bringing microarray platforms to light. Federal funding for high-tech startups and new industrial development was important at several phases in the early history of microarrays, and federal funding of academic researchers using microarrays was fundamental

  2. Feasibility and Preliminary Efficacy of an After-School Program for Middle Schoolers with ADHD: A Randomized Trial in a Large Public Middle School

    ERIC Educational Resources Information Center

    Molina, Brooke S. G.; Flory, Kate; Bukstein, Oscar G.; Greiner, Andrew R.; Baker, Jennifer L.; Krug, Vicky; Evans, Steven W.

    2008-01-01

    Objective: This pilot study tests the feasibility and preliminary efficacy of an after-school treatment program for middle schoolers with ADHD using a randomized clinical trial design. Method: A total of 23 students with ADHD (25% female, 48% African American) from a large public middle school were randomly assigned to a 10-week program or to…

  3. How Large Is the "Public Domain"? A Comparative Analysis of Ringer's 1961 Copyright Renewal Study and HathiTrust CRMS Data

    ERIC Educational Resources Information Center

    Wilkin, John P.

    2017-01-01

    The 1961 Copyright Office study on renewals, authored by Barbara Ringer, has cast an outsized influence on discussions of the U.S. 1923-1963 public domain. As more concrete data emerge from initiatives such as the large-scale determination process in the Copyright Review Management System (CRMS) project, questions are raised about the reliability…

  4. Feasibility and Preliminary Efficacy of an After-School Program for Middle Schoolers with ADHD: A Randomized Trial in a Large Public Middle School

    ERIC Educational Resources Information Center

    Molina, Brooke S. G.; Flory, Kate; Bukstein, Oscar G.; Greiner, Andrew R.; Baker, Jennifer L.; Krug, Vicky; Evans, Steven W.

    2008-01-01

    Objective: This pilot study tests the feasibility and preliminary efficacy of an after-school treatment program for middle schoolers with ADHD using a randomized clinical trial design. Method: A total of 23 students with ADHD (25% female, 48% African American) from a large public middle school were randomly assigned to a 10-week program or to…

  5. Class Counts: Exploring Differences in Academic and Social Integration between Working-Class and Middle/Upper-Class Students at Large, Public Research Universities

    ERIC Educational Resources Information Center

    Soria, Krista M.; Stebleton, Michael J.; Huesman, Ronald L., Jr.

    2013-01-01

    This multi-institutional study examines differences between working-class and middle/upper-class students at large, public research universities. Significant differences in factors related to working-class students' social integration (including satisfaction, campus climate, and sense of belonging) and academic integration (including collaborative…

  6. Class Counts: Exploring Differences in Academic and Social Integration between Working-Class and Middle/Upper-Class Students at Large, Public Research Universities

    ERIC Educational Resources Information Center

    Soria, Krista M.; Stebleton, Michael J.; Huesman, Ronald L., Jr.

    2013-01-01

    This multi-institutional study examines differences between working-class and middle/upper-class students at large, public research universities. Significant differences in factors related to working-class students' social integration (including satisfaction, campus climate, and sense of belonging) and academic integration (including collaborative…

  7. [DNA microarrays in parasitology and medical sciences].

    PubMed

    Jaros, Sławomir

    2006-01-01

    The article presents the current knowledge on the microarray technique and its applications in medical sciences and parasitology. The first part of the article is focused on the technical aspects (microarray preparation, different microarray platforms, probes preparation, hybridization and signal detection). The article also describes possible ways of proceeding during laboratory work on organism of which the genome sequence is not known or has been only partially sequenced. The second part of the review describes how microarray technique have been, or possibly will be, used for better understanding parasite life cycles and development, host-parasite relationship, comparative genomics of virulent organisms, develpoment vaccines against the most virulent parasites and host responses to infection.

  8. Protein Microarrays: Novel Developments and Applications

    PubMed Central

    Berrade, Luis; Garcia, Angie E.

    2011-01-01

    Protein microarray technology possesses some of the greatest potential for providing direct information on protein function and potential drug targets. For example, functional protein microarrays are ideal tools suited for the mapping of biological pathways. They can be used to study most major types of interactions and enzymatic activities that take place in biochemical pathways and have been used for the analysis of simultaneous multiple biomolecular interactions involving protein-protein, protein-lipid, protein-DNA and protein-small molecule interactions. Because of this unique ability to analyze many kinds of molecular interactions en masse, the requirement of very small sample amount and the potential to be miniaturized and automated, protein microarrays are extremely well suited for protein profiling, drug discovery, drug target identification and clinical prognosis and diagnosis. The aim of this review is to summarize the most recent developments in the production, applications and analysis of protein microarrays. PMID:21116694

  9. PATMA: parser of archival tissue microarray.

    PubMed

    Roszkowiak, Lukasz; Lopez, Carlos

    2016-01-01

    Tissue microarrays are commonly used in modern pathology for cancer tissue evaluation, as it is a very potent technique. Tissue microarray slides are often scanned to perform computer-aided histopathological analysis of the tissue cores. For processing the image, splitting the whole virtual slide into images of individual cores is required. The only way to distinguish cores corresponding to specimens in the tissue microarray is through their arrangement. Unfortunately, distinguishing the correct order of cores is not a trivial task as they are not labelled directly on the slide. The main aim of this study was to create a procedure capable of automatically finding and extracting cores from archival images of the tissue microarrays. This software supports the work of scientists who want to perform further image processing on single cores. The proposed method is an efficient and fast procedure, working in fully automatic or semi-automatic mode. A total of 89% of punches were correctly extracted with automatic selection. With an addition of manual correction, it is possible to fully prepare the whole slide image for extraction in 2 min per tissue microarray. The proposed technique requires minimum skill and time to parse big array of cores from tissue microarray whole slide image into individual core images.

  10. PATMA: parser of archival tissue microarray

    PubMed Central

    2016-01-01

    Tissue microarrays are commonly used in modern pathology for cancer tissue evaluation, as it is a very potent technique. Tissue microarray slides are often scanned to perform computer-aided histopathological analysis of the tissue cores. For processing the image, splitting the whole virtual slide into images of individual cores is required. The only way to distinguish cores corresponding to specimens in the tissue microarray is through their arrangement. Unfortunately, distinguishing the correct order of cores is not a trivial task as they are not labelled directly on the slide. The main aim of this study was to create a procedure capable of automatically finding and extracting cores from archival images of the tissue microarrays. This software supports the work of scientists who want to perform further image processing on single cores. The proposed method is an efficient and fast procedure, working in fully automatic or semi-automatic mode. A total of 89% of punches were correctly extracted with automatic selection. With an addition of manual correction, it is possible to fully prepare the whole slide image for extraction in 2 min per tissue microarray. The proposed technique requires minimum skill and time to parse big array of cores from tissue microarray whole slide image into individual core images. PMID:27920955

  11. Evaluation of Surface Chemistries for Antibody Microarrays

    SciTech Connect

    Seurynck-Servoss, Shannon L.; White, Amanda M.; Baird, Cheryl L.; Rodland, Karin D.; Zangar, Richard C.

    2007-12-01

    Antibody microarrays are an emerging technology that promises to be a powerful tool for the detection of disease biomarkers. The current technology for protein microarrays has been primarily derived from DNA microarrays and is not fully characterized for use with proteins. For example, there are a myriad of surface chemistries that are commercially available for antibody microarrays, but no rigorous studies that compare these different surfaces. Therefore, we have used an enzyme-linked immunosorbent assay (ELISA) microarray platform to analyze 16 different commercially available slide types. Full standard curves were generated for 24 different assays. We found that this approach provides a rigorous and quantitative system for comparing the different slide types based on spot size and morphology, slide noise, spot background, lower limit of detection, and reproducibility. These studies demonstrate that the properties of the slide surface affect the activity of immobilized antibodies and the quality of data produced. Although many slide types can produce useful data, glass slides coated with poly-L-lysine or aminosilane, with or without activation with a crosslinker, consistently produce superior results in the ELISA microarray analyses we performed.

  12. The Impact of Photobleaching on Microarray Analysis

    PubMed Central

    von der Haar, Marcel; Preuß, John-Alexander; von der Haar, Kathrin; Lindner, Patrick; Scheper, Thomas; Stahl, Frank

    2015-01-01

    DNA-Microarrays have become a potent technology for high-throughput analysis of genetic regulation. However, the wide dynamic range of signal intensities of fluorophore-based microarrays exceeds the dynamic range of a single array scan by far, thus limiting the key benefit of microarray technology: parallelization. The implementation of multi-scan techniques represents a promising approach to overcome these limitations. These techniques are, in turn, limited by the fluorophores’ susceptibility to photobleaching when exposed to the scanner’s laser light. In this paper the photobleaching characteristics of cyanine-3 and cyanine-5 as part of solid state DNA microarrays are studied. The effects of initial fluorophore intensity as well as laser scanner dependent variables such as the photomultiplier tube’s voltage on bleaching and imaging are investigated. The resulting data is used to develop a model capable of simulating the expected degree of signal intensity reduction caused by photobleaching for each fluorophore individually, allowing for the removal of photobleaching-induced, systematic bias in multi-scan procedures. Single-scan applications also benefit as they rely on pre-scans to determine the optimal scanner settings. These findings constitute a step towards standardization of microarray experiments and analysis and may help to increase the lab-to-lab comparability of microarray experiment results. PMID:26378589

  13. Contributions to Statistical Problems Related to Microarray Data

    ERIC Educational Resources Information Center

    Hong, Feng

    2009-01-01

    Microarray is a high throughput technology to measure the gene expression. Analysis of microarray data brings many interesting and challenging problems. This thesis consists three studies related to microarray data. First, we propose a Bayesian model for microarray data and use Bayes Factors to identify differentially expressed genes. Second, we…

  14. Contributions to Statistical Problems Related to Microarray Data

    ERIC Educational Resources Information Center

    Hong, Feng

    2009-01-01

    Microarray is a high throughput technology to measure the gene expression. Analysis of microarray data brings many interesting and challenging problems. This thesis consists three studies related to microarray data. First, we propose a Bayesian model for microarray data and use Bayes Factors to identify differentially expressed genes. Second, we…

  15. High-Throughput Variation Detection and Genotyping Using Microarrays

    PubMed Central

    Cutler, David J.; Zwick, Michael E.; Carrasquillo, Minerva M.; Yohn, Christopher T.; Tobin, Katherine P.; Kashuk, Carl; Mathews, Debra J.; Shah, Nila A.; Eichler, Evan E.; Warrington, Janet A.; Chakravarti, Aravinda

    2001-01-01

    The genetic dissection of complex traits may ultimately require a large number of SNPs to be genotyped in multiple individuals who exhibit phenotypic variation in a trait of interest. Microarray technology can enable rapid genotyping of variation specific to study samples. To facilitate their use, we have developed an automated statistical method (ABACUS) to analyze microarray hybridization data and applied this method to Affymetrix Variation Detection Arrays (VDAs). ABACUS provides a quality score to individual genotypes, allowing investigators to focus their attention on sites that give accurate information. We have applied ABACUS to an experiment encompassing 32 autosomal and eight X-linked genomic regions, each consisting of ∼50 kb of unique sequence spanning a 100-kb region, in 40 humans. At sufficiently high-quality scores, we are able to read ∼80% of all sites. To assess the accuracy of SNP detection, 108 of 108 SNPs have been experimentally confirmed; an additional 371 SNPs have been confirmed electronically. To access the accuracy of diploid genotypes at segregating autosomal sites, we confirmed 1515 of 1515 homozygous calls, and 420 of 423 (99.29%) heterozygotes. In replicate experiments, consisting of independent amplification of identical samples followed by hybridization to distinct microarrays of the same design, genotyping is highly repeatable. In an autosomal replicate experiment, 813,295 of 813,295 genotypes are called identically (including 351 heterozygotes); at an X-linked locus in males (haploid), 841,236 of 841,236 sites are called identically. PMID:11691856

  16. A Versatile Microarray Platform for Capturing Rare Cells

    PubMed Central

    Brinkmann, Falko; Hirtz, Michael; Haller, Anna; Gorges, Tobias M.; Vellekoop, Michael J.; Riethdorf, Sabine; Müller, Volkmar; Pantel, Klaus; Fuchs, Harald

    2015-01-01

    Analyses of rare events occurring at extremely low frequencies in body fluids are still challenging. We established a versatile microarray-based platform able to capture single target cells from large background populations. As use case we chose the challenging application of detecting circulating tumor cells (CTCs) – about one cell in a billion normal blood cells. After incubation with an antibody cocktail, targeted cells are extracted on a microarray in a microfluidic chip. The accessibility of our platform allows for subsequent recovery of targets for further analysis. The microarray facilitates exclusion of false positive capture events by co-localization allowing for detection without fluorescent labelling. Analyzing blood samples from cancer patients with our platform reached and partly outreached gold standard performance, demonstrating feasibility for clinical application. Clinical researchers free choice of antibody cocktail without need for altered chip manufacturing or incubation protocol, allows virtual arbitrary targeting of capture species and therefore wide spread applications in biomedical sciences. PMID:26493176

  17. Fecal source tracking in water using a mitochondrial DNA microarray.

    PubMed

    Vuong, Nguyet-Minh; Villemur, Richard; Payment, Pierre; Brousseau, Roland; Topp, Edward; Masson, Luke

    2013-01-01

    A mitochondrial-based microarray (mitoArray) was developed for rapid identification of the presence of 28 animals and one family (cervidae) potentially implicated in fecal pollution in mixed activity watersheds. Oligonucleotide probes for genus or subfamily-level identification were targeted within the 12S rRNA - Val tRNA - 16S rRNA region in the mitochondrial genome. This region, called MI-50, was selected based on three criteria: 1) the ability to be amplified by universal primers 2) these universal primer sequences are present in most commercial and domestic animals of interest in source tracking, and 3) that sufficient sequence variation exists within this region to meet the minimal requirements for microarray probe discrimination. To quantify the overall level of mitochondrial DNA (mtDNA) in samples, a quantitative-PCR (Q-PCR) universal primer pair was also developed. Probe validation was performed using DNA extracted from animal tissues and, for many cases, animal-specific fecal samples. To reduce the amplification of potentially interfering fish mtDNA sequences during the MI-50 enrichment step, a clamping PCR method was designed using a fish-specific peptide nucleic acid. DNA extracted from 19 water samples were subjected to both array and independent PCR analyses. Our results confirm that the mitochondrial microarray approach method could accurately detect the dominant animals present in water samples emphasizing the potential for this methodology in the parallel scanning of a large variety of animals normally monitored in fecal source tracking.

  18. A Java-based tool for the design of classification microarrays

    PubMed Central

    Meng, Da; Broschat, Shira L; Call, Douglas R

    2008-01-01

    discriminant analysis can be stored for analysis of subsequent experimental data. Additionally, PLASMID can be used to construct virtual microarrays with genomes from public databases, which can then be used to identify an optimal set of probes. PMID:18680597

  19. Photopatterning of Hydrogel Microarrays in Closed Microchips.

    PubMed

    Gumuscu, Burcu; Bomer, Johan G; van den Berg, Albert; Eijkel, Jan C T

    2015-12-14

    To date, optical lithography has been extensively used for in situ patterning of hydrogel structures in a scale range from hundreds of microns to a few millimeters. The two main limitations which prevent smaller feature sizes of hydrogel structures are (1) the upper glass layer of a microchip maintains a large spacing (typically 525 μm) between the photomask and hydrogel precursor, leading to diffraction of UV light at the edges of mask patterns, (2) diffusion of free radicals and monomers results in irregular polymerization near the illumination interface. In this work, we present a simple approach to enable the use of optical lithography to fabricate hydrogel arrays with a minimum feature size of 4 μm inside closed microchips. To achieve this, we combined two different techniques. First, the upper glass layer of the microchip was thinned by mechanical polishing to reduce the spacing between the photomask and hydrogel precursor, and thereby the diffraction of UV light at the edges of mask patterns. The polishing process reduces the upper layer thickness from ∼525 to ∼100 μm, and the mean surface roughness from 20 to 3 nm. Second, we developed an intermittent illumination technique consisting of short illumination periods followed by relatively longer dark periods, which decrease the diffusion of monomers. Combination of these two methods allows for fabrication of 0.4 × 10(6) sub-10 μm sized hydrogel patterns over large areas (cm(2)) with high reproducibility (∼98.5% patterning success). The patterning method is tested with two different types of photopolymerizing hydrogels: polyacrylamide and polyethylene glycol diacrylate. This method enables in situ fabrication of well-defined hydrogel patterns and presents a simple approach to fabricate 3-D hydrogel matrices for biomolecule separation, biosensing, tissue engineering, and immobilized protein microarray applications.

  20. Development of a 37K high-density oligo-nucleotide microarray for rainbow trout

    USDA-ARS?s Scientific Manuscript database

    We have constructed a rainbow trout high-density oligonucleotide microarray by using all the available tentative consensus (TC) sequences from the Rainbow Trout Gene Index database (The Computational Biology and Functional Genomics Lab., Dana Farber Cancer Institute and Harvard School of Public Heal...

  1. Alignment of gene expression profiles from test samples against a reference database: New method for context-specific interpretation of microarray data

    PubMed Central

    2011-01-01

    Background Gene expression microarray data have been organized and made available as public databases, but the utilization of such highly heterogeneous reference datasets in the interpretation of data from individual test samples is not as developed as e.g. in the field of nucleotide sequence comparisons. We have created a rapid and powerful approach for the alignment of microarray gene expression profiles (AGEP) from test samples with those contained in a large annotated public reference database and demonstrate here how this can facilitate interpretation of microarray data from individual samples. Methods AGEP is based on the calculation of kernel density distributions for the levels of expression of each gene in each reference tissue type and provides a quantitation of the similarity between the test sample and the reference tissue types as well as the identity of the typical and atypical genes in each comparison. As a reference database, we used 1654 samples from 44 normal tissues (extracted from the Genesapiens database). Results Using leave-one-out validation, AGEP correctly defined the tissue of origin for 1521 (93.6%) of all the 1654 samples in the original database. Independent validation of 195 external normal tissue samples resulted in 87% accuracy for the exact tissue type and 97% accuracy with related tissue types. AGEP analysis of 10 Duchenne muscular dystrophy (DMD) samples provided quantitative description of the key pathogenetic events, such as the extent of inflammation, in individual samples and pinpointed tissue-specific genes whose expression changed (SAMD4A) in DMD. AGEP analysis of microarray data from adipocytic differentiation of mesenchymal stem cells and from normal myeloid cell types and leukemias provided quantitative characterization of the transcriptomic changes during normal and abnormal cell differentiation. Conclusions The AGEP method is a widely applicable method for the rapid comprehensive interpretation of microarray data, as

  2. Chromosomal Microarray versus Karyotyping for Prenatal Diagnosis

    PubMed Central

    Wapner, Ronald J.; Martin, Christa Lese; Levy, Brynn; Ballif, Blake C.; Eng, Christine M.; Zachary, Julia M.; Savage, Melissa; Platt, Lawrence D.; Saltzman, Daniel; Grobman, William A.; Klugman, Susan; Scholl, Thomas; Simpson, Joe Leigh; McCall, Kimberly; Aggarwal, Vimla S.; Bunke, Brian; Nahum, Odelia; Patel, Ankita; Lamb, Allen N.; Thom, Elizabeth A.; Beaudet, Arthur L.; Ledbetter, David H.; Shaffer, Lisa G.; Jackson, Laird

    2013-01-01

    Background Chromosomal microarray analysis has emerged as a primary diagnostic tool for the evaluation of developmental delay and structural malformations in children. We aimed to evaluate the accuracy, efficacy, and incremental yield of chromosomal microarray analysis as compared with karyotyping for routine prenatal diagnosis. Methods Samples from women undergoing prenatal diagnosis at 29 centers were sent to a central karyotyping laboratory. Each sample was split in two; standard karyotyping was performed on one portion and the other was sent to one of four laboratories for chromosomal microarray. Results We enrolled a total of 4406 women. Indications for prenatal diagnosis were advanced maternal age (46.6%), abnormal result on Down’s syndrome screening (18.8%), structural anomalies on ultrasonography (25.2%), and other indications (9.4%). In 4340 (98.8%) of the fetal samples, microarray analysis was successful; 87.9% of samples could be used without tissue culture. Microarray analysis of the 4282 nonmosaic samples identified all the aneuploidies and unbalanced rearrangements identified on karyotyping but did not identify balanced translocations and fetal triploidy. In samples with a normal karyotype, microarray analysis revealed clinically relevant deletions or duplications in 6.0% with a structural anomaly and in 1.7% of those whose indications were advanced maternal age or positive screening results. Conclusions In the context of prenatal diagnostic testing, chromosomal microarray analysis identified additional, clinically significant cytogenetic information as compared with karyotyping and was equally efficacious in identifying aneuploidies and unbalanced rearrangements but did not identify balanced translocations and triploidies. (Funded by the Eunice Kennedy Shriver National Institute of Child Health and Human Development and others; ClinicalTrials.gov number, NCT01279733.) PMID:23215555

  3. Chromosomal microarray versus karyotyping for prenatal diagnosis.

    PubMed

    Wapner, Ronald J; Martin, Christa Lese; Levy, Brynn; Ballif, Blake C; Eng, Christine M; Zachary, Julia M; Savage, Melissa; Platt, Lawrence D; Saltzman, Daniel; Grobman, William A; Klugman, Susan; Scholl, Thomas; Simpson, Joe Leigh; McCall, Kimberly; Aggarwal, Vimla S; Bunke, Brian; Nahum, Odelia; Patel, Ankita; Lamb, Allen N; Thom, Elizabeth A; Beaudet, Arthur L; Ledbetter, David H; Shaffer, Lisa G; Jackson, Laird

    2012-12-06

    Chromosomal microarray analysis has emerged as a primary diagnostic tool for the evaluation of developmental delay and structural malformations in children. We aimed to evaluate the accuracy, efficacy, and incremental yield of chromosomal microarray analysis as compared with karyotyping for routine prenatal diagnosis. Samples from women undergoing prenatal diagnosis at 29 centers were sent to a central karyotyping laboratory. Each sample was split in two; standard karyotyping was performed on one portion and the other was sent to one of four laboratories for chromosomal microarray. We enrolled a total of 4406 women. Indications for prenatal diagnosis were advanced maternal age (46.6%), abnormal result on Down's syndrome screening (18.8%), structural anomalies on ultrasonography (25.2%), and other indications (9.4%). In 4340 (98.8%) of the fetal samples, microarray analysis was successful; 87.9% of samples could be used without tissue culture. Microarray analysis of the 4282 nonmosaic samples identified all the aneuploidies and unbalanced rearrangements identified on karyotyping but did not identify balanced translocations and fetal triploidy. In samples with a normal karyotype, microarray analysis revealed clinically relevant deletions or duplications in 6.0% with a structural anomaly and in 1.7% of those whose indications were advanced maternal age or positive screening results. In the context of prenatal diagnostic testing, chromosomal microarray analysis identified additional, clinically significant cytogenetic information as compared with karyotyping and was equally efficacious in identifying aneuploidies and unbalanced rearrangements but did not identify balanced translocations and triploidies. (Funded by the Eunice Kennedy Shriver National Institute of Child Health and Human Development and others; ClinicalTrials.gov number, NCT01279733.).

  4. GeneXplorer: an interactive web application for microarray data visualization and analysis.

    PubMed

    Rees, Christian A; Demeter, Janos; Matese, John C; Botstein, David; Sherlock, Gavin

    2004-10-01

    When publishing large-scale microarray datasets, it is of great value to create supplemental websites where either the full data, or selected subsets corresponding to figures within the paper, can be browsed. We set out to create a CGI application containing many of the features of some of the existing standalone software for the visualization of clustered microarray data. We present GeneXplorer, a web application for interactive microarray data visualization and analysis in a web environment. GeneXplorer allows users to browse a microarray dataset in an intuitive fashion. It provides simple access to microarray data over the Internet and uses only HTML and JavaScript to display graphic and annotation information. It provides radar and zoom views of the data, allows display of the nearest neighbors to a gene expression vector based on their Pearson correlations and provides the ability to search gene annotation fields. The software is released under the permissive MIT Open Source license, and the complete documentation and the entire source code are freely available for download from CPAN http://search.cpan.org/dist/Microarray-GeneXplorer/.

  5. Use of a bacterial antimicrobial resistance gene microarray for the identification of resistant Staphylococcus aureus.

    PubMed

    Garneau, P; Labrecque, O; Maynard, C; Messier, S; Masson, L; Archambault, M; Harel, J

    2010-11-01

    As diagnostic and surveillance activities are vital to determine measures needed to control antimicrobial resistance (AMR), new and rapid laboratory methods are necessary to facilitate this important effort. DNA microarray technology allows the detection of a large number of genes in a single reaction. This technology is simple, specific and high-throughput. We have developed a bacterial antimicrobial resistance gene DNA microarray that will allow rapid antimicrobial resistance gene screening for all Gram-positive and Gram-negative bacteria. A prototype microarray was designed using a 70-mer based oligonucleotide set targeting AMR genes of Gram-negative and Gram-positive bacteria. In the present version, the microarray consists of 182 oligonucleotides corresponding to 166 different acquired AMR gene targets, covering most of the resistance genes found in both Gram-negative and -positive bacteria. A test study was performed on a collection of Staphylococcus aureus isolates from milk samples from dairy farms in Québec, Canada. The reproducibility of the hybridizations was determined, and the microarray results were compared with those obtained by phenotypic resistance tests (either MIC or Kirby-Bauer). The microarray genotyping demonstrated a correlation between penicillin, tetracycline and erythromycin resistance phenotypes with the corresponding acquired resistance genes. The hybridizations showed that the 38 antimicrobial resistant S. aureus isolates possessed at least one AMR gene. © 2010 Blackwell Verlag GmbH.

  6. Development of a DNA-based microarray for the detection of zoonotic pathogens in rodent species.

    PubMed

    Giles, Timothy; Yon, Lisa; Hannant, Duncan; Barrow, Paul; Abu-Median, Abu-Bakr

    2015-12-01

    The demand for diagnostic tools that allow simultaneous screening of samples for multiple pathogens is increasing because they overcome the limitations of other methods, which can only screen for a single or a few pathogens at a time. Microarrays offer the advantages of being capable to test a large number of samples simultaneously, screening for multiple pathogen types per sample and having comparable sensitivity to existing methods such as PCR. Array design is often considered the most important process in any microarray experiment and can be the deciding factor in the success of a study. There are currently no microarrays for simultaneous detection of rodent-borne pathogens. The aim of this report is to explicate the design, development and evaluation of a microarray platform for use as a screening tool that combines ease of use and rapid identification of a number of rodent-borne pathogens of zoonotic importance. Nucleic acid was amplified by multiplex biotinylation PCR prior to hybridisation onto microarrays. The array sensitivity was comparable to standard PCR, though less sensitive than real-time PCR. The array presented here is a prototype microarray identification system for zoonotic pathogens that can infect rodent species.

  7. Development and Validation of Protein Microarray Technology for Simultaneous Inflammatory Mediator Detection in Human Sera

    PubMed Central

    Negm, Ola H.; Hamed, Mohamed R.; Tubby, Carolyn; Todd, Ian; Tighe, Patrick J.; Harrison, Tim; Fairclough, Lucy C.

    2014-01-01

    Biomarkers, including cytokines, can help in the diagnosis, prognosis, and prediction of treatment response across a wide range of disease settings. Consequently, the recent emergence of protein microarray technology, which is able to quantify a range of inflammatory mediators in a large number of samples simultaneously, has become highly desirable. However, the cost of commercial systems remains somewhat prohibitive. Here we show the development, validation, and implementation of an in-house microarray platform which enables the simultaneous quantitative analysis of multiple protein biomarkers. The accuracy and precision of the in-house microarray system were investigated according to the Food and Drug Administration (FDA) guidelines for pharmacokinetic assay validation. The assay fell within these limits for all but the very low-abundant cytokines, such as interleukin- (IL-) 10. Additionally, there were no significant differences between cytokine detection using our microarray system and the “gold standard” ELISA format. Crucially, future biomarker detection need not be limited to the 16 cytokines shown here but could be expanded as required. In conclusion, we detail a bespoke protein microarray system, utilizing well-validated ELISA reagents, that allows accurate, precise, and reproducible multiplexed biomarker quantification, comparable with commercial ELISA, and allowing customization beyond that of similar commercial microarrays. PMID:25382942

  8. Development and validation of protein microarray technology for simultaneous inflammatory mediator detection in human sera.

    PubMed

    Selvarajah, Senthooran; Negm, Ola H; Hamed, Mohamed R; Tubby, Carolyn; Todd, Ian; Tighe, Patrick J; Harrison, Tim; Fairclough, Lucy C

    2014-01-01

    Biomarkers, including cytokines, can help in the diagnosis, prognosis, and prediction of treatment response across a wide range of disease settings. Consequently, the recent emergence of protein microarray technology, which is able to quantify a range of inflammatory mediators in a large number of samples simultaneously, has become highly desirable. However, the cost of commercial systems remains somewhat prohibitive. Here we show the development, validation, and implementation of an in-house microarray platform which enables the simultaneous quantitative analysis of multiple protein biomarkers. The accuracy and precision of the in-house microarray system were investigated according to the Food and Drug Administration (FDA) guidelines for pharmacokinetic assay validation. The assay fell within these limits for all but the very low-abundant cytokines, such as interleukin- (IL-) 10. Additionally, there were no significant differences between cytokine detection using our microarray system and the "gold standard" ELISA format. Crucially, future biomarker detection need not be limited to the 16 cytokines shown here but could be expanded as required. In conclusion, we detail a bespoke protein microarray system, utilizing well-validated ELISA reagents, that allows accurate, precise, and reproducible multiplexed biomarker quantification, comparable with commercial ELISA, and allowing customization beyond that of similar commercial microarrays.

  9. A Comparative Study of the Career Development Patterns of Male and Female Library Administrators in Large Public Libraries.

    ERIC Educational Resources Information Center

    Greiner, Joy M.

    1985-01-01

    This nationwide study, conducted to investigate extent to which sex of individual is controlling factor relating to salaries, career progression, and library support, compared the careers of male and female public library directors serving populations of 100,000 or more in continental United States. Questionnaire is appended. (21 references) (EJS)

  10. The Pursuit of Excellence: An Analysis of the Honors College Application and Enrollment Decision for a Large Public University

    ERIC Educational Resources Information Center

    Singell, Larry D., Jr.; Tang, Hui-Hsuan

    2012-01-01

    Honors colleges housed in public universities began only in the last half century, but have become nearly ubiquitous over the last 20 years. This paper, using recent data from the oldest stand-alone honors college in the country, is the first to study how the application and enrollment decisions of honors college students differ from the general…

  11. Knowledgeability of Copyright Law among Librarians and Library Paraprofessionals Employed in Adult Services at a Large Public Library System.

    ERIC Educational Resources Information Center

    Lavelle, Bridget M.

    Since public libraries contain copyrighted works in the form of print, electronic or audiovisual sources, librarians and library paraprofessionals need to possess sufficient knowledge of United States copyright law to meet the information needs of patrons successfully and legally. A literature review revealed that minimal works address this topic.…

  12. Development, Characterization and Experimental Validation of a Cultivated Sunflower (Helianthus annuus L.) Gene Expression Oligonucleotide Microarray

    PubMed Central

    Fernandez, Paula; Soria, Marcelo; Blesa, David; DiRienzo, Julio; Moschen, Sebastian; Rivarola, Maximo; Clavijo, Bernardo Jose; Gonzalez, Sergio; Peluffo, Lucila; Príncipi, Dario; Dosio, Guillermo; Aguirrezabal, Luis; García-García, Francisco; Conesa, Ana; Hopp, Esteban; Dopazo, Joaquín; Heinz, Ruth Amelia; Paniego, Norma

    2012-01-01

    Oligonucleotide-based microarrays with accurate gene coverage represent a key strategy for transcriptional studies in orphan species such as sunflower, H. annuus L., which lacks full genome sequences. The goal of this study was the development and functional annotation of a comprehensive sunflower unigene collection and the design and validation of a custom sunflower oligonucleotide-based microarray. A large scale EST (>130,000 ESTs) curation, assembly and sequence annotation was performed using Blast2GO (www.blast2go.de). The EST assembly comprises 41,013 putative transcripts (12,924 contigs and 28,089 singletons). The resulting Sunflower Unigen Resource (SUR version 1.0) was used to design an oligonucleotide-based Agilent microarray for cultivated sunflower. This microarray includes a total of 42,326 features: 1,417 Agilent controls, 74 control probes for sunflower replicated 10 times (740 controls) and 40,169 different non-control probes. Microarray performance was validated using a model experiment examining the induction of senescence by water deficit. Pre-processing and differential expression analysis of Agilent microarrays was performed using the Bioconductor limma package. The analyses based on p-values calculated by eBayes (p<0.01) allowed the detection of 558 differentially expressed genes between water stress and control conditions; from these, ten genes were further validated by qPCR. Over-represented ontologies were identified using FatiScan in the Babelomics suite. This work generated a curated and trustable sunflower unigene collection, and a custom, validated sunflower oligonucleotide-based microarray using Agilent technology. Both the curated unigene collection and the validated oligonucleotide microarray provide key resources for sunflower genome analysis, transcriptional studies, and molecular breeding for crop improvement. PMID:23110046

  13. Development, characterization and experimental validation of a cultivated sunflower (Helianthus annuus L.) gene expression oligonucleotide microarray.

    PubMed

    Fernandez, Paula; Soria, Marcelo; Blesa, David; DiRienzo, Julio; Moschen, Sebastian; Rivarola, Maximo; Clavijo, Bernardo Jose; Gonzalez, Sergio; Peluffo, Lucila; Príncipi, Dario; Dosio, Guillermo; Aguirrezabal, Luis; García-García, Francisco; Conesa, Ana; Hopp, Esteban; Dopazo, Joaquín; Heinz, Ruth Amelia; Paniego, Norma

    2012-01-01

    Oligonucleotide-based microarrays with accurate gene coverage represent a key strategy for transcriptional studies in orphan species such as sunflower, H. annuus L., which lacks full genome sequences. The goal of this study was the development and functional annotation of a comprehensive sunflower unigene collection and the design and validation of a custom sunflower oligonucleotide-based microarray. A large scale EST (>130,000 ESTs) curation, assembly and sequence annotation was performed using Blast2GO (www.blast2go.de). The EST assembly comprises 41,013 putative transcripts (12,924 contigs and 28,089 singletons). The resulting Sunflower Unigen Resource (SUR version 1.0) was used to design an oligonucleotide-based Agilent microarray for cultivated sunflower. This microarray includes a total of 42,326 features: 1,417 Agilent controls, 74 control probes for sunflower replicated 10 times (740 controls) and 40,169 different non-control probes. Microarray performance was validated using a model experiment examining the induction of senescence by water deficit. Pre-processing and differential expression analysis of Agilent microarrays was performed using the Bioconductor limma package. The analyses based on p-values calculated by eBayes (p<0.01) allowed the detection of 558 differentially expressed genes between water stress and control conditions; from these, ten genes were further validated by qPCR. Over-represented ontologies were identified using FatiScan in the Babelomics suite. This work generated a curated and trustable sunflower unigene collection, and a custom, validated sunflower oligonucleotide-based microarray using Agilent technology. Both the curated unigene collection and the validated oligonucleotide microarray provide key resources for sunflower genome analysis, transcriptional studies, and molecular breeding for crop improvement.

  14. Goober: a fully integrated and user-friendly microarray data management and analysis solution for core labs and bench biologists.

    PubMed

    Luo, Wen; Gudipati, Murali; Jung, Kevin; Chen, Mao; Marschke, Keith B

    2009-08-23

    Despite the large number of software tools developed to address different areas of microarray data analysis, very few offer an all-in-one solution with little learning curve. For microarray core labs, there are even fewer software packages available to help with their routine but critical tasks, such as data quality control (QC) and inventory management. We have developed a simple-to-use web portal to allow bench biologists to analyze and query complicated microarray data and related biological pathways without prior training. Both experiment-based and gene-based analysis can be easily performed, even for the first-time user, through the intuitive multi-layer design and interactive graphic links. While being friendly to inexperienced users, most parameters in Goober can be easily adjusted via drop-down menus to allow advanced users to tailor their needs and perform more complicated analysis. Moreover, we have integrated graphic pathway analysis into the website to help users examine microarray data within the relevant biological content. Goober also contains features that cover most of the common tasks in microarray core labs, such as real time array QC, data loading, array usage and inventory tracking. Overall, Goober is a complete microarray solution to help biologists instantly discover valuable information from a microarray experiment and enhance the quality and productivity of microarray core labs. The whole package is freely available at http://sourceforge.net/projects/goober. A demo web server is available at http://www.goober-array.org.

  15. Sex-dependent liver gene expression is extensive and largely dependent upon signal transducer and activator of transcription 5b (STAT5b): STAT5b-dependent activation of male genes and repression of female genes revealed by microarray analysis.

    PubMed

    Clodfelter, Karl H; Holloway, Minita G; Hodor, Paul; Park, Soo-Hee; Ray, William J; Waxman, David J

    2006-06-01

    Sexual dimorphism in mammalian liver contributes to sex differences in physiology, homeostasis, and steroid and foreign compound metabolism. Many sex-dependent liver genes are regulated by sex differences in pituitary GH secretion, with the transcription factor, signal transducer and activator of transcription (STAT5b), proposed to mediate signaling by the pulsatile, male plasma GH profile. Presently, a large-scale gene expression study was conducted using male and female mice, wild type and Stat5b inactivated, to characterize sex differences in liver gene expression and their dependence on STAT5b. The relative abundance of individual liver RNAs was determined for each sex-genotype combination by competitive hybridization to 23,574-feature oligonucleotide microarrays. Significant sex differences in hepatic expression were seen for 1603 mouse genes. Of 850 genes showing higher expression in males, 767 (90%) were down-regulated in STAT5b-deficient males. Moreover, of 753 genes showing female-predominant expression, 461 (61%) were up-regulated in STAT5b-deficient males. In contrast, approximately 90% of the sex-dependent genes were unaffected by STAT5b deficiency in females. Thus: 1) STAT5b is essential for sex-dependent liver gene expression, a characteristic of approximately 1600 mouse genes (4% of the genome); 2) male-predominant liver gene expression requires STAT5b, or STAT5b-dependent factors, which act in a positive manner; and 3) many female-predominant liver genes are repressed in males in a STAT5b-dependent manner. Several of the STAT5b-dependent male genes encode transcriptional repressors; these may include direct STAT5b targets that repress female-predominant genes in male liver. Several female-predominant repressors are elevated in STAT5b-deficient males; these may contribute to the major loss of male gene expression seen in the absence of STAT5b.

  16. Validation of affinity reagents using antigen microarrays.

    PubMed

    Sjöberg, Ronald; Sundberg, Mårten; Gundberg, Anna; Sivertsson, Asa; Schwenk, Jochen M; Uhlén, Mathias; Nilsson, Peter

    2012-06-15

    There is a need for standardised validation of affinity reagents to determine their binding selectivity and specificity. This is of particular importance for systematic efforts that aim to cover the human proteome with different types of binding reagents. One such international program is the SH2-consortium, which was formed to generate a complete set of renewable affinity reagents to the SH2-domain containing human proteins. Here, we describe a microarray strategy to validate various affinity reagents, such as recombinant single-chain antibodies, mouse monoclonal antibodies and antigen-purified polyclonal antibodies using a highly multiplexed approach. An SH2-specific antigen microarray was designed and generated, containing more than 6000 spots displayed by 14 identical subarrays each with 406 antigens, where 105 of them represented SH2-domain containing proteins. Approximately 400 different affinity reagents of various types were analysed on these antigen microarrays carrying antigens of different types. The microarrays revealed not only very detailed specificity profiles for all the binders, but also showed that overlapping target sequences of spotted antigens were detected by off-target interactions. The presented study illustrates the feasibility of using antigen microarrays for integrative, high-throughput validation of various types of binders and antigens.

  17. Oligonucleotide microarrays for identification of microbial pathogens and detection of their virulence-associated or drug-resistance determinants.

    PubMed

    Volokhov, Dmitriy V; Kong, Hyesuk; Herold, Keith; Chizhikov, Vladimir E; Rasooly, Avraham

    2011-01-01

    Microarrays are spatially ordered arrays with ligands chemically immobilized in discrete spots on a solid matrix, usually a microscope slide. Microarrays are a high-throughput large-scale screening system enabling simultaneous identification of a large number of labeled target molecules (up to several hundred thousand) that bind specifically to the immobilized ligands of the array. DNA microarrays represent a promising tool for clinical, environmental, and industrial microbiology since the technology allows relatively rapid identification of large number of genetic determinants simultaneously, providing detailed genomic level information regarding the pathogen species, including identification of their virulence-associated factors and the presence of antibiotic resistance genes. In this chapter, we describe key aspects and methodologies important for the development and use of DNA microarrays for microbial diagnostics.

  18. hemaClass.org: Online One-By-One Microarray Normalization and Classification of Hematological Cancers for Precision Medicine

    PubMed Central

    Falgreen, Steffen; Ellern Bilgrau, Anders; Brøndum, Rasmus Froberg; Hjort Jakobsen, Lasse; Have, Jonas; Lindblad Nielsen, Kasper; El-Galaly, Tarec Christoffer; Bødker, Julie Støve; Schmitz, Alexander; H. Young, Ken; Johnsen, Hans Erik; Dybkær, Karen; Bøgsted, Martin

    2016-01-01

    Background Dozens of omics based cancer classification systems have been introduced with prognostic, diagnostic, and predictive capabilities. However, they often employ complex algorithms and are only applicable on whole cohorts of patients, making them difficult to apply in a personalized clinical setting. Results This prompted us to create hemaClass.org, an online web application providing an easy interface to one-by-one RMA normalization of microarrays and subsequent risk classifications of diffuse large B-cell lymphoma (DLBCL) into cell-of-origin and chemotherapeutic sensitivity classes. Classification results for one-by-one array pre-processing with and without a laboratory specific RMA reference dataset were compared to cohort based classifiers in 4 publicly available datasets. Classifications showed high agreement between one-by-one and whole cohort pre-processsed data when a laboratory specific reference set was supplied. The website is essentially the R-package hemaClass accompanied by a Shiny web application. The well-documented package can be used to run the website locally or to use the developed methods programmatically. Conclusions The website and R-package is relevant for biological and clinical lymphoma researchers using affymetrix U-133 Plus 2 arrays, as it provides reliable and swift methods for calculation of disease subclasses. The proposed one-by-one pre-processing method is relevant for all researchers using microarrays. PMID:27701436

  19. Recent discoveries and applications involving small-molecule microarrays.

    PubMed

    Hong, Jiyoung A; Neel, Dylan V; Wassaf, Dina; Caballero, Francisco; Koehler, Angela N

    2014-02-01

    High-throughput and unbiased binding assays have proven useful in probe discovery for a myriad of biomolecules, including targets of unknown structure or function and historically challenging target classes. Over the past decade, a number of novel formats for executing large-scale binding assays have been developed and used successfully in probe discovery campaigns. Here we review the use of one such format, the small-molecule microarray (SMM), as a tool for discovering protein-small molecule interactions. This review will briefly highlight selected recent probe discoveries using SMMs as well as novel uses of SMMs in profiling applications. Copyright © 2013 Elsevier Ltd. All rights reserved.

  20. CIIPro: a new read-across portal to fill data gaps using public large-scale chemical and biological data.

    PubMed

    Russo, Daniel P; Kim, Marlene T; Wang, Wenyi; Pinolini, Daniel; Shende, Sunil; Strickland, Judy; Hartung, Thomas; Zhu, Hao

    2016-10-14

    We have developed a public Chemical In vitro-In vivo Profiling (CIIPro) portal, which can automatically extract in vitro biological data from public resources (i.e. PubChem) for user-supplied compounds. For compounds with in vivo target activity data (e.g. animal toxicity testing results), the integrated cheminformatics algorithm will optimize the extracted biological data using in vitro-in vivo correlations. The resulting in vitro biological data for target compounds can be used for read-across risk assessment of target compounds. Additionally, the CIIPro portal can identify the most similar compounds based on their optimized bioprofiles. The CIIPro portal provides new powerful assessment capabilities to the scientific community and can be easily integrated with other cheminformatics tools.

  1. Characterizing dye bias in microarray experiments.

    PubMed

    Dobbin, K K; Kawasaki, E S; Petersen, D W; Simon, R M

    2005-05-15

    Spot intensity serves as a proxy for gene expression in dual-label microarray experiments. Dye bias is defined as an intensity difference between samples labeled with different dyes attributable to the dyes instead of the gene expression in the samples. Dye bias that is not removed by array normalization can introduce bias into comparisons between samples of interest. But if the bias is consistent across samples for the same gene, it can be corrected by proper experimental design and analysis. If the dye bias is not consistent across samples for the same gene, but is different for different samples, then removing the bias becomes more problematic, perhaps indicating a technical limitation to the ability of fluorescent signals to accurately represent gene expression. Thus, it is important to characterize dye bias to determine: (1) whether it will be removed for all genes by array normalization, (2) whether it will not be removed by normalization but can be removed by proper experimental design and analysis and (3) whether dye bias correction is more problematic than either of these and is not easily removable. We analyzed two large (each >27 arrays) tissue culture experiments with extensive dye swap arrays to better characterize dye bias. Indirect, amino-allyl labeling was used in both experiments. We found that post-normalization dye bias that is consistent across samples does appear to exist for many genes, and that controlling and correcting for this type of dye bias in design and analysis is advisable. The extent of this type of dye bias remained unchanged under a wide range of normalization methods (median-centering, various loess normalizations) and statistical analysis techniques (parametric, rank based, permutation based, etc.). We also found dye bias related to the individual samples for a much smaller subset of genes. But these sample-specific dye biases appeared to have minimal impact on estimated gene-expression differences between the cell lines.

  2. Report on the ESO Workshop ''Rainbows on the Southern Sky: Science and Legacy Value of the ESO Public Surveys and Large Programmes''

    NASA Astrophysics Data System (ADS)

    Arnaboldi, M.; Rejkuba, M.; Leibundgut, B.; Beccari, G.

    2015-12-01

    This was the third ESO workshop on the science from Large Programmes and the second on Public Surveys. By design, this workshop covered all areas of research in observational astronomy, providing a forum for the presentation of the most recent scientific results from these programmes and fostering discussions on the planned developments enabled by large and coherent time allocations on ESO telescopes. Several aspects of the legacy value of such programmes —technological, archival content, access to data, time domain and sociological — were evaluated and set a reference for future developments of ESO services to the community.

  3. A large-scale, rapid public health response to rabies in an organ recipient and the previously undiagnosed organ donor.

    PubMed

    Wallace, R M; Stanek, D; Griese, S; Krulak, D; Vora, N M; Pacha, L; Kan, V; Said, M; Williams, C; Burgess, T H; Clausen, S S; Austin, C; Gabel, J; Lehman, M; Finelli, L N; Selvaggi, G; Joyce, P; Gordin, F; Benator, D; Bettano, A; Cersovsky, S; Blackmore, C; Jones, S V; Buchanan, B D; Fernandez, A I; Dinelli, D; Agnes, K; Clark, A; Gill, J; Irmler, M; Blythe, D; Mitchell, K; Whitman, T J; Zapor, M J; Zorich, S; Witkop, C; Jenkins, P; Mora, P; Droller, D; Turner, S; Dunn, L; Williams, P; Richards, C; Ewing, G; Chapman, K; Corbitt, C; Girimont, T; Franka, R; Recuenco, S; Blanton, J D; Feldman, K A

    2014-12-01

    This article describes and contrasts the public health response to two human rabies cases: one organ recipient diagnosed within days of symptom onset and the transplant donor who was diagnosed 18 months post-symptom onset. In response to an organ-transplant-related rabies case diagnosed in 2013, organ donor and recipient investigations were conducted by multiple public health agencies. Persons with potential exposure to infectious patient materials were assessed for rabies virus exposure. An exposure investigation was conducted to determine the source of the organ donor's infection. Over 100 persons from more than 20 agencies spent over 2700 h conducting contact investigations in healthcare, military and community settings. The 564 persons assessed include 417 healthcare workers [5.8% recommended for post-exposure prophylaxis (PEP)], 96 community contacts (15.6% recommended for PEP), 30 autopsy personnel (50% recommended for PEP), and 21 other persons (4.8% recommended for PEP). Donor contacts represented 188 assessed with 20.2% recommended for PEP, compared with 5.6% of 306 recipient contacts recommended for PEP. Human rabies cases result in substantial use of public health and medical resources, especially when diagnosis is delayed. Although rare, clinicians should consider rabies in cases of encephalitis of unexplained aetiology, particularly for cases that may result in organ donation.

  4. EMAAS: An extensible grid-based Rich Internet Application for microarray data analysis and management

    PubMed Central

    Barton, G; Abbott, J; Chiba, N; Huang, DW; Huang, Y; Krznaric, M; Mack-Smith, J; Saleem, A; Sherman, BT; Tiwari, B; Tomlinson, C; Aitman, T; Darlington, J; Game, L; Sternberg, MJE; Butcher, SA

    2008-01-01

    Background Microarray experimentation requires the application of complex analysis methods as well as the use of non-trivial computer technologies to manage the resultant large data sets. This, together with the proliferation of tools and techniques for microarray data analysis, makes it very challenging for a laboratory scientist to keep up-to-date with the latest developments in this field. Our aim was to develop a distributed e-support system for microarray data analysis and management. Results EMAAS (Extensible MicroArray Analysis System) is a multi-user rich internet application (RIA) providing simple, robust access to up-to-date resources for microarray data storage and analysis, combined with integrated tools to optimise real time user support and training. The system leverages the power of distributed computing to perform microarray analyses, and provides seamless access to resources located at various remote facilities. The EMAAS framework allows users to import microarray data from several sources to an underlying database, to pre-process, quality assess and analyse the data, to perform functional analyses, and to track data analysis steps, all through a single easy to use web portal. This interface offers distance support to users both in the form of video tutorials and via live screen feeds using the web conferencing tool EVO. A number of analysis packages, including R-Bioconductor and Affymetrix Power Tools have been integrated on the server side and are available programmatically through the Postgres-PLR library or on grid compute clusters. Integrated distributed resources include the functional annotation tool DAVID, GeneCards and the microarray data repositories GEO, CELSIUS and MiMiR. EMAAS currently supports analysis of Affymetrix 3' and Exon expression arrays, and the system is extensible to cater for other microarray and transcriptomic platforms. Conclusion EMAAS enables users to track and perform microarray data management and analysis tasks

  5. Environmental impact assessment and environmental audit in large-scale public infrastructure construction: the case of the Qinghai-Tibet Railway.

    PubMed

    He, Guizhen; Zhang, Lei; Lu, Yonglong

    2009-09-01

    Large-scale public infrastructure projects have featured in China's modernization course since the early 1980s. During the early stages of China's rapid economic development, public attention focused on the economic and social impact of high-profile construction projects. In recent years, however, we have seen a shift in public concern toward the environmental and ecological effects of such projects, and today governments are required to provide valid environmental impact assessments prior to allowing large-scale construction. The official requirement for the monitoring of environmental conditions has led to an increased number of debates in recent years regarding the effectiveness of Environmental Impact Assessments (EIAs) and Governmental Environmental Audits (GEAs) as environmental safeguards in instances of large-scale construction. Although EIA and GEA are conducted by different institutions and have different goals and enforcement potential, these two practices can be closely related in terms of methodology. This article cites the construction of the Qinghai-Tibet Railway as an instance in which EIA and GEA offer complementary approaches to environmental impact management. This study concludes that the GEA approach can serve as an effective follow-up to the EIA and establishes that the EIA lays a base for conducting future GEAs. The relationship that emerges through a study of the Railway's construction calls for more deliberate institutional arrangements and cooperation if the two practices are to be used in concert to optimal effect.

  6. Environmental Impact Assessment and Environmental Audit in Large-Scale Public Infrastructure Construction: The Case of the Qinghai-Tibet Railway

    NASA Astrophysics Data System (ADS)

    He, Guizhen; Zhang, Lei; Lu, Yonglong

    2009-09-01

    Large-scale public infrastructure projects have featured in China’s modernization course since the early 1980s. During the early stages of China’s rapid economic development, public attention focused on the economic and social impact of high-profile construction projects. In recent years, however, we have seen a shift in public concern toward the environmental and ecological effects of such projects, and today governments are required to provide valid environmental impact assessments prior to allowing large-scale construction. The official requirement for the monitoring of environmental conditions has led to an increased number of debates in recent years regarding the effectiveness of Environmental Impact Assessments (EIAs) and Governmental Environmental Audits (GEAs) as environmental safeguards in instances of large-scale construction. Although EIA and GEA are conducted by different institutions and have different goals and enforcement potential, these two practices can be closely related in terms of methodology. This article cites the construction of the Qinghai-Tibet Railway as an instance in which EIA and GEA offer complementary approaches to environmental impact management. This study concludes that the GEA approach can serve as an effective follow-up to the EIA and establishes that the EIA lays a base for conducting future GEAs. The relationship that emerges through a study of the Railway’s construction calls for more deliberate institutional arrangements and cooperation if the two practices are to be used in concert to optimal effect.

  7. Microarray Data Analysis and Mining Tools

    PubMed Central

    Selvaraj, Saravanakumar; Natarajan, Jeyakumar

    2011-01-01

    Microarrays are one of the latest breakthroughs in experimental molecular biology that allow monitoring the expression levels of tens of thousands of genes simultaneously. Arrays have been applied to studies in gene expression, genome mapping, SNP discrimination, transcription factor activity, toxicity, pathogen identification and many other applications. In this paper we concentrate on discussing various bioinformatics tools used for microarray data mining tasks with its underlying algorithms, web resources and relevant reference. We emphasize this paper mainly for digital biologists to get an aware about the plethora of tools and programs available for microarray data analysis. First, we report the common data mining applications such as selecting differentially expressed genes, clustering, and classification. Next, we focused on gene expression based knowledge discovery studies such as transcription factor binding site analysis, pathway analysis, protein- protein interaction network analysis and gene enrichment analysis. PMID:21584183

  8. Microarray data analysis and mining tools.

    PubMed

    Selvaraj, Saravanakumar; Natarajan, Jeyakumar

    2011-04-22

    Microarrays are one of the latest breakthroughs in experimental molecular biology that allow monitoring the expression levels of tens of thousands of genes simultaneously. Arrays have been applied to studies in gene expression, genome mapping, SNP discrimination, transcription factor activity, toxicity, pathogen identification and many other applications. In this paper we concentrate on discussing various bioinformatics tools used for microarray data mining tasks with its underlying algorithms, web resources and relevant reference. We emphasize this paper mainly for digital biologists to get an aware about the plethora of tools and programs available for microarray data analysis. First, we report the common data mining applications such as selecting differentially expressed genes, clustering, and classification. Next, we focused on gene expression based knowledge discovery studies such as transcription factor binding site analysis, pathway analysis, protein- protein interaction network analysis and gene enrichment analysis.

  9. Posttranslational Modification Assays on Functional Protein Microarrays.

    PubMed

    Neiswinger, Johnathan; Uzoma, Ijeoma; Cox, Eric; Rho, HeeSool; Jeong, Jun Seop; Zhu, Heng

    2016-10-03

    Protein microarray technology provides a straightforward yet powerful strategy for identifying substrates of posttranslational modifications (PTMs) and studying the specificity of the enzymes that catalyze these reactions. Protein microarray assays can be designed for individual enzymes or a mixture to establish connections between enzymes and substrates. Assays for four well-known PTMs-phosphorylation, acetylation, ubiquitylation, and SUMOylation-have been developed and are described here for use on functional protein microarrays. Phosphorylation and acetylation require a single enzyme and are easily adapted for use on an array. The ubiquitylation and SUMOylation cascades are very similar, and the combination of the E1, E2, and E3 enzymes plus ubiquitin or SUMO protein and ATP is sufficient for in vitro modification of many substrates.

  10. Designing microarray phantoms for hyperspectral imaging validation

    PubMed Central

    Clarke, Matthew L.; Lee, Ji Youn; Samarov, Daniel V.; Allen, David W.; Litorja, Maritoni; Nossal, Ralph; Hwang, Jeeseong

    2012-01-01

    The design and fabrication of custom-tailored microarrays for use as phantoms in the characterization of hyperspectral imaging systems is described. Corresponding analysis methods for biologically relevant samples are also discussed. An image-based phantom design was used to program a microarrayer robot to print prescribed mixtures of dyes onto microscope slides. The resulting arrays were imaged by a hyperspectral imaging microscope. The shape of the spots results in significant scattering signals, which can be used to test image analysis algorithms. Separation of the scattering signals allowed elucidation of individual dye spectra. In addition, spectral fitting of the absorbance spectra of complex dye mixtures was performed in order to determine local dye concentrations. Such microarray phantoms provide a robust testing platform for comparisons of hyperspectral imaging acquisition and analysis methods. PMID:22741076

  11. MicroGen: a MIAME compliant web system for microarray experiment information and workflow management.

    PubMed

    Burgarella, Sarah; Cattaneo, Dario; Pinciroli, Francesco; Masseroli, Marco

    2005-12-01

    Improvements of bio-nano-technologies and biomolecular techniques have led to increasing production of high-throughput experimental data. Spotted cDNA microarray is one of the most diffuse technologies, used in single research laboratories and in biotechnology service facilities. Although they are routinely performed, spotted microarray experiments are complex procedures entailing several experimental steps and actors with different technical skills and roles. During an experiment, involved actors, who can also be located in a distance, need to access and share specific experiment information according to their roles. Furthermore, complete information describing all experimental steps must be orderly collected to allow subsequent correct interpretation of experimental results. We developed MicroGen, a web system for managing information and workflow in the production pipeline of spotted microarray experiments. It is constituted of a core multi-database system able to store all data completely characterizing different spotted microarray experiments according to the Minimum Information About Microarray Experiments (MIAME) standard, and of an intuitive and user-friendly web interface able to support the collaborative work required among multidisciplinary actors and roles involved in spotted microarray experiment production. MicroGen supports six types of user roles: the researcher who designs and requests the experiment, the spotting operator, the hybridisation operator, the image processing operator, the system administrator, and the generic public user who can access the unrestricted part of the system to get information about MicroGen services. MicroGen represents a MIAME compliant information system that enables managing workflow and supporting collaborative work in spotted microarray experiment production.

  12. MicroGen: a MIAME compliant web system for microarray experiment information and workflow management

    PubMed Central

    Burgarella, Sarah; Cattaneo, Dario; Pinciroli, Francesco; Masseroli, Marco

    2005-01-01

    Background Improvements of bio-nano-technologies and biomolecular techniques have led to increasing production of high-throughput experimental data. Spotted cDNA microarray is one of the most diffuse technologies, used in single research laboratories and in biotechnology service facilities. Although they are routinely performed, spotted microarray experiments are complex procedures entailing several experimental steps and actors with different technical skills and roles. During an experiment, involved actors, who can also be located in a distance, need to access and share specific experiment information according to their roles. Furthermore, complete information describing all experimental steps must be orderly collected to allow subsequent correct interpretation of experimental results. Results We developed MicroGen, a web system for managing information and workflow in the production pipeline of spotted microarray experiments. It is constituted of a core multi-database system able to store all data completely characterizing different spotted microarray experiments according to the Minimum Information About Microarray Experiments (MIAME) standard, and of an intuitive and user-friendly web interface able to support the collaborative work required among multidisciplinary actors and roles involved in spotted microarray experiment production. MicroGen supports six types of user roles: the researcher who designs and requests the experiment, the spotting operator, the hybridisation operator, the image processing operator, the system administrator, and the generic public user who can access the unrestricted part of the system to get information about MicroGen services. Conclusion MicroGen represents a MIAME compliant information system that enables managing workflow and supporting collaborative work in spotted microarray experiment production. PMID:16351755

  13. Microarray analysis of erythromycin resistance determinants.

    PubMed

    Volokhov, D; Chizhikov, V; Chumakov, K; Rasooly, A

    2003-01-01

    To develop a DNA microarray for analysis of genes encoding resistance determinants to erythromycin and the related macrolide, lincosamide and streptogramin B (MLS) compounds. We developed an oligonucleotide microarray containing seven oligonucleotide probes (oligoprobes) for each of the six genes (ermA, ermB, ermC, ereA, ereB and msrA/B) that account for more than 98% of MLS resistance in Staphylococcus aureus clinical isolates. The microarray was used to test reference and clinical S. aureus and Streptococcus pyrogenes strains. Target genes from clinical strains were amplified and fluorescently labelled using multiplex PCR target amplification. The microarray assay correctly identified the MLS resistance genes in the reference strains and clinical isolates of S. aureus, and the results were confirmed by direct DNA sequence analysis. Of 18 S. aureus clinical strains tested, 11 isolates carry MLS determinants. One gene (ermC) was found in all 11 clinical isolates tested, and two others, ermA and msrA/B, were found in five or more isolates. Indeed, eight (72%) of 11 clinical isolate strains contained two or three MLS resistance genes, in one of the three combinations (ermA with ermC, ermC with msrA/B, ermA with ermC and msrA/B). Oligonucleotide microarray can detect and identify the six MLS resistance determinants analysed in this study. Our results suggest that microarray-based detection of microbial antibiotic resistance genes might be a useful tool for identifying antibiotic resistance determinants in a wide range of bacterial strains, given the high homology among microbial MLS resistance genes.

  14. Hybridization and Selective Release of DNA Microarrays

    SciTech Connect

    Beer, N R; Baker, B; Piggott, T; Maberry, S; Hara, C M; DeOtte, J; Benett, W; Mukerjee, E; Dzenitis, J; Wheeler, E K

    2011-11-29

    DNA microarrays contain sequence specific probes arrayed in distinct spots numbering from 10,000 to over 1,000,000, depending on the platform. This tremendous degree of multiplexing gives microarrays great potential for environmental background sampling, broad-spectrum clinical monitoring, and continuous biological threat detection. In practice, their use in these applications is not common due to limited information content, long processing times, and high cost. The work focused on characterizing the phenomena of microarray hybridization and selective release that will allow these limitations to be addressed. This will revolutionize the ways that microarrays can be used for LLNL's Global Security missions. The goals of this project were two-fold: automated faster hybridizations and selective release of hybridized features. The first study area involves hybridization kinetics and mass-transfer effects. the standard hybridization protocol uses an overnight incubation to achieve the best possible signal for any sample type, as well as for convenience in manual processing. There is potential to significantly shorten this time based on better understanding and control of the rate-limiting processes and knowledge of the progress of the hybridization. In the hybridization work, a custom microarray flow cell was used to manipulate the chemical and thermal environment of the array and autonomously image the changes over time during hybridization. The second study area is selective release. Microarrays easily generate hybridization patterns and signatures, but there is still an unmet need for methodologies enabling rapid and selective analysis of these patterns and signatures. Detailed analysis of individual spots by subsequent sequencing could potentially yield significant information for rapidly mutating and emerging (or deliberately engineered) pathogens. In the selective release work, optical energy deposition with coherent light quickly provides the thermal energy to

  15. Microarray Meta-Analysis and Cross-Platform Normalization: Integrative Genomics for Robust Biomarker Discovery

    PubMed Central

    Walsh, Christopher J.; Hu, Pingzhao; Batt, Jane; Dos Santos, Claudia C.

    2015-01-01

    The diagnostic and prognostic potential of the vast quantity of publicly-available microarray data has driven the development of methods for integrating the data from different microarray platforms. Cross-platform integration, when appropriately implemented, has been shown to improve reproducibility and robustness of gene signature biomarkers. Microarray platform integration can be conceptually divided into approaches that perform early stage integration (cross-platform normalization) versus late stage data integration (meta-analysis). A growing number of statistical methods and associated software for platform integration are available to the user, however an understanding of their comparative performance and potential pitfalls is critical for best implementation. In this review we provide evidence-based, practical guidance to researchers performing cross-platform integration, particularly with an objective to discover biomarkers. PMID:27600230

  16. Grouping Gene Ontology terms to improve the assessment of gene set enrichment in microarray data.

    PubMed

    Lewin, Alex; Grieve, Ian C

    2006-10-03

    Gene Ontology (GO) terms are often used to assess the results of microarray experiments. The most common way to do this is to perform Fisher's exact tests to find GO terms which are over-represented amongst the genes declared to be differentially expressed in the analysis of the microarray experiment. However, due to the high degree of dependence between GO terms, statistical testing is conservative, and interpretation is difficult. We propose testing groups of GO terms rather than individual terms, to increase statistical power, reduce dependence between tests and improve the interpretation of results. We use the publicly available package POSOC to group the terms. Our method finds groups of GO terms significantly over-represented amongst differentially expressed genes which are not found by Fisher's tests on individual GO terms. Grouping Gene Ontology terms improves the interpretation of gene set enrichment for microarray data.

  17. Construction of citrus gene coexpression networks from microarray data using random matrix theory.

    PubMed

    Du, Dongliang; Rawat, Nidhi; Deng, Zhanao; Gmitter, Fred G

    2015-01-01

    After the sequencing of citrus genomes, gene function annotation is becoming a new challenge. Gene coexpression analysis can be employed for function annotation using publicly available microarray data sets. In this study, 230 sweet orange (Citrus sinensis) microarrays were used to construct seven coexpression networks, including one condition-independent and six condition-dependent (Citrus canker, Huanglongbing, leaves, flavedo, albedo, and flesh) networks. In total, these networks contain 37 633 edges among 6256 nodes (genes), which accounts for 52.11% measurable genes of the citrus microarray. Then, these networks were partitioned into functional modules using the Markov Cluster Algorithm. Significantly enriched Gene Ontology biological process terms and KEGG pathway terms were detected for 343 and 60 modules, respectively. Finally, independent verification of these networks was performed using another expression data of 371 genes. This study provides new targets for further functional analyses in citrus.

  18. Microarray Meta-Analysis and Cross-Platform Normalization: Integrative Genomics for Robust Biomarker Discovery.

    PubMed

    Walsh, Christopher J; Hu, Pingzhao; Batt, Jane; Santos, Claudia C Dos

    2015-08-21

    The diagnostic and prognostic potential of the vast quantity of publicly-available microarray data has driven the development of methods for integrating the data from different microarray platforms. Cross-platform integration, when appropriately implemented, has been shown to improve reproducibility and robustness of gene signature biomarkers. Microarray platform integration can be conceptually divided into approaches that perform early stage integration (cross-platform normalization) versus late stage data integration (meta-analysis). A growing number of statistical methods and associated software for platform integration are available to the user, however an understanding of their comparative performance and potential pitfalls is critical for best implementation. In this review we provide evidence-based, practical guidance to researchers performing cross-platform integration, particularly with an objective to discover biomarkers.

  19. Construction of citrus gene coexpression networks from microarray data using random matrix theory

    PubMed Central

    Du, Dongliang; Rawat, Nidhi; Deng, Zhanao; Gmitter, Fred G.

    2015-01-01

    After the sequencing of citrus genomes, gene function annotation is becoming a new challenge. Gene coexpression analysis can be employed for function annotation using publicly available microarray data sets. In this study, 230 sweet orange (Citrus sinensis) microarrays were used to construct seven coexpression networks, including one condition-independent and six condition-dependent (Citrus canker, Huanglongbing, leaves, flavedo, albedo, and flesh) networks. In total, these networks contain 37 633 edges among 6256 nodes (genes), which accounts for 52.11% measurable genes of the citrus microarray. Then, these networks were partitioned into functional modules using the Markov Cluster Algorithm. Significantly enriched Gene Ontology biological process terms and KEGG pathway terms were detected for 343 and 60 modules, respectively. Finally, independent verification of these networks was performed using another expression data of 371 genes. This study provides new targets for further functional analyses in citrus. PMID:26504573

  20. The use of microarrays in microbial ecology

    SciTech Connect

    Andersen, G.L.; He, Z.; DeSantis, T.Z.; Brodie, E.L.; Zhou, J.

    2009-09-15

    Microarrays have proven to be a useful and high-throughput method to provide targeted DNA sequence information for up to many thousands of specific genetic regions in a single test. A microarray consists of multiple DNA oligonucleotide probes that, under high stringency conditions, hybridize only to specific complementary nucleic acid sequences (targets). A fluorescent signal indicates the presence and, in many cases, the abundance of genetic regions of interest. In this chapter we will look at how microarrays are used in microbial ecology, especially with the recent increase in microbial community DNA sequence data. Of particular interest to microbial ecologists, phylogenetic microarrays are used for the analysis of phylotypes in a community and functional gene arrays are used for the analysis of functional genes, and, by inference, phylotypes in environmental samples. A phylogenetic microarray that has been developed by the Andersen laboratory, the PhyloChip, will be discussed as an example of a microarray that targets the known diversity within the 16S rRNA gene to determine microbial community composition. Using multiple, confirmatory probes to increase the confidence of detection and a mismatch probe for every perfect match probe to minimize the effect of cross-hybridization by non-target regions, the PhyloChip is able to simultaneously identify any of thousands of taxa present in an environmental sample. The PhyloChip is shown to reveal greater diversity within a community than rRNA gene sequencing due to the placement of the entire gene product on the microarray compared with the analysis of up to thousands of individual molecules by traditional sequencing methods. A functional gene array that has been developed by the Zhou laboratory, the GeoChip, will be discussed as an example of a microarray that dynamically identifies functional activities of multiple members within a community. The recent version of GeoChip contains more than 24,000 50mer

  1. MicroRNA expression profiling using microarrays.

    PubMed

    Love, Cassandra; Dave, Sandeep

    2013-01-01

    MicroRNAs are small noncoding RNAs which are able to regulate gene expression at both the transcriptional and translational levels. There is a growing recognition of the role of microRNAs in nearly every tissue type and cellular process. Thus there is an increasing need for accurate quantitation of microRNA expression in a variety of tissues. Microarrays provide a robust method for the examination of microRNA expression. In this chapter, we describe detailed methods for the use of microarrays to measure microRNA expression and discuss methods for the analysis of microRNA expression data.

  2. Overview of DNA microarrays: types, applications, and their future.

    PubMed

    Bumgarner, Roger

    2013-01-01

    This unit provides an overview of DNA microarrays. Microarrays are a technology in which thousands of nucleic acids are bound to a surface and are used to measure the relative concentration of nucleic acid sequences in a mixture via hybridization and subsequent detection of the hybridization events. This overview first discusses the history of microarrays and the antecedent technologies that led to their development. This is followed by discussion of the methods of manufacture of microarrays and the most common biological applications. The unit ends with a brief description of the limitations of microarrays and discusses how microarrays are being rapidly replaced by DNA sequencing technologies.

  3. Analysis of High-Throughput ELISA Microarray Data

    SciTech Connect

    White, Amanda M.; Daly, Don S.; Zangar, Richard C.

    2011-02-23

    Our research group develops analytical methods and software for the high-throughput analysis of quantitative enzyme-linked immunosorbent assay (ELISA) microarrays. ELISA microarrays differ from DNA microarrays in several fundamental aspects and most algorithms for analysis of DNA microarray data are not applicable to ELISA microarrays. In this review, we provide an overview of the steps involved in ELISA microarray data analysis and how the statistically sound algorithms we have developed provide an integrated software suite to address the needs of each data-processing step. The algorithms discussed are available in a set of open-source software tools (http://www.pnl.gov/statistics/ProMAT).

  4. Optimized LOWESS normalization parameter selection for DNA microarray data

    PubMed Central

    Berger, John A; Hautaniemi, Sampsa; Järvinen, Anna-Kaarina; Edgren, Henrik; Mitra, Sanjit K; Astola, Jaakko

    2004-01-01

    Background Microarray data normalization is an important step for obtaining data that are reliable and usable for subsequent analysis. One of the most commonly utilized normalization techniques is the locally weighted scatterplot smoothing (LOWESS) algorithm. However, a much overlooked concern with the LOWESS normalization strategy deals with choosing the appropriate parameters. Parameters are usually chosen arbitrarily, which may reduce the efficiency of the normalization and result in non-optimally normalized data. Thus, there is a need to explore LOWESS parameter selection in greater detail. Results and discussion In this work, we discuss how to choose parameters for the LOWESS method. Moreover, we present an optimization approach for obtaining the fraction of data points utilized in the local regression and analyze results for local print-tip normalization. The optimization procedure determines the bandwidth parameter for the local regression by minimizing a cost function that represents the mean-squared difference between the LOWESS estimates and the normalization reference level. We demonstrate the utility of the systematic parameter selection using two publicly available data sets. The first data set consists of three self versus self hybridizations, which allow for a quantitative study of the optimization method. The second data set contains a collection of DNA microarray data from a breast cancer study utilizing four breast cancer cell lines. Our results show that different parameter choices for the bandwidth window yield dramatically different calibration results in both studies. Conclusions Results derived from the self versus self experiment indicate that the proposed optimization approach is a plausible solution for estimating the LOWESS parameters, while results from the breast cancer experiment show that the optimization procedure is readily applicable to real-life microarray data normalization. In summary, the systematic approach to obtain critical

  5. An evaluation of two-channel ChIP-on-chip and DNA methylation microarray normalization strategies.

    PubMed

    Adriaens, Michiel E; Jaillard, Magali; Eijssen, Lars M T; Mayer, Claus-Dieter; Evelo, Chris T A

    2012-01-25

    The combination of chromatin immunoprecipitation with two-channel microarray technology enables genome-wide mapping of binding sites of DNA-interacting proteins (ChIP-on-chip) or sites with methylated CpG di-nucleotides (DNA methylation microarray). These powerful tools are the gateway to understanding gene transcription regulation. Since the goals of such studies, the sample preparation procedures, the microarray content and study design are all different from transcriptomics microarrays, the data pre-processing strategies traditionally applied to transcriptomics microarrays may not be appropriate. Particularly, the main challenge of the normalization of "regulation microarrays" is (i) to make the data of individual microarrays quantitatively comparable and (ii) to keep the signals of the enriched probes, representing DNA sequences from the precipitate, as distinguishable as possible from the signals of the un-enriched probes, representing DNA sequences largely absent from the precipitate. We compare several widely used normalization approaches (VSN, LOWESS, quantile, T-quantile, Tukey's biweight scaling, Peng's method) applied to a selection of regulation microarray datasets, ranging from DNA methylation to transcription factor binding and histone modification studies. Through comparison of the data distributions of control probes and gene promoter probes before and after normalization, and assessment of the power to identify known enriched genomic regions after normalization, we demonstrate that there are clear differences in performance between normalization procedures. T-quantile normalization applied separately on the channels and Tukey's biweight scaling outperform other methods in terms of the conservation of enriched and un-enriched signal separation, as well as in identification of genomic regions known to be enriched. T-quantile normalization is preferable as it additionally improves comparability between microarrays. In contrast, popular normalization

  6. An investigation of biomarkers derived from legacy microarray data for their utility in the RNA-seq era.

    PubMed

    Su, Zhenqiang; Fang, Hong; Hong, Huixiao; Shi, Leming; Zhang, Wenqian; Zhang, Wenwei; Zhang, Yanyan; Dong, Zirui; Lancashire, Lee J; Bessarabova, Marina; Yang, Xi; Ning, Baitang; Gong, Binsheng; Meehan, Joe; Xu, Joshua; Ge, Weigong; Perkins, Roger; Fischer, Matthias; Tong, Weida

    2014-12-03

    Gene expression microarray has been the primary biomarker platform ubiquitously applied in biomedical research, resulting in enormous data, predictive models, and biomarkers accrued. Recently, RNA-seq has looked likely to replace microarrays, but there will be a period where both technologies co-exist. This raises two important questions: Can microarray-based models and biomarkers be directly applied to RNA-seq data? Can future RNA-seq-based predictive models and biomarkers be applied to microarray data to leverage past investment? We systematically evaluated the transferability of predictive models and signature genes between microarray and RNA-seq using two large clinical data sets. The complexity of cross-platform sequence correspondence was considered in the analysis and examined using three human and two rat data sets, and three levels of mapping complexity were revealed. Three algorithms representing different modeling complexity were applied to the three levels of mappings for each of the eight binary endpoints and Cox regression was used to model survival times with expression data. In total, 240,096 predictive models were examined. Signature genes of predictive models are reciprocally transferable between microarray and RNA-seq data for model development, and microarray-based models can accurately predict RNA-seq-profiled samples; while RNA-seq-based models are less accurate in predicting microarray-profiled samples and are affected both by the choice of modeling algorithm and the gene mapping complexity. The results suggest continued usefulness of legacy microarray data and established microarray biomarkers and predictive models in the forthcoming RNA-seq era.

  7. CrossNorm: a novel normalization strategy for microarray data in cancers

    PubMed Central

    Cheng, Lixin; Lo, Leung-Yau; Tang, Nelson L. S.; Wang, Dong; Leung, Kwong-Sak

    2016-01-01

    Normalization is essential to get rid of biases in microarray data for their accurate analysis. Existing normalization methods for microarray gene expression data commonly assume a similar global expression pattern among samples being studied. However, scenarios of global shifts in gene expressions are dominant in cancers, making the assumption invalid. To alleviate the problem, here we propose and develop a novel normalization strategy, Cross Normalization (CrossNorm), for microarray data with unbalanced transcript levels among samples. Conventional procedures, such as RMA and LOESS, arbitrarily flatten the difference between case and control groups leading to biased gene expression estimates. Noticeably, applying these methods under the strategy of CrossNorm, which makes use of the overall statistics of the original signals, the results showed significantly improved robustness and accuracy in estimating transcript level dynamics for a series of publicly available datasets, including titration experiment, simulated data, spike-in data and several real-life microarray datasets across various types of cancers. The results have important implications for the past and the future cancer studies based on microarray samples with non-negligible difference. Moreover, the strategy can also be applied to other sorts of high-throughput data as long as the experiments have global expression variations between conditions. PMID:26732145

  8. Fuzzy support vector machine: an efficient rule-based classification technique for microarrays.

    PubMed

    Hajiloo, Mohsen; Rabiee, Hamid R; Anooshahpour, Mahdi

    2013-01-01

    The abundance of gene expression microarray data has led to the development of machine learning algorithms applicable for tackling disease diagnosis, disease prognosis, and treatment selection problems. However, these algorithms often produce classifiers with weaknesses in terms of accuracy, robustness, and interpretability. This paper introduces fuzzy support vector machine which is a learning algorithm based on combination of fuzzy classifiers and kernel machines for microarray classification. Experimental results on public leukemia, prostate, and colon cancer datasets show that fuzzy support vector machine applied in combination with filter or wrapper feature selection methods develops a robust model with higher accuracy than the conventional microarray classification models such as support vector machine, artificial neural network, decision trees, k nearest neighbors, and diagonal linear discriminant analysis. Furthermore, the interpretable rule-base inferred from fuzzy support vector machine helps extracting biological knowledge from microarray data. Fuzzy support vector machine as a new classification model with high generalization power, robustness, and good interpretability seems to be a promising tool for gene expression microarray classification.

  9. MiMiR: a comprehensive solution for storage, annotation and exchange of microarray data

    PubMed Central

    Navarange, Mahendra; Game, Laurence; Fowler, Derek; Wadekar, Vihar; Banks, Helen; Cooley, Nicola; Rahman, Fatimah; Hinshelwood, Justin; Broderick, Peter; Causton, Helen C

    2005-01-01

    Background The generation of large amounts of microarray data presents challenges for data collection, annotation, exchange and analysis. Although there are now widely accepted formats, minimum standards for data content and ontologies for microarray data, only a few groups are using them together to build and populate large-scale databases. Structured environments for data management are crucial for making full use of these data. Description The MiMiR database provides a comprehensive infrastructure for microarray data annotation, storage and exchange and is based on the MAGE format. MiMiR is MIAME-supportive, customised for use with data generated on the Affymetrix platform and includes a tool for data annotation using ontologies. Detailed information on the experiment, methods, reagents and signal intensity data can be captured in a systematic format. Reports screens permit the user to query the database, to view annotation on individual experiments and provide summary statistics. MiMiR has tools for automatic upload of the data from the microarray scanner and export to databases using MAGE-ML. Conclusion MiMiR facilitates microarray data management, annotation and exchange, in line with international guidelines. The database is valuable for underpinning research activities and promotes a systematic approach to data handling. Copies of MiMiR are freely available to academic groups under licence. PMID:16280078

  10. Teaching Practices and Language Use in Two-Way Dual Language Immersion Programs in a Large Public School District

    ERIC Educational Resources Information Center

    Li, Jennifer; Steele, Jennifer; Slater, Robert; Bacon, Michael; Miller, Trey

    2016-01-01

    Many educators and policy makers look to two-way dual language immersion as one of the most promising options to close achievement gaps for English learners. However, the programs' effectiveness depends on the quality of their implementation. This article reports on a large-scale study of the implementation of dual language immersion across a…

  11. The Utilization of Psychologists for Staff Development in a Large Public School System: A Staff Development Director's Perspective.

    ERIC Educational Resources Information Center

    Stone, James L., Jr.

    This model proposes the TAP Team approach as an on-site delivery system for local school staff development in large, urban school systems. TAP emphasizes in-service training for both upgrading skills of staff and for helping staff acquire new skills in the areas of coping strategies, classroom management, communication skills, instructional…

  12. Teaching Practices and Language Use in Two-Way Dual Language Immersion Programs in a Large Public School District

    ERIC Educational Resources Information Center

    Li, Jennifer; Steele, Jennifer; Slater, Robert; Bacon, Michael; Miller, Trey

    2016-01-01

    Many educators and policy makers look to two-way dual language immersion as one of the most promising options to close achievement gaps for English learners. However, the programs' effectiveness depends on the quality of their implementation. This article reports on a large-scale study of the implementation of dual language immersion across a…

  13. Self-Reported Household Impacts of Large-Scale Chemical Contamination of the Public Water Supply, Charleston, West Virginia, USA

    PubMed Central

    Schade, Charles P.; Wright, Nasandra; Gupta, Rahul; Latif, David A.; Jha, Ayan; Robinson, John

    2015-01-01

    A January 2014 industrial accident contaminated the public water supply of approximately 300,000 homes in and near Charleston, West Virginia (USA) with low levels of a strongly-smelling substance consisting principally of 4-methylcyclohexane methanol (MCHM). The ensuing state of emergency closed schools and businesses. Hundreds of people sought medical care for symptoms they related to the incident. We surveyed 498 households by telephone to assess the episode’s health and economic impact as well as public perception of risk communication by responsible officials. Thirty two percent of households (159/498) reported someone with illness believed to be related to the chemical spill, chiefly dermatological or gastrointestinal symptoms. Respondents experienced more frequent symptoms of psychological distress during and within 30 days of the emergency than 90 days later. Sixty-seven respondent households (13%) had someone miss work because of the crisis, missing a median of 3 days of work. Of 443 households reporting extra expenses due to the crisis, 46% spent less than $100, while 10% spent over $500 (estimated average about $206). More than 80% (401/485) households learned of the spill the same day it occurred. More than 2/3 of households complied fully with “do not use” orders that were issued; only 8% reported drinking water against advice. Household assessments of official communications varied by source, with local officials receiving an average “B” rating, whereas some federal and water company communication received a “D” grade. More than 90% of households obtained safe water from distribution centers or stores during the emergency. We conclude that the spill had major economic impact with substantial numbers of individuals reporting incident-related illnesses and psychological distress. Authorities were successful supplying emergency drinking water, but less so with risk communication. PMID:25951197

  14. Facts, misconceptions, and myths about cancer. What do patients with gynecological cancer and the female public at large know?

    PubMed

    Carlsson, M E; Strang, P M

    1997-04-01

    Misconceptions about cancer may increase the level of fear in the general public and render coping more difficult in cancer patients. The aim of this survey was to study the level of knowledge and misconceptions. A questionnaire comprising 27 questions related to cancer etiology, treatment, and prognosis was mailed to 100 patients with gynecological cancers and to 120 healthy women. The response rates were 86 and 78%, respectively. The proportion of correct answers was similar in both groups. Everyone considered cancer to be noncontagious. A majority knew that gynecological cancers have a good prognosis if diagnosed in early stages and that morphine is very effective in the treatment of severe cancer pain, but believed that it causes addiction. Questions with a significant proportion of erroneous answers were related to hormones and cancer. Patients were more aware of the risk associated between unopposed estrogen therapy and endometrial carcinoma (P < 0.05). However, the patients incorrectly believed that combined hormonal therapy (estrogen + gestagens) also increased the risk of endometrial and ovarians carcinoma and they did so much more often than the control group (P < 0.05). The general public more often believed that cancer often arises as a consequence of previous physical injury (P < 0.05). Formal education correlated positively with correct responses (P < 0.01). In conclusion, the results emphasize the importance of proper information about cancer and cancer treatment, especially with regard to hormonal treatment and the use of morphine. Individuals with the least formal education constitute an especially important target group for information.

  15. Self-reported household impacts of large-scale chemical contamination of the public water supply, Charleston, West Virginia, USA.

    PubMed

    Schade, Charles P; Wright, Nasandra; Gupta, Rahul; Latif, David A; Jha, Ayan; Robinson, John

    2015-01-01

    A January 2014 industrial accident contaminated the public water supply of approximately 300,000 homes in and near Charleston, West Virginia (USA) with low levels of a strongly-smelling substance consisting principally of 4-methylcyclohexane methanol (MCHM). The ensuing state of emergency closed schools and businesses. Hundreds of people sought medical care for symptoms they related to the incident. We surveyed 498 households by telephone to assess the episode's health and economic impact as well as public perception of risk communication by responsible officials. Thirty two percent of households (159/498) reported someone with illness believed to be related to the chemical spill, chiefly dermatological or gastrointestinal symptoms. Respondents experienced more frequent symptoms of psychological distress during and within 30 days of the emergency than 90 days later. Sixty-seven respondent households (13%) had someone miss work because of the crisis, missing a median of 3 days of work. Of 443 households reporting extra expenses due to the crisis, 46% spent less than $100, while 10% spent over $500 (estimated average about $206). More than 80% (401/485) households learned of the spill the same day it occurred. More than 2/3 of households complied fully with "do not use" orders that were issued; only 8% reported drinking water against advice. Household assessments of official communications varied by source, with local officials receiving an average "B" rating, whereas some federal and water company communication received a "D" grade. More than 90% of households obtained safe water from distribution centers or stores during the emergency. We conclude that the spill had major economic impact with substantial numbers of individuals reporting incident-related illnesses and psychological distress. Authorities were successful supplying emergency drinking water, but less so with risk communication.

  16. Microbial forensics: fiber optic microarray subtyping of Bacillus anthracis

    NASA Astrophysics Data System (ADS)

    Shepard, Jason R. E.

    2009-05-01

    The past decade has seen increased development and subsequent adoption of rapid molecular techniques involving DNA analysis for detection of pathogenic microorganisms, also termed microbial forensics. The continued accumulation of microbial sequence information in genomic databases now better positions the field of high-throughput DNA analysis to proceed in a more manageable fashion. The potential to build off of these databases exists as technology continues to develop, which will enable more rapid, cost effective analyses. This wealth of genetic information, along with new technologies, has the potential to better address some of the current problems and solve the key issues involved in DNA analysis of pathogenic microorganisms. To this end, a high density fiber optic microarray has been employed, housing numerous DNA sequences simultaneously for detection of various pathogenic microorganisms, including Bacillus anthracis, among others. Each organism is analyzed with multiple sequences and can be sub-typed against other closely related organisms. For public health labs, real-time PCR methods have been developed as an initial preliminary screen, but culture and growth are still considered the gold standard. Technologies employing higher throughput than these standard methods are better suited to capitalize on the limitless potential garnered from the sequence information. Microarray analyses are one such format positioned to exploit this potential, and our array platform is reusable, allowing repetitive tests on a single array, providing an increase in throughput and decrease in cost, along with a certainty of detection, down to the individual strain level.

  17. Diagnostic Oligonucleotide Microarray Fingerprinting of Bacillus Isolates

    SciTech Connect

    Chandler, Darrell P.; Alferov, Oleg; Chernov, Boris; Daly, Don S.; Golova, Julia; Perov, Alexander N.; Protic, Miroslava; Robison, Richard; Shipma, Matthew; White, Amanda M.; Willse, Alan R.

    2006-01-01

    A diagnostic, genome-independent microbial fingerprinting method using DNA oligonucleotide microarrays was used for high-resolution differentiation between closely related Bacillus strains, including two strains of Bacillus anthracis that are monomorphic (indistinguishable) via amplified fragment length polymorphism fingerprinting techniques. Replicated hybridizations on 391-probe nonamer arrays were used to construct a prototype fingerprint library for quantitative comparisons. Descriptive analysis of the fingerprints, including phylogenetic reconstruction, is consistent with previous taxonomic organization of the genus. Newly developed statistical analysis methods were used to quantitatively compare and objectively confirm apparent differences in microarray fingerprints with the statistical rigor required for microbial forensics and clinical diagnostics. These data suggest that a relatively simple fingerprinting microarray and statistical analysis method can differentiate between species in the Bacillus cereus complex, and between strains of B. anthracis. A synthetic DNA standard was used to understand underlying microarray and process-level variability, leading to specific recommendations for the development of a standard operating procedure and/or continued technology enhancements for microbial forensics and diagnostics.

  18. Analytical Protein Microarrays: Advancements Towards Clinical Applications.

    PubMed

    Sauer, Ursula

    2017-01-29

    Protein microarrays represent a powerful technology with the potential to serve as tools for the detection of a broad range of analytes in numerous applications such as diagnostics, drug development, food safety, and environmental monitoring. Key features of analytical protein microarrays include high throughput and relatively low costs due to minimal reagent consumption, multiplexing, fast kinetics and hence measurements, and the possibility of functional integration. So far, especially fundamental studies in molecular and cell biology have been conducted using protein microarrays, while the potential for clinical, notably point-of-care applications is not yet fully utilized. The question arises what features have to be implemented and what improvements have to be made in order to fully exploit the technology. In the past we have identified various obstacles that have to be overcome in order to promote protein microarray technology in the diagnostic field. Issues that need significant improvement to make the technology more attractive for the diagnostic market are for instance: too low sensitivity and deficiency in reproducibility, inadequate analysis time, lack of high-quality antibodies and validated reagents, lack of automation and portable instruments, and cost of instruments necessary for chip production and read-out. The scope of the paper at hand is to review approaches to solve these problems.

  19. Analytical Protein Microarrays: Advancements Towards Clinical Applications

    PubMed Central

    Sauer, Ursula

    2017-01-01

    Protein microarrays represent a powerful technology with the potential to serve as tools for the detection of a broad range of analytes in numerous applications such as diagnostics, drug development, food safety, and environmental monitoring. Key features of analytical protein microarrays include high throughput and relatively low costs due to minimal reagent consumption, multiplexing, fast kinetics and hence measurements, and the possibility of functional integration. So far, especially fundamental studies in molecular and cell biology have been conducted using protein microarrays, while the potential for clinical, notably point-of-care applications is not yet fully utilized. The question arises what features have to be implemented and what improvements have to be made in order to fully exploit the technology. In the past we have identified various obstacles that have to be overcome in order to promote protein microarray technology in the diagnostic field. Issues that need significant improvement to make the technology more attractive for the diagnostic market are for instance: too low sensitivity and deficiency in reproducibility, inadequate analysis time, lack of high-quality antibodies and validated reagents, lack of automation and portable instruments, and cost of instruments necessary for chip production and read-out. The scope of the paper at hand is to review approaches to solve these problems. PMID:28146048

  20. Microarrays (DNA Chips) for the Classroom Laboratory

    ERIC Educational Resources Information Center

    Barnard, Betsy; Sussman, Michael; BonDurant, Sandra Splinter; Nienhuis, James; Krysan, Patrick

    2006-01-01

    We have developed and optimized the necessary laboratory materials to make DNA microarray technology accessible to all high school students at a fraction of both cost and data size. The primary component is a DNA chip/array that students "print" by hand and then analyze using research tools that have been adapted for classroom use. The…

  1. High confidence rule mining for microarray analysis.

    PubMed

    McIntosh, Tara; Chawla, Sanjay

    2007-01-01

    We present an association rule mining method for mining high confidence rules, which describe interesting gene relationships from microarray datasets. Microarray datasets typically contain an order of magnitude more genes than experiments, rendering many data mining methods impractical as they are optimised for sparse datasets. A new family of row-enumeration rule mining algorithms have emerged to facilitate mining in dense datasets. These algorithms rely on pruning infrequent relationships to reduce the search space by using the support measure. This major shortcoming results in the pruning of many potentially interesting rules with low support but high confidence. We propose a new row-enumeration rule mining method, MaxConf, to mine high confidence rules from microarray data. MaxConf is a support-free algorithm which directly uses the confidence measure to effectively prune the search space. Experiments on three microarray datasets show that MaxConf outperforms support-based rule mining with respect to scalability and rule extraction. Furthermore, detailed biological analyses demonstrate the effectiveness of our approach -- the rules discovered by MaxConf are substantially more interesting and meaningful compared with support-based methods.

  2. MICROARRAY DATA ANALYSIS USING MULTIPLE STATISTICAL MODELS

    EPA Science Inventory

    Microarray Data Analysis Using Multiple Statistical Models

    Wenjun Bao1, Judith E. Schmid1, Amber K. Goetz1, Ming Ouyang2, William J. Welsh2,Andrew I. Brooks3,4, ChiYi Chu3,Mitsunori Ogihara3,4, Yinhe Cheng5, David J. Dix1. 1National Health and Environmental Effects Researc...

  3. DISC-BASED IMMUNOASSAY MICROARRAYS. (R825433)

    EPA Science Inventory

    Microarray technology as applied to areas that include genomics, diagnostics, environmental, and drug discovery, is an interesting research topic for which different chip-based devices have been developed. As an alternative, we have explored the principle of compact disc-based...

  4. Microarrays (DNA Chips) for the Classroom Laboratory

    ERIC Educational Resources Information Center

    Barnard, Betsy; Sussman, Michael; BonDurant, Sandra Splinter; Nienhuis, James; Krysan, Patrick

    2006-01-01

    We have developed and optimized the necessary laboratory materials to make DNA microarray technology accessible to all high school students at a fraction of both cost and data size. The primary component is a DNA chip/array that students "print" by hand and then analyze using research tools that have been adapted for classroom use. The…

  5. Microarray technology: a promising tool in nutrigenomics.

    PubMed

    Masotti, Andrea; Da Sacco, Letizia; Bottazzo, Gian Franco; Alisi, Anna

    2010-08-01

    Microarray technology is a powerful tool for the global evaluation of gene expression profiles in tissues and for understanding many of the factors controlling the regulation of gene transcription. This technique not only provides a considerable amount of information on markers and predictive factors that may potentially characterize a specific clinical picture, but also promises new applications for therapy. One of the most recent applications of microarrays concerns nutritional genomics. Nutritional genomics, known as nutrigenomics, aims to identify and understand mechanisms of molecular interaction between nutrients and/or other dietary bioactive compounds and the genome. Actually, many nutrigenomic studies utilize new approaches such as microarrays, genomics, and bioinformatics to understand how nutrients influence gene expression. The coupling of these new technologies with nutrigenomics promises to lead to improvements in diet and health. In fact, it may provide new information which can be used to ameliorate dietary regimens and to discover novel natural agents for the treatment of important diseases such as diabetes and cancer. This critical review gives an overview of the clinical relevance of a nutritional approach to several important diseases, and proposes the use of microarray for nutrigenomic studies.

  6. DISC-BASED IMMUNOASSAY MICROARRAYS. (R825433)

    EPA Science Inventory

    Microarray technology as applied to areas that include genomics, diagnostics, environmental, and drug discovery, is an interesting research topic for which different chip-based devices have been developed. As an alternative, we have explored the principle of compact disc-based...

  7. MICROARRAY DATA ANALYSIS USING MULTIPLE STATISTICAL MODELS

    EPA Science Inventory

    Microarray Data Analysis Using Multiple Statistical Models

    Wenjun Bao1, Judith E. Schmid1, Amber K. Goetz1, Ming Ouyang2, William J. Welsh2,Andrew I. Brooks3,4, ChiYi Chu3,Mitsunori Ogihara3,4, Yinhe Cheng5, David J. Dix1. 1National Health and Environmental Effects Researc...

  8. Shrinkage covariance matrix approach for microarray data

    NASA Astrophysics Data System (ADS)

    Karjanto, Suryaefiza; Aripin, Rasimah

    2013-04-01

    Microarray technology was developed for the purpose of monitoring the expression levels of thousands of genes. A microarray data set typically consists of tens of thousands of genes (variables) from just dozens of samples due to various constraints including the high cost of producing microarray chips. As a result, the widely used standard covariance estimator is not appropriate for this purpose. One such technique is the Hotelling's T2 statistic which is a multivariate test statistic for comparing means between two groups. It requires that the number of observations (n) exceeds the number of genes (p) in the set but in microarray studies it is common that n < p. This leads to a biased estimate of the covariance matrix. In this study, the Hotelling's T2 statistic with the shrinkage approach is proposed to estimate the covariance matrix for testing differential gene expression. The performance of this approach is then compared with other commonly used multivariate tests using a widely analysed diabetes data set as illustrations. The results across the methods are consistent, implying that this approach provides an alternative to existing techniques.

  9. PRACTICAL STRATEGIES FOR PROCESSING AND ANALYZING SPOTTED OLIGONUCLEOTIDE MICROARRAY DATA

    EPA Science Inventory

    Thoughtful data analysis is as important as experimental design, biological sample quality, and appropriate experimental procedures for making microarrays a useful supplement to traditional toxicology. In the present study, spotted oligonucleotide microarrays were used to profile...

  10. A Method of Microarray Data Storage Using Array Data Type

    PubMed Central

    Tsoi, Lam C.; Zheng, W. Jim

    2009-01-01

    A well-designed microarray database can provide valuable information on gene expression levels. However, designing an efficient microarray database with minimum space usage is not an easy task since designers need to integrate the microarray data with the information of genes, probe annotation, and the descriptions of each microarray experiment. Developing better methods to store microarray data can greatly improve the efficiency and usefulness of such data. A new schema is proposed to store microarray data by using array data type in an object-relational database management system – PostgreSQL. The implemented database can store all the microarray data from the same chip in an array data structure. The variable length array data type in PostgreSQL can store microarray data from same chip. The implementation of our schema can help to increase the data retrieval and space efficiency. PMID:17392028

  11. PRACTICAL STRATEGIES FOR PROCESSING AND ANALYZING SPOTTED OLIGONUCLEOTIDE MICROARRAY DATA

    EPA Science Inventory

    Thoughtful data analysis is as important as experimental design, biological sample quality, and appropriate experimental procedures for making microarrays a useful supplement to traditional toxicology. In the present study, spotted oligonucleotide microarrays were used to profile...

  12. Adjustment method for microarray data generated using two-cycle RNA labeling protocol.

    PubMed

    Wang, Fugui; Chen, Rui; Ji, Dong; Bai, Shunong; Qian, Minping; Deng, Minghua

    2013-01-16

    Microarray technology is widely utilized for monitoring the expression changes of thousands of genes simultaneously. However, the requirement of relatively large amount of RNA for labeling and hybridization makes it difficult to perform microarray experiments with limited biological materials, thus leads to the development of many methods for preparing and amplifying mRNA. It is addressed that amplification methods usually bring bias, which may strongly hamper the following interpretation of the results. A big challenge is how to correct for the bias before further analysis. In this article, we observed the bias in rice gene expression microarray data generated with the Affymetrix one-cycle, two-cycle RNA labeling protocols, followed by validation with Real Time PCR. Based on these data, we proposed a statistical framework to model the processes of mRNA two-cycle linear amplification, and established a linear model for probe level correction. Maximum Likelihood Estimation (MLE) was applied to perform robust estimation of the Retaining Rate for each probe. After bias correction, some known pre-processing methods, such as PDNN, could be combined to finish preprocessing. Then, we evaluated our model and the results suggest that our model can effectively increase the quality of the microarray raw data: (i) Decrease the Coefficient of Variation for PM intensities of probe sets; (ii) Distinguish the microarray samples of five stages for rice stamen development more clearly; (iii) Improve the correlation coefficients among stamen microarray samples. We also discussed the necessity of model adjustment by comparing with another simple adjustment method. We conclude that the adjustment model is necessary and could effectively increase the quality of estimation for gene expression from the microarray raw data.

  13. Examining microarray slide quality for the EPA using SNL's hyperspectral microarray scanner.

    SciTech Connect

    Rohde, Rachel M.; Timlin, Jerilyn Ann

    2005-11-01

    This report summarizes research performed at Sandia National Laboratories (SNL) in collaboration with the Environmental Protection Agency (EPA) to assess microarray quality on arrays from two platforms of interest to the EPA. Custom microarrays from two novel, commercially produced array platforms were imaged with SNL's unique hyperspectral imaging technology and multivariate data analysis was performed to investigate sources of emission on the arrays. No extraneous sources of emission were evident in any of the array areas scanned. This led to the conclusions that either of these array platforms could produce high quality, reliable microarray data for the EPA toxicology programs. Hyperspectral imaging results are presented and recommendations for microarray analyses using these platforms are detailed within the report.

  14. Design of a covalently bonded glycosphingolipid microarray.

    PubMed

    Arigi, Emma; Blixt, Ola; Buschard, Karsten; Clausen, Henrik; Levery, Steven B

    2012-01-01

    Glycosphingolipids (GSLs) are well known ubiquitous constituents of all eukaryotic cell membranes, yet their normal biological functions are not fully understood. As with other glycoconjugates and saccharides, solid phase display on microarrays potentially provides an effective platform for in vitro study of their functional interactions. However, with few exceptions, the most widely used microarray platforms display only the glycan moiety of GSLs, which not only ignores potential modulating effects of the lipid aglycone, but inherently limits the scope of application, excluding, for example, the major classes of plant and fungal GSLs. In this work, a prototype "universal" GSL-based covalent microarray has been designed, and preliminary evaluation of its potential utility in assaying protein-GSL binding interactions investigated. An essential step in development involved the enzymatic release of the fatty acyl moiety of the ceramide aglycone of selected mammalian GSLs with sphingolipid N-deacylase (SCDase). Derivatization of the free amino group of a typical lyso-GSL, lyso-G(M1), with a prototype linker assembled from succinimidyl-[(N-maleimidopropionamido)-diethyleneglycol] ester and 2-mercaptoethylamine, was also tested. Underivatized or linker-derivatized lyso-GSL were then immobilized on N-hydroxysuccinimide- or epoxide-activated glass microarray slides and probed with carbohydrate binding proteins of known or partially known specificities (i.e., cholera toxin B-chain; peanut agglutinin, a monoclonal antibody to sulfatide, Sulph 1; and a polyclonal antiserum reactive to asialo-G(M2)). Preliminary evaluation of the method indicated successful immobilization of the GSLs, and selective binding of test probes. The potential utility of this methodology for designing covalent microarrays that incorporate GSLs for serodiagnosis is discussed.

  15. Methods in molecular cardiology: microarray technology

    PubMed Central

    van den Bosch, B.; Doevendans, P.A.; Lips, D.; Smeets, H.J.M.

    2003-01-01

    It has become more and more evident that changes in expression levels of genes can play an important role in cardiovascular diseases. Specific gene expression profiles may explain, for example, the pathophysiology of myocardial hypertrophy and pump failure and may provide clues for therapeutic interventions. Knowledge of gene expression patterns can also be applied for diagnostic and prognostic purposes, in which differences in gene activity can be used for classification. DNA microarray technology has become the method of choice to simultaneously study the expression of many different genes in a single assay. Each microarray contains many thousands of different DNA sequences attached to a glass slide. The amount of messenger RNA, which is a measure of gene activity, is compared for each gene on the microarray by labelling the mRNA with different fluorescently labelled nucleotides (Cy3 or Cy5) for the test and reference samples. After hybridisation to the microarray the relative amounts of a particular gene transcript in the two samples can be determined by measuring the signal intensities for the fluorescent groups (Cy3 and Cy5) and calculating signal ratios. This paper describes the development of in-house microarray technology, using commercially available cDNA collections. Several technical approaches will be compared and an overview of the pitfalls and possibilities will be presented. The technology will be explained in the context of our project to determine gene expression differences between normal, hypertrophic and failing heart. ImagesFigure 1Figure 2Figure 3Figure 4Figure 5Figure 6Figure 7Figure 9 PMID:25696214

  16. Comparison of gene expression microarray data with count-based RNA measurements informs microarray interpretation.

    PubMed

    Richard, Arianne C; Lyons, Paul A; Peters, James E; Biasci, Daniele; Flint, Shaun M; Lee, James C; McKinney, Eoin F; Siegel, Richard M; Smith, Kenneth G C

    2014-08-04

    Although numerous investigations have compared gene expression microarray platforms, preprocessing methods and batch correction algorithms using constructed spike-in or dilution datasets, there remains a paucity of studies examining the properties of microarray data using diverse biological samples. Most microarray experiments seek to identify subtle differences between samples with variable background noise, a scenario poorly represented by constructed datasets. Thus, microarray users lack important information regarding the complexities introduced in real-world experimental settings. The recent development of a multiplexed, digital technology for nucleic acid measurement enables counting of individual RNA molecules without amplification and, for the first time, permits such a study. Using a set of human leukocyte subset RNA samples, we compared previously acquired microarray expression values with RNA molecule counts determined by the nCounter Analysis System (NanoString Technologies) in selected genes. We found that gene measurements across samples correlated well between the two platforms, particularly for high-variance genes, while genes deemed unexpressed by the nCounter generally had both low expression and low variance on the microarray. Confirming previous findings from spike-in and dilution datasets, this "gold-standard" comparison demonstrated signal compression that varied dramatically by expression level and, to a lesser extent, by dataset. Most importantly, examination of three different cell types revealed that noise levels differed across tissues. Microarray measurements generally correlate with relative RNA molecule counts within optimal ranges but suffer from expression-dependent accuracy bias and precision that varies across datasets. We urge microarray users to consider expression-level effects in signal interpretation and to evaluate noise properties in each dataset independently.

  17. Assessing the Capacity of the US Health Care System to Use Additional Mechanical Ventilators During a Large-Scale Public Health Emergency.

    PubMed

    Ajao, Adebola; Nystrom, Scott V; Koonin, Lisa M; Patel, Anita; Howell, David R; Baccam, Prasith; Lant, Tim; Malatino, Eileen; Chamberlin, Margaret; Meltzer, Martin I

    2015-12-01

    A large-scale public health emergency, such as a severe influenza pandemic, can generate large numbers of critically ill patients in a short time. We modeled the number of mechanical ventilators that could be used in addition to the number of hospital-based ventilators currently in use. We identified key components of the health care system needed to deliver ventilation therapy, quantified the maximum number of additional ventilators that each key component could support at various capacity levels (ie, conventional, contingency, and crisis), and determined the constraining key component at each capacity level. Our study results showed that US hospitals could absorb between 26,200 and 56,300 additional ventilators at the peak of a national influenza pandemic outbreak with robust pre-pandemic planning. The current US health care system may have limited capacity to use additional mechanical ventilators during a large-scale public health emergency. Emergency planners need to understand their health care systems' capability to absorb additional resources and expand care. This methodology could be adapted by emergency planners to determine stockpiling goals for critical resources or to identify alternatives to manage overwhelming critical care need.

  18. The Management of Long-Term Sickness Absence in Large Public Sector Healthcare Organisations: A Realist Evaluation Using Mixed Methods.

    PubMed

    Higgins, Angela; O'Halloran, Peter; Porter, Sam

    2015-09-01

    The success of measures to reduce long-term sickness absence (LTSA) in public sector organisations is contingent on organisational context. This realist evaluation investigates how interventions interact with context to influence successful management of LTSA. Multi-method case study in three Health and Social Care Trusts in Northern Ireland comprising realist literature review, semi-structured interviews (61 participants), Process-Mapping and feedback meetings (59 participants), observation of training, analysis of documents. Important activities included early intervention; workplace-based occupational rehabilitation; robust sickness absence policies with clear trigger points for action. Used appropriately, in a context of good interpersonal and interdepartmental communication and shared goals, these are able to increase the motivation of staff to return to work. Line managers are encouraged to take a proactive approach when senior managers provide support and accountability. Hindering factors: delayed intervention; inconsistent implementation of policy and procedure; lack of resources; organisational complexity; stakeholders misunderstanding each other's goals and motives. Different mechanisms have the potential to encourage common motivations for earlier return from LTSA, such as employees feeling that they have the support of their line manager to return to work and having the confidence to do so. Line managers' proactively engage when they have confidence in the support of seniors and in their own ability to address LTSA. Fostering these motivations calls for a thoughtful, diagnostic process, taking into account the contextual factors (and whether they can be modified) and considering how a given intervention can be used to trigger the appropriate mechanisms.

  19. Public appraisal of government efforts and participation intent in medico-ethical policymaking in Japan: a large scale national survey concerning brain death and organ transplant

    PubMed Central

    Sato, Hajime; Akabayashi, Akira; Kai, Ichiro

    2005-01-01

    Background Public satisfaction with policy process influences the legitimacy and acceptance of policies, and conditions the future political process, especially when contending ethical value judgments are involved. On the other hand, public involvement is required if effective policy is to be developed and accepted. Methods Using the data from a large-scale national opinion survey, this study evaluates public appraisal of past government efforts to legalize organ transplant from brain-dead bodies in Japan, and examines the public's intent to participate in future policy. Results A relatively large percentage of people became aware of the issue when government actions were initiated, and many increasingly formed their own opinions on the policy in question. However, a significant number (43.3%) remained unaware of any legislative efforts, and only 26.3% of those who were aware provided positive appraisals of the policymaking process. Furthermore, a majority of respondents (61.8%) indicated unwillingness to participate in future policy discussions of bioethical issues. Multivariate analysis revealed the following factors are associated with positive appraisals of policy development: greater age; earlier opinion formation; and familiarity with donor cards. Factors associated with likelihood of future participation in policy discussion include younger age, earlier attention to the issue, and knowledge of past government efforts. Those unwilling to participate cited as their reasons that experts are more knowledgeable and that the issues are too complex. Conclusions Results of an opinion survey in Japan were presented, and a set of factors statistically associated with them were discussed. Further efforts to improve policy making process on bioethical issues are desirable. PMID:15661080

  20. Why (and how) they decide to leave: A grounded theory analysis of STEM attrition at a large public research university

    NASA Astrophysics Data System (ADS)

    Minutello, Michael F.

    A grounded theory investigation of STEM attrition was conducted that describes and explains why undergraduates at a large Mid-Atlantic research university decided to leave their initial STEM majors to pursue non-STEM courses of study. Participants ultimately decided to leave their initial STEM majors because they were able to locate preferable non-STEM courses of study that did not present the same kinds of obstacles they had encountered in their original STEM majors. Grounded theory data analysis revealed participants initially enrolled in STEM majors with tenuous motivation that did not withstand the various obstacles that were present in introductory STEM coursework. Obstacles that acted as demotivating influences and prompted participants to locate alternative academic pathways include the following: (1.) disengaging curricula; (2.) competitive culture; (3.) disappointing grades; (4.) demanding time commitments; and (5.) unappealing career options. Once discouraged from continuing along their initial STEM pathways, participants then employed various strategies to discover suitable non-STEM majors that would allow them to realize their intrinsic interests and extrinsic goals. Participants were largely satisfied with their decisions to leave STEM and have achieved measures of personal satisfaction and professional success.

  1. The psychometric properties of the Illness Management and Recovery scale in a large American public mental health system.

    PubMed

    Sklar, Marisa; Sarkin, Andrew; Gilmer, Todd; Groessl, Erik

    2012-10-30

    The Illness Management and Recovery (IMR) scale was created to measure recovery outcomes produced by the IMR program. However, many other mental health care programs are now designed to impact recovery-oriented outcomes, and the IMR has been identified as a potentially valuable measure of recovery-oriented mental health outcomes. The purpose of this study was to examine the psychometric properties and structural validity of the IMR clinician scale within a variety of therapeutic modalities other than IMR in a large multiethnic sample (N=10,659) of clients with mental illness from a large U.S. county mental health system. Clients completed the IMR on a single occasion. Our estimates of internal consistency were stronger than those found in previous studies (α=0.82). The scale also related to other measures of theoretically similar constructs, supporting construct and criterion validity claims. Additionally, confirmatory factor analyses supported the multidimensional representation of the IMR clinician scale. The three-factor model of illness self-management and recovery was represented by dimensions of recovery, management, and substance use. These reliable psychometric properties support the use of both the original one-factor and revised three-factor models to assess illness self-management and recovery among a broad spectrum of clients with mental illness. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

  2. Mapping the affinity landscape of Thrombin-binding aptamers on 2'F-ANA/DNA chimeric G-Quadruplex microarrays.

    PubMed

    Lietard, Jory; Abou Assi, Hala; Gómez-Pinto, Irene; González, Carlos; Somoza, Mark M; Damha, Masad J

    2017-01-18

    In situ fabricated nucleic acids microarrays are versatile and very high-throughput platforms for aptamer optimization and discovery, but the chemical space that can be probed against a given target has largely been confined to DNA, while RNA and non-natural nucleic acid microarrays are still an essentially uncharted territory. 2'-Fluoroarabinonucleic acid (2'F-ANA) is a prime candidate for such use in microarrays. Indeed, 2'F-ANA chemistry is readily amenable to photolithographic microarray synthesis and its potential in high affinity aptamers has been recently discovered. We thus synthesized the first microarrays containing 2'F-ANA and 2'F-ANA/DNA chimeric sequences to fully map the binding affinity landscape of the TBA1 thrombin-binding G-quadruplex aptamer containing all 32 768 possible DNA-to-2'F-ANA mutations. The resulting microarray was screened against thrombin to identify a series of promising 2'F-ANA-modified aptamer candidates with Kds significantly lower than that of the unmodified control and which were found to adopt highly stable, antiparallel-folded G-quadruplex structures. The solution structure of the TBA1 aptamer modified with 2'F-ANA at position T3 shows that fluorine substitution preorganizes the dinucleotide loop into the proper conformation for interaction with thrombin. Overall, our work strengthens the potential of 2'F-ANA in aptamer research and further expands non-genomic applications of nucleic acids microarrays.

  3. Polypyrrole-peptide microarray for biomolecular interaction analysis by SPR imaging

    PubMed Central

    Villiers, Marie-Bernadette; Cortès, Sandra; Brakha, Carine; Marche, Patrice; Roget, André; Livache, Thierry

    2009-01-01

    Nowadays, high-throughput analysis of biological events is a great challenge which could take benefit of the recent development of microarray devices. The great potential of such technology is related to the availability of a chip bearing a large set of probes, stable and easy to obtain, and suitable for ligand binding detection. Here, we described a new method based on polypyrrole chemistry and allowing the covalent immobilization of peptides in a microarray format and on a gold surface compatible with the use of Surface Plasmon Resonance. This technique is then illustrated by the detection and characterization of antibodies induced by hepatitis C virus and present in patients’serums. PMID:19649603

  4. High-throughput cellular microarray platforms: applications in drug discovery, toxicology and stem cell research

    PubMed Central

    Fernandes, Tiago G.; Diogo, Maria Margarida; Clark, Douglas S.; Dordick, Jonathan S.; Cabral, Joaquim M.S.

    2017-01-01

    Cellular microarrays are powerful experimental tools for high-throughput screening of large numbers of test samples. Miniaturization increases assay throughput while reducing reagent consumption and the number of cells required, making these systems attractive for a wide range of assays in drug discovery, toxicology, stem cell research and potentially therapy. Here, we provide an overview of the emerging technologies that can be used to generate cellular microarrays, and we highlight recent significant advances in the field. This emerging and multidisciplinary approach offers new opportunities for the design and control of stem cells in tissue engineering and cellular therapies and promises to expedite drug discovery in the biotechnology and pharmaceutical industries. PMID:19398140

  5. Assessment of dosimetric quantities for patients undergoing X-ray examinations in a large public hospital in Brazil--a preliminary study.

    PubMed

    Lacerda, Marco Aurélio de Sousa; da Silva, Teógenes Augusto; Khoury, Helen Jamil

    2008-01-01

    The introduction of routine patient dosimetry to Brazilian radiological institutions is very necessary in order to meet national and international standard requirements for radiation protection. This work presents a survey of the air kerma-area product (P(KA)), the entrance surface air kerma (K(e)) and the effective dose (E) in common radiographic examinations during the routine of a large public hospital in the city of Belo Horizonte, Brazil. Results draw attention to the use of field sizes larger than the cassette dimension, the lack of both the collimation X-ray beam and the standardisation of the exposure parameters by radiology technicians.

  6. Multiplex RT-PCR and Automated Microarray for Detection of Eight Bovine Viruses.

    PubMed

    Lung, O; Furukawa-Stoffer, T; Burton Hughes, K; Pasick, J; King, D P; Hodko, D

    2016-11-23

    Microarrays can be a useful tool for pathogen detection as it allow for simultaneous interrogation of the presence of a large number of genetic sequences in a sample. However, conventional microarrays require extensive manual handling and multiple pieces of equipment for printing probes, hybridization, washing and signal detection. In this study, a reverse transcription (RT)-PCR with an accompanying novel automated microarray for simultaneous detection of eight viruses that affect cattle [vesicular stomatitis virus (VSV), bovine viral diarrhoea virus type 1 and type 2, bovine herpesvirus 1, bluetongue virus, malignant catarrhal fever virus, rinderpest virus (RPV) and parapox viruses] is described. The assay accurately identified a panel of 37 strains of the target viruses and identified a mixed infection. No non-specific reactions were observed with a panel of 23 non-target viruses associated with livestock. Vesicular stomatitis virus was detected as early as 2 days post-inoculation in oral swabs from experimentally infected animals. The limit of detection of the microarray assay was as low as 1 TCID50 /ml for RPV. The novel microarray platform automates the entire post-PCR steps of the assay and integrates electrophoretic-driven capture probe printing in a single user-friendly instrument that allows array layout and assay configuration to be user-customized on-site.

  7. ExpressYourself: a modular platform for processing and visualizing microarray data

    PubMed Central

    Luscombe, Nicholas M.; Royce, Thomas E.; Bertone, Paul; Echols, Nathaniel; Horak, Christine E.; Chang, Joseph T.; Snyder, Michael; Gerstein, Mark

    2003-01-01

    DNA microarrays are widely used in biological research; by analyzing differential hybridization on a single microarray slide, one can detect changes in mRNA expression levels, increases in DNA copy numbers and the location of transcription factor binding sites on a genomic scale. Having performed the experiments, the major challenge is to process large, noisy datasets in order to identify the specific array elements that are significantly differentially hybridized. This normally requires aggregating different, often incompatible programs into a multi-step pipeline. Here we present ExpressYourself, a fully integrated platform for processing microarray data. In completely automated fashion, it will correct the background array signal, normalize the Cy5 and Cy3 signals, score levels of differential hybridization, combine the results of replicate experiments, filter problematic regions of the array and assess the quality of individual and replicate experiments. ExpressYourself is designed with a highly modular architecture so various types of microarray analysis algorithms can readily be incorporated as they are developed; for example, the system currently implements several normalization methods, including those that simultaneously consider signal intensity and slide location. The processed data are presented using a web-based graphical interface to facilitate comparison with the original images of the array slides. In particular, Express Yourself is able to regenerate images of the original microarray after applying various steps of processing, which greatly facilities identification of position-specific artifacts. The program is freely available for use at http://bioinfo.mbb.yale.edu/expressyourself. PMID:12824348

  8. A probabilistic framework for microarray data analysis: fundamental probability models and statistical inference.

    PubMed

    Ogunnaike, Babatunde A; Gelmi, Claudio A; Edwards, Jeremy S

    2010-05-21

    Gene expression studies generate large quantities of data with the defining characteristic that the number of genes (whose expression profiles are to be determined) exceed the number of available replicates by several orders of magnitude. Standard spot-by-spot analysis still seeks to extract useful information for each gene on the basis of the number of available replicates, and thus plays to the weakness of microarrays. On the other hand, because of the data volume, treating the entire data set as an ensemble, and developing theoretical distributions for these ensembles provides a framework that plays instead to the strength of microarrays. We present theoretical results that under reasonable assumptions, the distribution of microarray intensities follows the Gamma model, with the biological interpretations of the model parameters emerging naturally. We subsequently establish that for each microarray data set, the fractional intensities can be represented as a mixture of Beta densities, and develop a procedure for using these results to draw statistical inference regarding differential gene expression. We illustrate the results with experimental data from gene expression studies on Deinococcus radiodurans following DNA damage using cDNA microarrays.

  9. A proposed metric for assessing the measurement quality of individual microarrays

    PubMed Central

    Kim, Kyoungmi; Page, Grier P; Beasley, T Mark; Barnes, Stephen; Scheirer, Katherine E; Allison, David B

    2006-01-01

    Background High-density microarray technology is increasingly applied to study gene expression levels on a large scale. Microarray experiments rely on several critical steps that may introduce error and uncertainty in analyses. These steps include mRNA sample extraction, amplification and labeling, hybridization, and scanning. In some cases this may be manifested as systematic spatial variation on the surface of microarray in which expression measurements within an individual array may vary as a function of geographic position on the array surface. Results We hypothesized that an index of the degree of spatiality of gene expression measurements associated with their physical geographic locations on an array could indicate the summary of the physical reliability of the microarray. We introduced a novel way to formulate this index using a statistical analysis tool. Our approach regressed gene expression intensity measurements on a polynomial response surface of the microarray's Cartesian coordinates. We demonstrated this method using a fixed model and presented results from real and simulated datasets. Conclusion We demonstrated the potential of such a quantitative metric for assessing the reliability of individual arrays. Moreover, we showed that this procedure can be incorporated into laboratory practice as a means to set quality control specifications and as a tool to determine whether an array has sufficient quality to be retained in terms of spatial correlation of gene expression measurements. PMID:16430768

  10. Assessing quality and normalization of microarrays: case studies using neurological genomic data.

    PubMed

    Hershey, A D; Burdine, D; Liu, C; Nick, T G; Gilbert, D L; Glauser, T A

    2008-07-01

    Genomic analysis using microarray tools has the potential benefit of enhancing our understanding of neurological diseases. The analysis of these data is complex due to the large amount of data generated. Many tools have been developed to assist with this, but standard methods of analysis of these tools have not been established. This study analyzed the sensitivity and specificity of different analytical methods for gene identification and presents a standardized approach. Affymetrix HG-U133 plus 2.0 microarray datasets from two neurological diseases - chronic migraine and new-onset epilepsy - were used as source data and methods of analysis for normalization of data and identification of gene changes were compared. Housekeeping genes were used to identify non-specific changes and gender related genes were used to identify specific changes. Initial normalization of data revealed that 5-10% of the microarray were potential outliers due to technical errors. Two separate methods of analysis (dChip and Bioconductor) identified the same microarray chips as outliers. For specificity and sensitivity testing, performing a per-gene normalization was found to be inferior to standard preprocessing procedures using robust multichip average analysis. Technical variation in microarray preprocessing may account for chip-to-chip and batch-to-batch variations and outliers need to be removed prior to analysis. Specificity and sensitivity of the final results are best achieved following this identification and removal with standard genomic analysis techniques. Future tools may benefit from the use of standard tools of measurement.

  11. ampliPHOX Colorimetric Detection on a DNA Microarray for Influenza

    PubMed Central

    Moulton, Kevin R.; Taylor, Amber W.; Rowlen, Kathy L.; Dawson, Erica D.

    2011-01-01

    DNA microarrays have emerged as a powerful tool for pathogen detection.1-5 For instance, many examples of the ability to type and subtype influenza virus have been demonstrated.6-11 The identification and subtyping of influenza on DNA microarrays has applications in both public health and the clinic for early detection, rapid intervention, and minimizing the impact of an influenza pandemic. Traditional fluorescence is currently the most commonly used microarray detection method. However, as microarray technology progresses towards clinical use,1 replacing expensive instrumentation with low cost detection technology exhibiting similar performance characteristics to fluorescence will make microarray assays more attractive and cost-effective. The ampliPHOX colorimetric detection technology is intended for research applications, and has a limit of detection within one order of magnitude of traditional fluorescence11, with a main advantage being an approximate ten-fold lower instrument cost compared to the confocal microarray scanners required for fluorescence microarray detection. Another advantage is the compact size of the instrument which allows for portability and flexibility, unlike traditional fluorescence instruments. Because the polymerization technology is not as inherently linear as fluorescence detection, however, it is best suited for lower density microarray applications in which a yes/no answer for the presence of a certain sequence is desired, such as for pathogen detection arrays. Currently the maximum spot density compatible with ampliPHOX detection is ˜1800 spots/array. Because of the spot density limitations, higher density microarrays are not suitable for ampliPHOX detection. Here, we present ampliPHOX colorimetric detection technology as a method of signal amplification on a low density microarray developed for the detection and characterization of influenza viruses (FluChip). Although this protocol uses the FluChip (a DNA microarray) as one

  12. The North Coast Cholesterol Check Campaign. Results of the first three years of a large-scale public screening programme.

    PubMed

    van Beurden, E K; James, R; Henrikson, D; Tyler, C; Christian, J

    1991-03-18

    Although cardiovascular disease (CVD) mortality has been declining, CVD is still the major cause of death in Australia and an elevated blood cholesterol level is considered a major contributor. Large-scale community-based screening programmes in other countries have demonstrated that a population approach can be effective in reducing cholesterol levels and the risk of CVD. The North Coast Cholesterol Check Campaign is the largest community-based cholesterol intervention programme in Australia. Since its inception in 1987, 13% of the Region's adult population (over 29,000 persons) have been screened. About half had elevated blood cholesterol levels (greater than or equal to 5.5 mmol/L) and were given dietary counselling to reduce fat intake. Mean blood cholesterol levels were significantly reduced between initial screening and follow-up in all three years. Reductions, after correction for regression, were 8%, 6% and 10%, respectively, in 1987, 1988 and 1989. There was also a consistent and significant 1.5% to 2% reduction in weight. All age/sex cohorts above age 35 were well represented each year although self-referral did bias both initial and follow-up samples towards women and the aged. Nevertheless, the proportion of men and men in their middle age increased during the three years. The proportion of participants with elevated cholesterol levels increased in each successive year while the proportion of participants who complied with referrals to visit their general practitioner and with requests to return for follow-up decreased. Over half of the North Coast adult population has now had a cholesterol test. The rate of increase in testing since the inception of the Campaign has been approximately four times the national rate. North Coast general practitioners have played a major role by catering for the increased community demand for cholesterol testing and by providing an effective referral service for the Campaign. Community-based screening programmes in

  13. Peptide microarray patterning for controlling and monitoring cell growth.

    PubMed

    Lin, Edith; Sikand, Adhirath; Wickware, Jessica; Hao, Yubin; Derda, Ratmir

    2016-04-01

    The fate of cells is influenced by their microenvironment and many cell types undergo differentiation when stimulated by extracellular cues, such as soluble growth factors and the insoluble extracellular matrix (ECM). Stimulating differentiation by insoluble or "immobilized" cues is a particularly attractive method because it allows for the induction of differentiation in a spatially-defined cohort of cells within a larger subpopulation. To improve the design of de novo screening of such insoluble factors, we describe a methodology for producing high-density peptide microarrays suitable for extended cell culture and fluorescence microscopy. As a model, we used a murine mammary gland cell line (NMuMG) that undergoes epithelial to mesenchymal transition (EMT) in response to soluble transforming growth factor beta (TGF-β) and surface-immobilized peptides that target TGF-β receptors (TGFβRI/II). We repurposed a well-established DNA microarray printing technique to produce arrays of micropatterned surfaces that displayed TGFβRI/II-binding peptides and integrin binding peptides. Upon long-term culture on these arrays, only NMuMG cells residing on EMT-stimulating areas exhibited growth arrest and decreased E-cadherin expression. We believe that the methodology created in this report will aid the development of peptide-decorated surfaces that can locally stimulate defined cell surface receptors and control EMT and other well-characterized differentiation events. Scope of work: This manuscript aims to accelerate the development of instructive biomaterials decorated with specific ligands that target cell-surface receptors and induce specific differentiation of cells upon contact. These materials can be used for practical applications, such as fabricating synthetic materials for large scale, stem cell culture, or investigating differentiation and asymmetric division in stem cells. Specifically, in this manuscript, we repurposed a DNA microarray printer to produce

  14. Collective response to public health emergencies and large-scale disasters: putting hospitals at the core of community resilience.

    PubMed

    Paturas, James L; Smith, Deborah; Smith, Stewart; Albanese, Joseph

    2010-07-01

    Healthcare organisations are a critical part of a community's resilience and play a prominent role as the backbone of medical response to natural and manmade disasters. The importance of healthcare organisations, in particular hospitals, to remain operational extends beyond the necessity to sustain uninterrupted medical services for the community, in the aftermath of a large-scale disaster. Hospitals are viewed as safe havens where affected individuals go for shelter, food, water and psychosocial assistance, as well as to obtain information about missing family members or learn of impending dangers related to the incident. The ability of hospitals to respond effectively to high-consequence incidents producing a massive arrival of patients that disrupt daily operations requires surge capacity and capability. The activation of hospital emergency support functions provides an approach by which hospitals manage a short-term shortfall of hospital personnel through the reallocation of hospital employees, thereby obviating the reliance on external qualified volunteers for surge capacity and capability. Recent revisions to the Joint Commission's hospital emergency preparedness standard have impelled healthcare facilities to participate actively in community-wide planning, rather than confining planning exclusively to a single healthcare facility, in order to harmonise disaster management strategies and effectively coordinate the allocation of community resources and expertise across all local response agencies.

  15. Public Transit Equity Analysis at Metropolitan and Local Scales: A Focus on Nine Large Cities in the US

    PubMed Central

    Griffin, Greg Phillip; Sener, Ipek Nese

    2016-01-01

    Recent studies on transit service through an equity lens have captured broad trends from the literature and national-level data or analyzed disaggregate data at the local level. This study integrates these methods by employing a geostatistical analysis of new transit access and income data compilations from the Environmental Protection Agency. By using a national data set, this study demonstrates a method for income-based transit equity analysis and provides results spanning nine large auto-oriented cities in the US. Results demonstrate variability among cities’ transit services to low-income populations, with differing results when viewed at the regional and local levels. Regional-level analysis of transit service hides significant variation through spatial averaging, whereas the new data employed in this study demonstrates a block-group scale equity analysis that can be used on a national-scale data set. The methods used can be adapted for evaluation of transit and other modes’ transportation service in areas to evaluate equity at the regional level and at the neighborhood scale while controlling for spatial autocorrelation. Transit service equity planning can be enhanced by employing local Moran’s I to improve local analysis. PMID:28638236

  16. Public Transit Equity Analysis at Metropolitan and Local Scales: A Focus on Nine Large Cities in the US.

    PubMed

    Griffin, Greg Phillip; Sener, Ipek Nese

    2016-01-01

    Recent studies on transit service through an equity lens have captured broad trends from the literature and national-level data or analyzed disaggregate data at the local level. This study integrates these methods by employing a geostatistical analysis of new transit access and income data compilations from the Environmental Protection Agency. By using a national data set, this study demonstrates a method for income-based transit equity analysis and provides results spanning nine large auto-oriented cities in the US. Results demonstrate variability among cities' transit services to low-income populations, with differing results when viewed at the regional and local levels. Regional-level analysis of transit service hides significant variation through spatial averaging, whereas the new data employed in this study demonstrates a block-group scale equity analysis that can be used on a national-scale data set. The methods used can be adapted for evaluation of transit and other modes' transportation service in areas to evaluate equity at the regional level and at the neighborhood scale while controlling for spatial autocorrelation. Transit service equity planning can be enhanced by employing local Moran's I to improve local analysis.

  17. Detection of protozoan and bacterial pathogens of public health importance in faeces of Corvus spp. (large-billed crow).

    PubMed

    Lee, H Y; Stephen, A; Sushela, D; Mala, M

    2008-08-01

    Parasites and bacteria are reported in the faeces of birds in the current study. Fresh faecal samples of the large-billed crow (Corvus spp.) were collected from the study site at Bangsar, an urban setting in Kuala Lumpur, Malaysia. These samples were transported to laboratory and analysed for parasites and bacteria. Pre-prepared XLD agar plates were used for culturing the bacteria in the laboratory. Using the API 20ETM Test Strips, 9 different species of bacteria were identified belonging to the family Enterobacteriacea. They were Citrobacter freundii, Enterobacter cloacae, Proteus mirabilis, Klebsiella pneumoniae, Kluyvera ascorbata, Salmonella arizonae, Salmonella typhi, Shigella flexneri and Shigella sonnei. The protozoan parasites detected include Cryptosporidium spp., Cyclospora spp., Blastocystis spp., and Capillaria hepatica and Ascaris lumbricoidus ova. Environmental air samples collected on agar plates using an air sampler in the area only produced fungal colonies. Some of these pathogens found in the crows are of zoonotic importance, especially Cryptosporidium, Blastocystis, Cyclopsora, Salmonella, Shigella and Kluyvera. The finding of Kluyvera spp. in crows in our current study highlights its zoonotic potential in an urban setting.

  18. Multi-gene detection and identification of mosquito-borne RNA viruses using an oligonucleotide microarray.

    PubMed

    Grubaugh, Nathan D; McMenamy, Scott S; Turell, Michael J; Lee, John S

    2013-01-01

    Arthropod-borne viruses are important emerging pathogens world-wide. Viruses transmitted by mosquitoes, such as dengue, yellow fever, and Japanese encephalitis viruses, infect hundreds of millions of people and animals each year. Global surveillance of these viruses in mosquito vectors using molecular based assays is critical for prevention and control of the associated diseases. Here, we report an oligonucleotide DNA microarray design, termed ArboChip5.1, for multi-gene detection and identification of mosquito-borne RNA viruses from the genera Flavivirus (family Flaviviridae), Alphavirus (Togaviridae), Orthobunyavirus (Bunyaviridae), and Phlebovirus (Bunyaviridae). The assay utilizes targeted PCR amplification of three genes from each virus genus for electrochemical detection on a portable, field-tested microarray platform. Fifty-two viruses propagated in cell-culture were used to evaluate the specificity of the PCR primer sets and the ArboChip5.1 microarray capture probes. The microarray detected all of the tested viruses and differentiated between many closely related viruses such as members of the dengue, Japanese encephalitis, and Semliki Forest virus clades. Laboratory infected mosquitoes were used to simulate field samples and to determine the limits of detection. Additionally, we identified dengue virus type 3, Japanese encephalitis virus, Tembusu virus, Culex flavivirus, and a Quang Binh-like virus from mosquitoes collected in Thailand in 2011 and 2012. We demonstrated that the described assay can be utilized in a comprehensive field surveillance program by the broad-range amplification and specific identification of arboviruses from infected mosquitoes. Furthermore, the microarray platform can be deployed in the field and viral RNA extraction to data analysis can occur in as little as 12 h. The information derived from the ArboChip5.1 microarray can help to establish public health priorities, detect disease outbreaks, and evaluate control programs.

  19. ArrayQuest: a web resource for the analysis of DNA microarray data

    PubMed Central

    Argraves, Gary L; Jani, Saurin; Barth, Jeremy L; Argraves, W Scott

    2005-01-01

    Background Numerous microarray analysis programs have been created through the efforts of Open Source software development projects. Providing browser-based interfaces that allow these programs to be executed over the Internet enhances the applicability and utility of these analytic software tools. Results Here we present ArrayQuest, a web-based DNA microarray analysis process controller. Key features of ArrayQuest are that (1) it is capable of executing numerous analysis programs such as those written in R, BioPerl and C++; (2) new analysis programs can be added to ArrayQuest Methods Library at the request of users or developers; (3) input DNA microarray data can be selected from public databases (i.e., the Medical University of South Carolina (MUSC) DNA Microarray Database or Gene Expression Omnibus (GEO)) or it can be uploaded to the ArrayQuest center-point web server into a password-protected area; and (4) analysis jobs are distributed across computers configured in a backend cluster. To demonstrate the utility of ArrayQuest we have populated the methods library with methods for analysis of Affymetrix DNA microarray data. Conclusion ArrayQuest enables browser-based implementation of DNA microarray data analysis programs that can be executed on a Linux-based platform. Importantly, ArrayQuest is a platform that will facilitate the distribution and implementation of new analysis algorithms and is therefore of use to both developers of analysis applications as well as users. ArrayQuest is freely available for use at . PMID:16321157

  20. ArrayQuest: a web resource for the analysis of DNA microarray data.

    PubMed

    Argraves, Gary L; Jani, Saurin; Barth, Jeremy L; Argraves, W Scott

    2005-12-01

    Numerous microarray analysis programs have been created through the efforts of Open Source software development projects. Providing browser-based interfaces that allow these programs to be executed over the Internet enhances the applicability and utility of these analytic software tools. Here we present ArrayQuest, a web-based DNA microarray analysis process controller. Key features of ArrayQuest are that (1) it is capable of executing numerous analysis programs such as those written in R, BioPerl and C++; (2) new analysis programs can be added to ArrayQuest Methods Library at the request of users or developers; (3) input DNA microarray data can be selected from public databases (i.e., the Medical University of South Carolina (MUSC) DNA Microarray Database or Gene Expression Omnibus (GEO)) or it can be uploaded to the ArrayQuest center-point web server into a password-protected area; and (4) analysis jobs are distributed across computers configured in a backend cluster. To demonstrate the utility of ArrayQuest we have populated the methods library with methods for analysis of Affymetrix DNA microarray data. ArrayQuest enables browser-based implementation of DNA microarray data analysis programs that can be executed on a Linux-based platform. Importantly, ArrayQuest is a platform that will facilitate the distribution and implementation of new analysis algorithms and is therefore of use to both developers of analysis applications as well as users. ArrayQuest is freely available for use at http://proteogenomics.musc.edu/arrayquest.html.

  1. Multi-Gene Detection and Identification of Mosquito-Borne RNA Viruses Using an Oligonucleotide Microarray

    PubMed Central

    Grubaugh, Nathan D.; McMenamy, Scott S.; Turell, Michael J.; Lee, John S.

    2013-01-01

    Background Arthropod-borne viruses are important emerging pathogens world-wide. Viruses transmitted by mosquitoes, such as dengue, yellow fever, and Japanese encephalitis viruses, infect hundreds of millions of people and animals each year. Global surveillance of these viruses in mosquito vectors using molecular based assays is critical for prevention and control of the associated diseases. Here, we report an oligonucleotide DNA microarray design, termed ArboChip5.1, for multi-gene detection and identification of mosquito-borne RNA viruses from the genera Flavivirus (family Flaviviridae), Alphavirus (Togaviridae), Orthobunyavirus (Bunyaviridae), and Phlebovirus (Bunyaviridae). Methodology/Principal Findings The assay utilizes targeted PCR amplification of three genes from each virus genus for electrochemical detection on a portable, field-tested microarray platform. Fifty-two viruses propagated in cell-culture were used to evaluate the specificity of the PCR primer sets and the ArboChip5.1 microarray capture probes. The microarray detected all of the tested viruses and differentiated between many closely related viruses such as members of the dengue, Japanese encephalitis, and Semliki Forest virus clades. Laboratory infected mosquitoes were used to simulate field samples and to determine the limits of detection. Additionally, we identified dengue virus type 3, Japanese encephalitis virus, Tembusu virus, Culex flavivirus, and a Quang Binh-like virus from mosquitoes collected in Thailand in 2011 and 2012. Conclusions/Significance We demonstrated that the described assay can be utilized in a comprehensive field surveillance program by the broad-range amplification and specific identification of arboviruses from infected mosquitoes. Furthermore, the microarray platform can be deployed in the field and viral RNA extraction to data analysis can occur in as little as 12 h. The information derived from the ArboChip5.1 microarray can help to establish public health

  2. Improving FoRe: A New Inlet Design for Filtering Samples through Individual Microarray Spots.

    PubMed

    de Lange, Victoria; Habegger, Marco; Schmidt, Marco; Vörös, János

    2017-03-24

    In this publication we present an improvement to our previously introduced vertical flow microarray, the FoRe array, which capitalizes on the fusion of immunofiltration and densely packed micron test sites. Filtering samples through individual microarray spots allows us to rapidly analyze dilute samples with high-throughput and high signal-to-noise. Unlike other flowthrough microarrays, in the FoRe design samples are injected into micron channels and sequentially exposed to different targets. This arrangement makes it possible to increase the sensitivity of the microarray by simply increasing the sample volume or to rapidly reconcentrate samples after preprocessing steps dilute the analyte. Here we present a new inlet system which allows us to increase the analyzed sample volume without compromising the micron spot size and dense layout. We combined this with a model assay to demonstrate that the device is sensitive to the amount of antigen, and as a result, sample volume directly correlates to sensitivity. We introduced a simple technique for analysis of blood, which previously clogged the nanometer-sized pores, requiring only microliter volumes expected from an infant heel prick. A drop of blood is mixed with buffer to separate the plasma before reconcentrating the sample on the microarray spot. We demonstrated the success of this procedure by spiking TNF-α into blood and achieved a limit of detection of 18 pM. Compared to traditional protein microarrays, the FoRe array is still inexpensive, customizable, and simple to use, and thanks to these improvements has a broad range of applications from small animal studies to environmental monitoring.

  3. Viral diagnosis in Indian livestock using customized microarray chips.

    PubMed

    Yadav, Brijesh S; Pokhriyal, Mayank; Ratta, Barkha; Kumar, Ajay; Saxena, Meeta; Sharma, Bhaskar

    2015-01-01

    Viral diagnosis in Indian livestock using customized microarray chips is gaining momentum in recent years. Hence, it is possible to design customized microarray chip for viruses infecting livestock in India. Customized microarray chips identified Bovine herpes virus-1 (BHV-1), Canine Adeno Virus-1 (CAV-1), and Canine Parvo Virus-2 (CPV-2) in clinical samples. Microarray identified specific probes were further confirmed using RT-PCR in all clinical and known samples. Therefore, the application of microarray chips during viral disease outbreaks in Indian livestock is possible where conventional methods are unsuitable. It should be noted that customized application requires a detailed cost efficiency calculation.

  4. Integrated analysis of microarray data and gene function information.

    PubMed

    Cui, Yan; Zhou, Mi; Wong, Wing Hung

    2004-01-01

    Microarray data should be interpreted in the context of existing biological knowledge. Here we present integrated analysis of microarray data and gene function classification data using homogeneity analysis. Homogeneity analysis is a graphical multivariate statistical method for analyzing categorical data. It converts categorical data into graphical display. By simultaneously quantifying the microarray-derived gene groups and gene function categories, it captures the complex relations between biological information derived from microarray data and the existing knowledge about the gene function. Thus, homogeneity analysis provides a mathematical framework for integrating the analysis of microarray data and the existing biological knowledge.

  5. Viral diagnosis in Indian livestock using customized microarray chips

    PubMed Central

    Yadav, Brijesh S; Pokhriyal, Mayank; Ratta, Barkha; Kumar, Ajay; Saxena, Meeta; Sharma, Bhaskar

    2015-01-01

    Viral diagnosis in Indian livestock using customized microarray chips is gaining momentum in recent years. Hence, it is possible to design customized microarray chip for viruses infecting livestock in India. Customized microarray chips identified Bovine herpes virus-1 (BHV-1), Canine Adeno Virus-1 (CAV-1), and Canine Parvo Virus-2 (CPV-2) in clinical samples. Microarray identified specific probes were further confirmed using RT-PCR in all clinical and known samples. Therefore, the application of microarray chips during viral disease outbreaks in Indian livestock is possible where conventional methods are unsuitable. It should be noted that customized application requires a detailed cost efficiency calculation. PMID:26912948

  6. STIDP: A U.S. Department of Homeland Security program for countering explosives attacks at large public events and mass transit facilities

    NASA Astrophysics Data System (ADS)

    Knudson, Christa K.; Kemp, Michael C.; Lombardo, Nicholas J.

    2009-05-01

    The U.S. Department of Homeland Security's Standoff Technology Integration and Demonstration Program is designed to accelerate the development and integration of technologies, concepts of operations, and training to defeat explosives attacks at large public events and mass transit facilities. The program will address threats posed by suicide bombers, vehicle-borne improvised explosive devices, and leave-behind bombs. The program is focused on developing and testing explosives countermeasure architectures using commercial off-the-shelf and near-commercial standoff and remotely operated detection technologies in prototypic operational environments. An important part of the program is the integration of multiple technologies and systems to protect against a wider range of threats, improve countermeasure performance, increase the distance from the venue at which screening is conducted, and reduce staffing requirements. The program will routinely conduct tests in public venues involving successively more advanced technology, higher levels of system integration, and more complex scenarios. This paper describes the initial field test of an integrated countermeasure system that included infrared, millimeter-wave, and video analytics technologies for detecting person-borne improvised explosive devices at a public arena. The test results are being used to develop a concept for the next generation of integrated countermeasures, to refine technical and operational requirements for architectures and technologies, and engage industry and academia in solution development.

  7. Systematic interpretation of microarray data using experiment annotations

    PubMed Central

    Fellenberg, Kurt; Busold, Christian H; Witt, Olaf; Bauer, Andrea; Beckmann, Boris; Hauser, Nicole C; Frohme, Marcus; Winter, Stefan; Dippon, Jürgen; Hoheisel, Jörg D

    2006-01-01

    Background Up to now, microarray data are mostly assessed in context with only one or few parameters characterizing the experimental conditions under study. More explicit experiment annotations, however, are highly useful for interpreting microarray data, when available in a statistically accessible format. Results We provide means to preprocess these additional data, and to extract relevant traits corresponding to the transcription patterns under study. We found correspondence analysis particularly well-suited for mapping such extracted traits. It visualizes associations both among and between the traits, the hereby annotated experiments, and the genes, revealing how they are all interrelated. Here, we apply our methods to the systematic interpretation of radioactive (single channel) and two-channel data, stemming from model organisms such as yeast and drosophila up to complex human cancer samples. Inclusion of technical parameters allows for identification of artifacts and flaws in experimental design. Conclusion Biological and clinical traits can act as landmarks in transcription space, systematically mapping the variance of large datasets from the predominant changes down toward intricate details. PMID:17181856

  8. Structural analysis of hepatitis C RNA genome using DNA microarrays

    PubMed Central

    Martell, María; Briones, Carlos; de Vicente, Aránzazu; Piron, María; Esteban, Juan I.; Esteban, Rafael; Guardia, Jaime; Gómez, Jordi

    2004-01-01

    Many studies have tried to identify specific nucleotide sequences in the quasispecies of hepatitis C virus (HCV) that determine resistance or sensitivity to interferon (IFN) therapy, unfortunately without conclusive results. Although viral proteins represent the most evident phenotype of the virus, genomic RNA sequences determine secondary and tertiary structures which are also part of the viral phenotype and can be involved in important biological roles. In this work, a method of RNA structure analysis has been developed based on the hybridization of labelled HCV transcripts to microarrays of complementary DNA oligonucleotides. Hybridizations were carried out at non-denaturing conditions, using appropriate temperature and buffer composition to allow binding to the immobilized probes of the RNA transcript without disturbing its secondary/tertiary structural motifs. Oligonucleotides printed onto the microarray covered the entire 5′ non-coding region (5′NCR), the first three-quarters of the core region, the E2–NS2 junction and the first 400 nt of the NS3 region. We document the use of this methodology to analyse the structural degree of a large region of HCV genomic RNA in two genotypes associated with different responses to IFN treatment. The results reported here show different structural degree along the genome regions analysed, and differential hybridization patterns for distinct genotypes in NS2 and NS3 HCV regions. PMID:15247323

  9. Biocompatible Hydrogels for Microarray Cell Printing and Encapsulation

    PubMed Central

    Datar, Akshata; Joshi, Pranav; Lee, Moo-Yeal

    2015-01-01

    Conventional drug screening processes are a time-consuming and expensive endeavor, but highly rewarding when they are successful. To identify promising lead compounds, millions of compounds are traditionally screened against therapeutic targets on human cells grown on the surface of 96-wells. These two-dimensional (2D) cell monolayers are physiologically irrelevant, thus, often providing false-positive or false-negative results, when compared to cells grown in three-dimensional (3D) structures such as hydrogel droplets. However, 3D cell culture systems are not easily amenable to high-throughput screening (HTS), thus inherently low throughput, and requiring relatively large volume for cell-based assays. In addition, it is difficult to control cellular microenvironments and hard to obtain reliable cell images due to focus position and transparency issues. To overcome these problems, miniaturized 3D cell cultures in hydrogels were developed via cell printing techniques where cell spots in hydrogels can be arrayed on the surface of glass slides or plastic chips by microarray spotters and cultured in growth media to form cells encapsulated 3D droplets for various cell-based assays. These approaches can dramatically reduce assay volume, provide accurate control over cellular microenvironments, and allow us to obtain clear 3D cell images for high-content imaging (HCI). In this review, several hydrogels that are compatible to microarray printing robots are discussed for miniaturized 3D cell cultures. PMID:26516921

  10. Biocompatible Hydrogels for Microarray Cell Printing and Encapsulation.

    PubMed

    Datar, Akshata; Joshi, Pranav; Lee, Moo-Yeal

    2015-10-26

    Conventional drug screening processes are a time-consuming and expensive endeavor, but highly rewarding when they are successful. To identify promising lead compounds, millions of compounds are traditionally screened against therapeutic targets on human cells grown on the surface of 96-wells. These two-dimensional (2D) cell monolayers are physiologically irrelevant, thus, often providing false-positive or false-negative results, when compared to cells grown in three-dimensional (3D) structures such as hydrogel droplets. However, 3D cell culture systems are not easily amenable to high-throughput screening (HTS), thus inherently low throughput, and requiring relatively large volume for cell-based assays. In addition, it is difficult to control cellular microenvironments and hard to obtain reliable cell images due to focus position and transparency issues. To overcome these problems, miniaturized 3D cell cultures in hydrogels were developed via cell printing techniques where cell spots in hydrogels can be arrayed on the surface of glass slides or plastic chips by microarray spotters and cultured in growth media to form cells encapsulated 3D droplets for various cell-based assays. These approaches can dramatically reduce assay volume, provide accurate control over cellular microenvironments, and allow us to obtain clear 3D cell images for high-content imaging (HCI). In this review, several hydrogels that are compatible to microarray printing robots are discussed for miniaturized 3D cell cultures.

  11. Blood Signature of Pre-Heart Failure: A Microarrays Study

    PubMed Central

    Smih, Fatima; Desmoulin, Franck; Berry, Matthieu; Turkieh, Annie; Harmancey, Romain; Iacovoni, Jason; Trouillet, Charlotte; Delmas, Clement; Pathak, Atul; Lairez, Olivier; Koukoui, François; Massabuau, Pierre; Ferrieres, Jean; Galinier, Michel; Rouet, Philippe

    2011-01-01

    Background The preclinical stage of systolic heart failure (HF), known as asymptomatic left ventricular dysfunction (ALVD), is diagnosed only by echocardiography, frequent in the general population and leads to a high risk of developing severe HF. Large scale screening for ALVD is a difficult task and represents a major unmet clinical challenge that requires the determination of ALVD biomarkers. Methodology/Principal Findings 294 individuals were screened by echocardiography. We identified 9 ALVD cases out of 128 subjects with cardiovascular risk factors. White blood cell gene expression profiling was performed using pangenomic microarrays. Data were analyzed using principal component analysis (PCA) and Significant Analysis of Microarrays (SAM). To build an ALVD classifier model, we used the nearest centroid classification method (NCCM) with the ClaNC software package. Classification performance was determined using the leave-one-out cross-validation method. Blood transcriptome analysis provided a specific molecular signature for ALVD which defined a model based on 7 genes capable of discriminating ALVD cases. Analysis of an ALVD patients validation group demonstrated that these genes are accurate diagnostic predictors for ALVD with 87% accuracy and 100% precision. Furthermore, Receiver Operating Characteristic curves of expression levels confirmed that 6 out of 7 genes discriminate for left ventricular dysfunction classification. Conclusions/Significance These targets could serve to enhance the ability to efficiently detect ALVD by general care practitioners to facilitate preemptive initiation of medical treatment preventing the development of HF. PMID:21731613

  12. Public Attitudes toward Consent and Data Sharing in Biobank Research: A Large Multi-site Experimental Survey in the US.

    PubMed

    Sanderson, Saskia C; Brothers, Kyle B; Mercaldo, Nathaniel D; Clayton, Ellen Wright; Antommaria, Armand H Matheny; Aufox, Sharon A; Brilliant, Murray H; Campos, Diego; Carrell, David S; Connolly, John; Conway, Pat; Fullerton, Stephanie M; Garrison, Nanibaa' A; Horowitz, Carol R; Jarvik, Gail P; Kaufman, David; Kitchner, Terrie E; Li, Rongling; Ludman, Evette J; McCarty, Catherine A; McCormick, Jennifer B; McManus, Valerie D; Myers, Melanie F; Scrol, Aaron; Williams, Janet L; Shrubsole, Martha J; Schildcrout, Jonathan S; Smith, Maureen E; Holm, Ingrid A

    2017-03-02

    Individuals participating in biobanks and other large research projects are increasingly asked to provide broad consent for open-ended research use and widespread sharing of their biosamples and data. We assessed willingness to participate in a biobank using different consent and data sharing models, hypothesizing that willingness would be higher under more restrictive scenarios. Perceived benefits, concerns, and information needs were also assessed. In this experimental survey, individuals from 11 US healthcare systems in the Electronic Medical Records and Genomics (eMERGE) Network were randomly allocated to one of three hypothetical scenarios: tiered consent and controlled data sharing; broad consent and controlled data sharing; or broad consent and open data sharing. Of 82,328 eligible individuals, exactly 13,000 (15.8%) completed the survey. Overall, 66% (95% CI: 63%-69%) of population-weighted respondents stated they would be willing to participate in a biobank; willingness and attitudes did not differ between respondents in the three scenarios. Willingness to participate was associated with self-identified white race, higher educational attainment, lower religiosity, perceiving more research benefits, fewer concerns, and fewer information needs. Most (86%, CI: 84%-87%) participants would want to know what would happen if a researcher misused their health information; fewer (51%, CI: 47%-55%) would worry about their privacy. The concern that the use of broad consent and open data sharing could adversely affect participant recruitment is not supported by these findings. Addressing potential participants' concerns and information needs and building trust and relationships with communities may increase acceptance of broad consent and wide data sharing in biobank research.

  13. Non-pharmaceutical interventions during an outbreak of 2009 pandemic influenza A (H1N1) virus infection at a large public university, April-May 2009.

    PubMed

    Mitchell, Tarissa; Dee, Deborah L; Phares, Christina R; Lipman, Harvey B; Gould, L Hannah; Kutty, Preeta; Desai, Mitesh; Guh, Alice; Iuliano, A Danielle; Silverman, Paul; Siebold, Joseph; Armstrong, Gregory L; Swerdlow, David L; Massoudi, Mehran S; Fishbein, Daniel B

    2011-01-01

    Nonpharmaceutical interventions (NPIs), such as home isolation, social distancing, and infection control measures, are recommended by public health agencies as strategies to mitigate transmission during influenza pandemics. However, NPI implementation has rarely been studied in large populations. During an outbreak of 2009 Pandemic Influenza A (H1N1) virus infection at a large public university in April 2009, an online survey was conducted among students, faculty, and staff to assess knowledge of and adherence to university-recommended NPI. Although 3924 (65%) of 6049 student respondents and 1057 (74%) of 1401 faculty respondents reported increased use of self-protective NPI, such as hand washing, only 27 (6.4%) of 423 students and 5 (8.6%) of 58 faculty with acute respiratory infection (ARI) reported staying home while ill. Nearly one-half (46%) of student respondents, including 44.7% of those with ARI, attended social events. Results indicate a need for efforts to increase compliance with home isolation and social distancing measures.

  14. Molecular diagnosis and prognosis with DNA microarrays.

    PubMed

    Wiltgen, Marco; Tilz, Gernot P

    2011-05-01

    Microarray analysis makes it possible to determine thousands of gene expression values simultaneously. Changes in gene expression, as a response to diseases, can be detected allowing a better understanding and differentiation of diseases at a molecular level. By comparing different kinds of tissue, for example healthy tissue and cancer tissue, the microarray analysis indicates induced gene activity, repressed gene activity or when there is no change in the gene activity level. Fundamental patterns in gene expression are extracted by several clustering and machine learning algorithms. Certain kinds of cancer can be divided into subtypes, with different clinical outcomes, by their specific gene expression patterns. This enables a better diagnosis and tailoring of individual patient treatments.

  15. Detecting outlier samples in microarray data.

    PubMed

    Shieh, Albert D; Hung, Yeung Sam

    2009-01-01

    In this paper, we address the problem of detecting outlier samples with highly different expression patterns in microarray data. Although outliers are not common, they appear even in widely used benchmark data sets and can negatively affect microarray data analysis. It is important to identify outliers in order to explore underlying experimental or biological problems and remove erroneous data. We propose an outlier detection method based on principal component analysis (PCA) and robust estimation of Mahalanobis distances that is fully automatic. We demonstrate that our outlier detection method identifies biologically significant outliers with high accuracy and that outlier removal improves the prediction accuracy of classifiers. Our outlier detection method is closely related to existing robust PCA methods, so we compare our outlier detection method to a prominent robust PCA method.

  16. DNA microarrays: an introduction to the technology.

    PubMed

    Bilitewski, Ursula

    2009-01-01

    DNA microarrays allow the comprehensive genetic analysis of an organism or a sample. They are based on probes, which are immobilized in an ordered two-dimensional pattern on substrates, such as nylon membranes or glass slides. Probes are either spotted cDNAs or oligonucleotides and are designed to be specific for an organism, a gene, a genetic variant (mutation or polymorphism), or intergenic regions. Thus, they can be used for example for genotyping, expression analysis, or studies of protein-DNA interactions, and in the biomedical field they allow the detection of pathogens, antibiotic resistances, gene mutations and polymorphisms, and pathogenic states and can guide therapy. Microarrays, which cover the whole genome of an organism, are as well available as those which are focussed on genes related to a certain diagnostic application.

  17. Plasmonically amplified fluorescence bioassay with microarray format

    NASA Astrophysics Data System (ADS)

    Gogalic, S.; Hageneder, S.; Ctortecka, C.; Bauch, M.; Khan, I.; Preininger, Claudia; Sauer, U.; Dostalek, J.

    2015-05-01

    Plasmonic amplification of fluorescence signal in bioassays with microarray detection format is reported. A crossed relief diffraction grating was designed to couple an excitation laser beam to surface plasmons at the wavelength overlapping with the absorption and emission bands of fluorophore Dy647 that was used as a label. The surface of periodically corrugated sensor chip was coated with surface plasmon-supporting gold layer and a thin SU8 polymer film carrying epoxy groups. These groups were employed for the covalent immobilization of capture antibodies at arrays of spots. The plasmonic amplification of fluorescence signal on the developed microarray chip was tested by using interleukin 8 sandwich immunoassay. The readout was performed ex situ after drying the chip by using a commercial scanner with high numerical aperture collecting lens. Obtained results reveal the enhancement of fluorescence signal by a factor of 5 when compared to a regular glass chip.

  18. Respiratory Tularemia: Francisella Tularensis and Microarray Probe Designing

    PubMed Central

    Ranjbar, Reza; Behzadi, Payam; Mammina, Caterina

    2016-01-01

    Background: Francisella tularensis (F. tularensis) is the etiological microorganism for tularemia. There are different forms of tularemia such as respiratory tularemia. Respiratory tularemia is the most severe form of tularemia with a high rate of mortality; if not treated. Therefore, traditional microbiological tools and Polymerase Chain Reaction (PCR) are not useful for a rapid, reliable, accurate, sensitive and specific diagnosis. But, DNA microarray technology does. DNA microarray technology needs to appropriate microarray probe designing. Objective: The main goal of this original article was to design suitable long oligo microarray probes for detection and identification of F. tularensis. Method: For performing this research, the complete genomes of F. tularensis subsp. tularensis FSC198, F. tularensis subsp. holarctica LVS, F. tularensis subsp. mediasiatica, F. tularensis subsp. novicida (F. novicida U112), and F. philomiragia subsp. philomiragia ATCC 25017 were studied via NCBI BLAST tool, GView and PanSeq Servers and finally the microarray probes were produced and processed via AlleleID 7.7 software and Oligoanalyzer tool, respectively. Results: In this in silico investigation, a number of long oligo microarray probes were designed for detecting and identifying F. tularensis. Among these probes, 15 probes were recognized as the best candidates for microarray chip designing. Conclusion: Calibrated microarray probes reduce the biasis of DNA microarray technology as an advanced, rapid, accurate and cost-effective molecular diagnostic tool with high specificity and sensitivity. Professional microarray probe designing provides us with much more facility and flexibility regarding preparation of a microarray diagnostic chip. PMID:28077973

  19. Respiratory Tularemia: Francisella Tularensis and Microarray Probe Designing.

    PubMed

    Ranjbar, Reza; Behzadi, Payam; Mammina, Caterina

    2016-01-01

    Francisella tularensis (F. tularensis) is the etiological microorganism for tularemia. There are different forms of tularemia such as respiratory tularemia. Respiratory tularemia is the most severe form of tularemia with a high rate of mortality; if not treated. Therefore, traditional microbiological tools and Polymerase Chain Reaction (PCR) are not useful for a rapid, reliable, accurate, sensitive and specific diagnosis. But, DNA microarray technology does. DNA microarray technology needs to appropriate microarray probe designing. The main goal of this original article was to design suitable long oligo microarray probes for detection and identification of F. tularensis. For performing this research, the complete genomes of F. tularensis subsp. tularensis FSC198, F. tularensis subsp. holarctica LVS, F. tularensis subsp. mediasiatica, F. tularensis subsp. novicida (F. novicida U112), and F. philomiragia subsp. philomiragia ATCC 25017 were studied via NCBI BLAST tool, GView and PanSeq Servers and finally the microarray probes were produced and processed via AlleleID 7.7 software and Oligoanalyzer tool, respectively. In this in silico investigation, a number of long oligo microarray probes were designed for detecting and identifying F. tularensis. Among these probes, 15 probes were recognized as the best candidates for microarray chip designing. Calibrated microarray probes reduce the biasis of DNA microarray technology as an advanced, rapid, accurate and cost-effective molecular diagnostic tool with high specificity and sensitivity. Professional microarray probe designing provides us with much more facility and flexibility regarding preparation of a microarray diagnostic chip.

  20. Development of a Physical Model-Based Algorithm for the Detection of Single-Nucleotide Substitutions by Using Tiling Microarrays

    PubMed Central

    Ono, Naoaki; Suzuki, Shingo; Furusawa, Chikara; Shimizu, Hiroshi; Yomo, Tetsuya

    2013-01-01

    High-density DNA microarrays are useful tools for analyzing sequence changes in DNA samples. Although microarray analysis provides informative signals from a large number of probes, the analysis and interpretation of these signals have certain inherent limitations, namely, complex dependency of signals on the probe sequences and the existence of false signals arising from non-specific binding between probe and target. In this study, we have developed a novel algorithm to detect the single-base substitutions by using microarray data based on a thermodynamic model of hybridization. We modified the thermodynamic model by introducing a penalty for mismatches that represent the effects of substitutions on hybridization affinity. This penalty results in significantly higher detection accuracy than other methods, indicating that the incorporation of hybridization free energy can improve the analysis of sequence variants by using microarray data. PMID:23382915

  1. An Affymetrix Microarray Design for Microbial Genotyping

    DTIC Science & Technology

    2009-10-01

    Pagotto, F. 2004. Selective discrimination of Listeria monocytogenes epidemic strains by a mixed-genome DNA microarray compared to discrimination by...Legionella pneumophila Paris 399 Legionella pneumophila pneumophila 5 Listeria innocua Clip 11262 105 Listeria ivanoviiI ATCC 19119 5 Listeria ...monocytogenes monocytogenes 10 Listeria monocytogenes APRT EGD-e 5 Listeria monocytogenes HPT 4b 2365 10 Listeria monocytogenes HPT EGD-e 5 Listeria

  2. Ultrahigh density microarrays of solid samples.

    PubMed

    LeBaron, Matthew J; Crismon, Heidi R; Utama, Fransiscus E; Neilson, Lynn M; Sultan, Ahmed S; Johnson, Kevin J; Andersson, Eva C; Rui, Hallgeir

    2005-07-01

    We present a sectioning and bonding technology to make ultrahigh density microarrays of solid samples, cutting edge matrix assembly (CEMA). Maximized array density is achieved by a scaffold-free, self-supporting construction with rectangular array features that are incrementally scalable. This platform technology facilitates arrays of >10,000 tissue features on a standard glass slide, inclusion of unique sample identifiers for improved manual or automated tracking, and oriented arraying of stratified or polarized samples.

  3. Systematic analysis of T7 RNA polymerase based in vitro linear RNA amplification for use in microarray experiments.

    PubMed

    Schneider, Jörg; Buness, Andreas; Huber, Wolfgang; Volz, Joachim; Kioschis, Petra; Hafner, Mathias; Poustka, Annemarie; Sültmann, Holger

    2004-04-30

    The requirement of a large amount of high-quality RNA is a major limiting factor for microarray experiments using biopsies. An average microarray experiment requires 10-100 microg of RNA. However, due to their small size, most biopsies do not yield this amount. Several different approaches for RNA amplification in vitro have been described and applied for microarray studies. In most of these, systematic analyses of the potential bias introduced by the enzymatic modifications are lacking. We examined the sources of error introduced by the T7 RNA polymerase based RNA amplification method through hybridisation studies on microarrays and performed statistical analysis of the parameters that need to be evaluated prior to routine laboratory use. The results demonstrate that amplification of the RNA has no systematic influence on the outcome of the microarray experiment. Although variations in differential expression between amplified and total RNA hybridisations can be observed, RNA amplification is reproducible, and there is no evidence that it introduces a large systematic bias. Our results underline the utility of the T7 based RNA amplification for use in microarray experiments provided that all samples under study are equally treated.

  4. Systematic analysis of T7 RNA polymerase based in vitro linear RNA amplification for use in microarray experiments

    PubMed Central

    Schneider, Jörg; Buneß, Andreas; Huber, Wolfgang; Volz, Joachim; Kioschis, Petra; Hafner, Mathias; Poustka, Annemarie; Sültmann, Holger

    2004-01-01

    Background The requirement of a large amount of high-quality RNA is a major limiting factor for microarray experiments using biopsies. An average microarray experiment requires 10–100 μg of RNA. However, due to their small size, most biopsies do not yield this amount. Several different approaches for RNA amplification in vitro have been described and applied for microarray studies. In most of these, systematic analyses of the potential bias introduced by the enzymatic modifications are lacking. Results We examined the sources of error introduced by the T7 RNA polymerase based RNA amplification method through hybridisation studies on microarrays and performed statistical analysis of the parameters that need to be evaluated prior to routine laboratory use. The results demonstrate that amplification of the RNA has no systematic influence on the outcome of the microarray experiment. Although variations in differential expression between amplified and total RNA hybridisations can be observed, RNA amplification is reproducible, and there is no evidence that it introduces a large systematic bias. Conclusions Our results underline the utility of the T7 based RNA amplification for use in microarray experiments provided that all samples under study are equally treated. PMID:15119961

  5. High-Throughput Enzyme Kinetics Using Microarrays

    SciTech Connect

    Guoxin Lu; Edward S. Yeung

    2007-11-01

    We report a microanalytical method to study enzyme kinetics. The technique involves immobilizing horseradish peroxidase on a poly-L-lysine (PLL)- coated glass slide in a microarray format, followed by applying substrate solution onto the enzyme microarray. Enzyme molecules are immobilized on the PLL-coated glass slide through electrostatic interactions, and no further modification of the enzyme or glass slide is needed. In situ detection of the products generated on the enzyme spots is made possible by monitoring the light intensity of each spot using a scientific-grade charged-coupled device (CCD). Reactions of substrate solutions of various types and concentrations can be carried out sequentially on one enzyme microarray. To account for the loss of enzyme from washing in between runs, a standard substrate solution is used for calibration. Substantially reduced amounts of substrate solution are consumed for each reaction on each enzyme spot. The Michaelis constant K{sub m} obtained by using this method is comparable to the result for homogeneous solutions. Absorbance detection allows universal monitoring, and no chemical modification of the substrate is needed. High-throughput studies of native enzyme kinetics for multiple enzymes are therefore possible in a simple, rapid, and low-cost manner.

  6. Methods for fabricating microarrays of motile bacteria.

    PubMed

    Rozhok, Sergey; Shen, Clifton K-F; Littler, Pey-Lih H; Fan, Zhifang; Liu, Chang; Mirkin, Chad A; Holz, Richard C

    2005-04-01

    Motile bacterial cell microarrays were fabricated by attaching Escherichia coli K-12 cells onto predesigned 16-mercaptohexadecanoic acid patterned microarrays, which were covalently functionalized with E. coli antibodies or poly-L-lysine. By utilizing 11-mercaptoundecyl-penta(ethylene glycol) or 11-mercapto-1-undecanol as passivating molecules, nonspecific binding of E. coli was significantly reduced. Microcontact printing and dip-pen nanolithography were used to prepare microarrays for bacterial adhesion, which was studied by optical fluorescence and atomic force microscopy. These data indicate that single motile E. coli can be attached to predesigned line or dot features and binding can occur via the cell body or the flagella of bacteria. Adherent bacteria are viable (remain alive and motile after adhesion to patterned surface features) for more than four hours. Individual motile bacterial cells can be placed onto predesigned surface features that are at least 1.3 microm in diameter or larger. The importance of controlling the adhesion of single bacterial cell to a surface is discussed with regard to biomotor design.

  7. A New Distribution Family for Microarray Data.

    PubMed

    Kelmansky, Diana Mabel; Ricci, Lila

    2017-02-10

    The traditional approach with microarray data has been to apply transformations that approximately normalize them, with the drawback of losing the original scale. The alternative stand point taken here is to search for models that fit the data, characterized by the presence of negative values, preserving their scale; one advantage of this strategy is that it facilitates a direct interpretation of the results. A new family of distributions named gpower-normal indexed by p∈R is introduced and it is proven that these variables become normal or truncated normal when a suitable gpower transformation is applied. Expressions are given for moments and quantiles, in terms of the truncated normal density. This new family can be used to model asymmetric data that include non-positive values, as required for microarray analysis. Moreover, it has been proven that the gpower-normal family is a special case of pseudo-dispersion models, inheriting all the good properties of these models, such as asymptotic normality for small variances. A combined maximum likelihood method is proposed to estimate the model parameters, and it is applied to microarray and contamination data. Rcodes are available from the authors upon request.

  8. Integrated microfluidic biochips for DNA microarray analysis.

    PubMed

    Liu, Robin Hui; Dill, Kilian; Fuji, H Sho; McShea, Andy

    2006-03-01

    A fully integrated and self-contained microfluidic biochip device has been developed to automate the fluidic handling steps required to perform a gene expression study of the human leukemia cell line (K-562). The device consists of a DNA microarray semiconductor chip with 12,000 features and a microfluidic cartridge that consists of microfluidic pumps, mixers, valves, fluid channels and reagent storage chambers. Microarray hybridization and subsequent fluidic handling and reactions (including a number of washing and labeling steps) were performed in this fully automated and miniature device before fluorescent image scanning of the microarray chip. Electrochemical micropumps were integrated in the cartridge to provide pumping of liquid solutions. A micromixing technique based on gas bubbling generated by electrochemical micropumps was developed. Low-cost check valves were implemented in the cartridge to prevent cross-talk of the stored reagents. A single-color transcriptional analysis of K-562 cells with a series of calibration controls (spiked-in controls) was performed to characterize this new platform with regard to sensitivity, specificity and dynamic range. The device detected sample RNAs with a concentration as low as 0.375 pM. Detection was quantitative over more than 3 orders of magnitude. Experiments also demonstrated that chip-to-chip variability was low, indicating that the integrated microfluidic devices eliminate manual fluidic handling steps that can be a significant source of variability in genomic analysis.

  9. Development and Applications of the Lectin Microarray.

    PubMed

    Hirabayashi, Jun; Kuno, Atsushi; Tateno, Hiroaki

    2015-01-01

    The lectin microarray is an emerging technology for glycomics. It has already found maximum use in diverse fields of glycobiology by providing simple procedures for differential glycan profiling in a rapid and high-throughput manner. Since its first appearance in the literature in 2005, many application methods have been developed essentially on the same platform, comprising a series of glycan-binding proteins immobilized on an appropriate substrate such as a glass slide. Because the lectin microarray strategy does not require prior liberation of glycans from the core protein in glycoprotein analysis, it should encourage researchers not familiar with glycotechnology to use glycan analysis in future work. This feasibility should provide a broader range of experimental scientists with good opportunities to investigate novel aspects of glycoscience. Applications of the technology include not only basic sciences but also the growing fields of bio-industry. This chapter describes first the essence of glycan profiling and the basic fabrication of the lectin microarray for this purpose. In the latter part the focus is on diverse applications to both structural and functional glycomics, with emphasis on the wide applicability now available with this new technology. Finally, the importance of developing advanced lectin engineering is discussed.

  10. Metadata management and semantics in microarray repositories.

    PubMed

    Kocabaş, F; Can, T; Baykal, N

    2011-12-01

    The number of microarray and other high-throughput experiments on primary repositories keeps increasing as do the size and complexity of the results in response to biomedical investigations. Initiatives have been started on standardization of content, object model, exchange format and ontology. However, there are backlogs and inability to exchange data between microarray repositories, which indicate that there is a great need for a standard format and data management. We have introduced a metadata framework that includes a metadata card and semantic nets that make experimental results visible, understandable and usable. These are encoded in syntax encoding schemes and represented in RDF (Resource Description Frame-word), can be integrated with other metadata cards and semantic nets, and can be exchanged, shared and queried. We demonstrated the performance and potential benefits through a case study on a selected microarray repository. We concluded that the backlogs can be reduced and that exchange of information and asking of knowledge discovery questions can become possible with the use of this metadata framework.

  11. Metadata Management and Semantics in Microarray Repositories

    PubMed Central

    Kocabaş, F; Can, T; Baykal, N

    2011-01-01

    The number of microarray and other high-throughput experiments on primary repositories keeps increasing as do the size and complexity of the results in response to biomedical investigations. Initiatives have been started on standardization of content, object model, exchange format and ontology. However, there are backlogs and inability to exchange data between microarray repositories, which indicate that there is a great need for a standard format and data management. We have introduced a metadata framework that includes a metadata card and semantic nets that make experimental results visible, understandable and usable. These are encoded in syntax encoding schemes and represented in RDF (Resource Description Frame-word), can be integrated with other metadata cards and semantic nets, and can be exchanged, shared and queried. We demonstrated the performance and potential benefits through a case study on a selected microarray repository. We concluded that the backlogs can be reduced and that exchange of information and asking of knowledge discovery questions can become possible with the use of this metadata framework. PMID:24052712

  12. Moderated effect size and P-value combinations for microarray meta-analyses.

    PubMed

    Marot, Guillemette; Foulley, Jean-Louis; Mayer, Claus-Dieter; Jaffrézic, Florence

    2009-10-15

    With the proliferation of microarray experiments and their availability in the public domain, the use of meta-analysis methods to combine results from different studies increases. In microarray experiments, where the sample size is often limited, meta-analysis offers the possibility to considerably increase the statistical power and give more accurate results. A moderated effect size combination method was proposed and compared with other meta-analysis approaches. All methods were applied to real publicly available datasets on prostate cancer, and were compared in an extensive simulation study for various amounts of inter-study variability. Although the proposed moderated effect size combination improved already existing effect size approaches, the P-value combination was found to provide a better sensitivity and a better gene ranking than the other meta-analysis methods, while effect size methods were more conservative. An R package metaMA is available on the CRAN.

  13. Application of genetic algorithms and constructive neural networks for the analysis of microarray cancer data

    PubMed Central

    2014-01-01

    Background Extracting relevant information from microarray data is a very complex task due to the characteristics of the data sets, as they comprise a large number of features while few samples are generally available. In this sense, feature selection is a very important aspect of the analysis helping in the tasks of identifying relevant genes and also for maximizing predictive information. Methods Due to its simplicity and speed, Stepwise Forward Selection (SFS) is a widely used feature selection technique. In this work, we carry a comparative study of SFS and Genetic Algorithms (GA) as general frameworks for the analysis of microarray data with the aim of identifying group of genes with high predictive capability and biological relevance. Six standard and machine learning-based techniques (Linear Discriminant Analysis (LDA), Support Vector Machines (SVM), Naive Bayes (NB), C-MANTEC Constructive Neural Network, K-Nearest Neighbors (kNN) and Multilayer perceptron (MLP)) are used within both frameworks using six free-public datasets for the task of predicting cancer outcome. Results Better cancer outcome prediction results were obtained using the GA framework noting that this approach, in comparison to the SFS one, leads to a larger selection set, uses a large number of comparison between genetic profiles and thus it is computationally more intensive. Also the GA framework permitted to obtain a set of genes that can be considered to be more biologically relevant. Regarding the different classifiers used standard feedforward neural networks (MLP), LDA and SVM lead to similar and best results, while C-MANTEC and k-NN followed closely but with a lower accuracy. Further, C-MANTEC, MLP and LDA permitted to obtain a more limited set of genes in comparison to SVM, NB and kNN, and in particular C-MANTEC resulted in the most robust classifier in terms of changes in the parameter settings. Conclusions This study shows that if prediction accuracy is the objective, the GA

  14. Application of genetic algorithms and constructive neural networks for the analysis of microarray cancer data.

    PubMed

    Luque-Baena, Rafael Marcos; Urda, Daniel; Subirats, Jose Luis; Franco, Leonardo; Jerez, Jose M

    2014-05-07

    Extracting relevant information from microarray data is a very complex task due to the characteristics of the data sets, as they comprise a large number of features while few samples are generally available. In this sense, feature selection is a very important aspect of the analysis helping in the tasks of identifying relevant genes and also for maximizing predictive information. Due to its simplicity and speed, Stepwise Forward Selection (SFS) is a widely used feature selection technique. In this work, we carry a comparative study of SFS and Genetic Algorithms (GA) as general frameworks for the analysis of microarray data with the aim of identifying group of genes with high predictive capability and biological relevance. Six standard and machine learning-based techniques (Linear Discriminant Analysis (LDA), Support Vector Machines (SVM), Naive Bayes (NB), C-MANTEC Constructive Neural Network, K-Nearest Neighbors (kNN) and Multilayer perceptron (MLP)) are used within both frameworks using six free-public datasets for the task of predicting cancer outcome. Better cancer outcome prediction results were obtained using the GA framework noting that this approach, in comparison to the SFS one, leads to a larger selection set, uses a large number of comparison between genetic profiles and thus it is computationally more intensive. Also the GA framework permitted to obtain a set of genes that can be considered to be more biologically relevant. Regarding the different classifiers used standard feedforward neural networks (MLP), LDA and SVM lead to similar and best results, while C-MANTEC and k-NN followed closely but with a lower accuracy. Further, C-MANTEC, MLP and LDA permitted to obtain a more limited set of genes in comparison to SVM, NB and kNN, and in particular C-MANTEC resulted in the most robust classifier in terms of changes in the parameter settings. This study shows that if prediction accuracy is the objective, the GA-based approach lead to better results

  15. virtualArray: a R/bioconductor package to merge raw data from different microarray platforms

    PubMed Central

    2013-01-01

    Background Microarrays have become a routine tool to address diverse biological questions. Therefore, different types and generations of microarrays have been produced by several manufacturers over time. Likewise, the diversity of raw data deposited in public databases such as NCBI GEO or EBI ArrayExpress has grown enormously. This has resulted in databases currently containing several hundred thousand microarray samples clustered by different species, manufacturers and chip generations. While one of the original goals of these databases was to make the data available to other researchers for independent analysis and, where appropriate, integration with their own data, current software implementations could not provide that feature. Only those data sets generated on the same chip platform can be readily combined and even here there are batch effects to be taken care of. A straightforward approach to deal with multiple chip types and batch effects has been missing. The software presented here was designed to solve both of these problems in a convenient and user friendly way. Results The virtualArray software package can combine raw data sets using almost any chip types based on current annotations from NCBI GEO or Bioconductor. After establishing congruent annotations for the raw data, virtualArray can then directly employ one of seven implemented methods to adjust for batch effects in the data resulting from differences between the chip types used. Both steps can be tuned to the preferences of the user. When the run is finished, the whole dataset is presented as a conventional Bioconductor “ExpressionSet” object, which can be used as input to other Bioconductor packages. Conclusions Using this software package, researchers can easily integrate their own microarray data with data from public repositories or other sources that are based on different microarray chip types. Using the default approach a robust and up-to-date batch effect correction technique is

  16. MAAMD: a workflow to standardize meta-analyses and comparison of affymetrix microarray data

    PubMed Central

    2014-01-01

    Background Mandatory deposit of raw microarray data files for public access, prior to study publication, provides significant opportunities to conduct new bioinformatics analyses within and across multiple datasets. Analysis of raw microarray data files (e.g. Affymetrix CEL files) can be time consuming, complex, and requires fundamental computational and bioinformatics skills. The development of analytical workflows to automate these tasks simplifies the processing of, improves the efficiency of, and serves to standardize multiple and sequential analyses. Once installed, workflows facilitate the tedious steps required to run rapid intra- and inter-dataset comparisons. Results We developed a workflow to facilitate and standardize Meta-Analysis of Affymetrix Microarray Data analysis (MAAMD) in Kepler. Two freely available stand-alone software tools, R and AltAnalyze were embedded in MAAMD. The inputs of MAAMD are user-editable csv files, which contain sample information and parameters describing the locations of input files and required tools. MAAMD was tested by analyzing 4 different GEO datasets from mice and drosophila. MAAMD automates data downloading, data organization, data quality control assesment, differential gene expression analysis, clustering analysis, pathway visualization, gene-set enrichment analysis, and cross-species orthologous-gene comparisons. MAAMD was utilized to identify gene orthologues responding to hypoxia or hyperoxia in both mice and drosophila. The entire set of analyses for 4 datasets (34 total microarrays) finished in ~ one hour. Conclusions MAAMD saves time, minimizes the required computer skills, and offers a standardized procedure for users to analyze microarray datasets and make new intra- and inter-dataset comparisons. PMID:24621103

  17. Design and validation of an oligonucleotide microarray for the detection of genomic rearrangements associated with common hereditary cancer syndromes.

    PubMed

    Mancini-DiNardo, Debora; Judkins, Thaddeus; Woolstenhulme, Nick; Burton, Collin; Schoenberger, Jeremy; Ryder, Matthew; Murray, Adam; Gutin, Natalia; Theisen, Aaron; Holladay, Jayson; Craft, Jonathan; Arnell, Christopher; Moyes, Kelsey; Roa, Benjamin

    2014-09-11

    Conventional Sanger sequencing reliably detects the majority of genetic mutations associated with hereditary cancers, such as single-base changes and small insertions or deletions. However, detection of genomic rearrangements, such as large deletions and duplications, requires special technologies. Microarray analysis has been successfully used to detect large rearrangements (LRs) in genetic disorders. We designed and validated a high-density oligonucleotide microarray for the detection of gene-level genomic rearrangements associated with hereditary breast and ovarian cancer (HBOC), Lynch, and polyposis syndromes. The microarray consisted of probes corresponding to the exons and flanking introns of BRCA1 and BRCA2 (≈1,700) and Lynch syndrome/polyposis genes MLH1, MSH2, MSH6, APC, MUTYH, and EPCAM (≈2,200). We validated the microarray with 990 samples previously tested for LR status in BRCA1, BRCA2, MLH1, MSH2, MSH6, APC, MUTYH, or EPCAM. Microarray results were 100% concordant with previous results in the validation studies. Subsequently, clinical microarray analysis was performed on samples from patients with a high likelihood of HBOC mutations (13,124), Lynch syndrome mutations (18,498), and polyposis syndrome mutations (2,739) to determine the proportion of LRs. Our results demonstrate that LRs constitute a substantial proportion of genetic mutations found in patients referred for hereditary cancer genetic testing. The use of microarray comparative genomic hybridization (CGH) for the detection of LRs is well-suited as an adjunct technology for both single syndrome (by Sanger sequencing analysis) and extended gene panel testing by next generation sequencing analysis. Genetic testing strategies using microarray analysis will help identify additional patients carrying LRs, who are predisposed to various hereditary cancers.

  18. DNA Microarray for Detection of Gastrointestinal Viruses

    PubMed Central

    Martínez, Miguel A.; Soto-del Río, María de los Dolores; Gutiérrez, Rosa María; Chiu, Charles Y.; Greninger, Alexander L.; Contreras, Juan Francisco; López, Susana; Arias, Carlos F.

    2014-01-01

    Gastroenteritis is a clinical illness of humans and other animals that is characterized by vomiting and diarrhea and caused by a variety of pathogens, including viruses. An increasing number of viral species have been associated with gastroenteritis or have been found in stool samples as new molecular tools have been developed. In this work, a DNA microarray capable in theory of parallel detection of more than 100 viral species was developed and tested. Initial validation was done with 10 different virus species, and an additional 5 species were validated using clinical samples. Detection limits of 1 × 103 virus particles of Human adenovirus C (HAdV), Human astrovirus (HAstV), and group A Rotavirus (RV-A) were established. Furthermore, when exogenous RNA was added, the limit for RV-A detection decreased by one log. In a small group of clinical samples from children with gastroenteritis (n = 76), the microarray detected at least one viral species in 92% of the samples. Single infection was identified in 63 samples (83%), and coinfection with more than one virus was identified in 7 samples (9%). The most abundant virus species were RV-A (58%), followed by Anellovirus (15.8%), HAstV (6.6%), HAdV (5.3%), Norwalk virus (6.6%), Human enterovirus (HEV) (9.2%), Human parechovirus (1.3%), Sapporo virus (1.3%), and Human bocavirus (1.3%). To further test the specificity and sensitivity of the microarray, the results were verified by reverse transcription-PCR (RT-PCR) detection of 5 gastrointestinal viruses. The RT-PCR assay detected a virus in 59 samples (78%). The microarray showed good performance for detection of RV-A, HAstV, and calicivirus, while the sensitivity for HAdV and HEV was low. Furthermore, some discrepancies in detection of mixed infections were observed and were addressed by reverse transcription-quantitative PCR (RT-qPCR) of the viruses involved. It was observed that differences in the amount of genetic material favored the detection of the most abundant

  19. DNA microarray for detection of gastrointestinal viruses.

    PubMed

    Martínez, Miguel A; Soto-Del Río, María de Los Dolores; Gutiérrez, Rosa María; Chiu, Charles Y; Greninger, Alexander L; Contreras, Juan Francisco; López, Susana; Arias, Carlos F; Isa, Pavel

    2015-01-01

    Gastroenteritis is a clinical illness of humans and other animals that is characterized by vomiting and diarrhea and caused by a variety of pathogens, including viruses. An increasing number of viral species have been associated with gastroenteritis or have been found in stool samples as new molecular tools have been developed. In this work, a DNA microarray capable in theory of parallel detection of more than 100 viral species was developed and tested. Initial validation was done with 10 different virus species, and an additional 5 species were validated using clinical samples. Detection limits of 1 × 10(3) virus particles of Human adenovirus C (HAdV), Human astrovirus (HAstV), and group A Rotavirus (RV-A) were established. Furthermore, when exogenous RNA was added, the limit for RV-A detection decreased by one log. In a small group of clinical samples from children with gastroenteritis (n = 76), the microarray detected at least one viral species in 92% of the samples. Single infection was identified in 63 samples (83%), and coinfection with more than one virus was identified in 7 samples (9%). The most abundant virus species were RV-A (58%), followed by Anellovirus (15.8%), HAstV (6.6%), HAdV (5.3%), Norwalk virus (6.6%), Human enterovirus (HEV) (9.2%), Human parechovirus (1.3%), Sapporo virus (1.3%), and Human bocavirus (1.3%). To further test the specificity and sensitivity of the microarray, the results were verified by reverse transcription-PCR (RT-PCR) detection of 5 gastrointestinal viruses. The RT-PCR assay detected a virus in 59 samples (78%). The microarray showed good performance for detection of RV-A, HAstV, and calicivirus, while the sensitivity for HAdV and HEV was low. Furthermore, some discrepancies in detection of mixed infections were observed and were addressed by reverse transcription-quantitative PCR (RT-qPCR) of the viruses involved. It was observed that differences in the amount of genetic material favored the detection of the most abundant

  20. A process for analysis of microarray comparative genomics hybridisation studies for bacterial genomes

    PubMed Central

    Carter, Ben; Wu, Guanghui; Woodward, Martin J; Anjum, Muna F

    2008-01-01

    Background Microarray based comparative genomic hybridisation (CGH) experiments have been used to study numerous biological problems including understanding genome plasticity in pathogenic bacteria. Typically such experiments produce large data sets that are difficult for biologists to handle. Although there are some programmes available for interpretation of bacterial transcriptomics data and CGH microarray data for looking at genetic stability in oncogenes, there are none specifically to understand the mosaic nature of bacterial genomes. Consequently a bottle neck still persists in accurate processing and mathematical analysis of these data. To address this shortfall we have produced a simple and robust CGH microarray data analysis process that may be automated in the future to understand bacterial genomic diversity. Results The process involves five steps: cleaning, normalisation, estimating gene presence and absence or divergence, validation, and analysis of data from test against three reference strains simultaneously. Each stage of the process is described and we have compared a number of methods available for characterising bacterial genomic diversity, for calculating the cut-off between gene presence and absence or divergence, and shown that a simple dynamic approach using a kernel density estimator performed better than both established, as well as a more sophisticated mixture modelling technique. We have also shown that current methods commonly used for CGH microarray analysis in tumour and cancer cell lines are not appropriate for analysing our data. Conclusion After carrying out the analysis and validation for three sequenced Escherichia coli strains, CGH microarray data from 19 E. coli O157 pathogenic test strains were used to demonstrate the benefits of applying this simple and robust process to CGH microarray studies using bacterial genomes. PMID:18230148

  1. Identification of new autoantigens for primary biliary cirrhosis using human proteome microarrays.

    PubMed

    Hu, Chao-Jun; Song, Guang; Huang, Wei; Liu, Guo-Zhen; Deng, Chui-Wen; Zeng, Hai-Pan; Wang, Li; Zhang, Feng-Chun; Zhang, Xuan; Jeong, Jun Seop; Blackshaw, Seth; Jiang, Li-Zhi; Zhu, Heng; Wu, Lin; Li, Yong-Zhe

    2012-09-01

    Primary biliary cirrhosis (PBC) is a chronic cholestatic liver disease of unknown etiology and is considered to be an autoimmune disease. Autoantibodies are important tools for accurate diagnosis of PBC. Here, we employed serum profiling analysis using a human proteome microarray composed of about 17,000 full-length unique proteins and identified 23 proteins that correlated with PBC. To validate these results, we fabricated a PBC-focused microarray with 21 of these newly identified candidates and nine additional known PBC antigens. By screening the PBC microarrays with additional cohorts of 191 PBC patients and 321 controls (43 autoimmune hepatitis, 55 hepatitis B virus, 31 hepatitis C virus, 48 rheumatoid arthritis, 45 systematic lupus erythematosus, 49 systemic sclerosis, and 50 healthy), six proteins were confirmed as novel PBC autoantigens with high sensitivities and specificities, including hexokinase-1 (isoforms I and II), Kelch-like protein 7, Kelch-like protein 12, zinc finger and BTB domain-containing protein 2, and eukaryotic translation initiation factor 2C, subunit 1. To facilitate clinical diagnosis, we developed ELISA for Kelch-like protein 12 and zinc finger and BTB domain-containing protein 2 and tested large cohorts (297 PBC and 637 control sera) to confirm the sensitivities and specificities observed in the microarray-based assays. In conclusion, our research showed that a strategy using high content protein microarray combined with a smaller but more focused protein microarray can effectively identify and validate novel PBC-specific autoantigens and has the capacity to be translated to clinical diagnosis by means of an ELISA-based method.

  2. A comparative analytical assay of gene regulatory networks inferred using microarray and RNA-seq datasets

    PubMed Central

    Izadi, Fereshteh; Zarrini, Hamid Najafi; Kiani, Ghaffar; Jelodar, Nadali Babaeian

    2016-01-01

    A Gene Regulatory Network (GRN) is a collection of interactions between molecular regulators and their targets in cells governing gene expression level. Omics data explosion generated from high-throughput genomic assays such as microarray and RNA-Seq technologies and the emergence of a number of pre-processing methods demands suitable guidelines to determine the impact of transcript data platforms and normalization procedures on describing associations in GRNs. In this study exploiting publically available microarray and RNA-Seq datasets and a gold standard of transcriptional interactions in Arabidopsis, we performed a comparison between six GRNs derived by RNA-Seq and microarray data and different normalization procedures. As a result we observed that compared algorithms were highly data-specific and Networks reconstructed by RNA-Seq data revealed a considerable accuracy against corresponding networks captured by microarrays. Topological analysis showed that GRNs inferred from two platforms were similar in several of topological features although we observed more connectivity in RNA-Seq derived genes network. Taken together transcriptional regulatory networks obtained by Robust Multiarray Averaging (RMA) and Variance-Stabilizing Transformed (VST) normalized data demonstrated predicting higher rate of true edges over the rest of methods used in this comparison. PMID:28293077

  3. Gene microarray data analysis using parallel point-symmetry-based clustering.

    PubMed

    Sarkar, Anasua; Maulik, Ujjwal

    2015-01-01

    Identification of co-expressed genes is the central goal in microarray gene expression analysis. Point-symmetry-based clustering is an important unsupervised learning technique for recognising symmetrical convex- or non-convex-shaped clusters. To enable fast clustering of large microarray data, we propose a distributed time-efficient scalable approach for point-symmetry-based K-Means algorithm. A natural basis for analysing gene expression data using symmetry-based algorithm is to group together genes with similar symmetrical expression patterns. This new parallel implementation also satisfies linear speedup in timing without sacrificing the quality of clustering solution on large microarray data sets. The parallel point-symmetry-based K-Means algorithm is compared with another new parallel symmetry-based K-Means and existing parallel K-Means over eight artificial and benchmark microarray data sets, to demonstrate its superiority, in both timing and validity. The statistical analysis is also performed to establish the significance of this message-passing-interface based point-symmetry K-Means implementation. We also analysed the biological relevance of clustering solutions.

  4. Interpreting the gene expression microarray results: a user-based experience.

    PubMed

    Melissari, Erika; Di Russo, Manuela; Mariotti, Veronica; Righi, Marco; Iofrida, Caterina; Pellegrini, Silvia

    2013-06-01

    In recent years many tools have been developed to cope with the interpretation of gene expression results from microarray experiments. The effectiveness of these tools largely depends on their ease of use by biomedical researchers. Tools based on effective computational methods, indeed, cannot be fully exploited by users if they are not supported by an intuitive interface, a large set of utilities and effective outputs. In this paper, 10 tools for the interpretation of gene expression microarray results have been tested on 11 microarray datasets and evaluated according to eight assessment criteria: 1. interface design and usability, 2. easiness of input submission, 3. effectiveness of output representation and 4. of the downloaded outputs, 5. possibility to submit multiple gene IDs, 6. sources of information, 7. provision of different statistical tests and 8. of multiple test correction methods. Strengths and weaknesses of each tool are highlighted to: a. provide useful tips to users dealing with the biological interpretation of microarray results; b. draw the attention of software developers on the usability of their tools.

  5. Thermodynamically optimal whole-genome tiling microarray design and validation.

    PubMed

    Cho, Hyejin; Chou, Hui-Hsien

    2016-06-13

    Microarray is an efficient apparatus to interrogate the whole transcriptome of species. Microarray can be designed according to annotated gene sets, but the resulted microarrays cannot be used to identify novel transcripts and this design method is not applicable to unannotated species. Alternatively, a whole-genome tiling microarray can be designed using only genomic sequences without gene annotations, and it can be used to detect novel RNA transcripts as well as known genes. The difficulty with tiling microarray design lies in the tradeoff between probe-specificity and coverage of the genome. Sequence comparison methods based on BLAST or similar software are commonly employed in microarray design, but they cannot precisely determine the subtle thermodynamic competition between probe targets and partially matched probe nontargets during hybridizations. Using the whole-genome thermodynamic analysis software PICKY to design tiling microarrays, we can achieve maximum whole-genome coverage allowable under the thermodynamic constraints of each target genome. The resulted tiling microarrays are thermodynamically optimal in the sense that all selected probes share the same melting temperature separation range between their targets and closest nontargets, and no additional probes can be added without violating the specificity of the microarray to the target genome. This new design method was used to create two whole-genome tiling microarrays for Escherichia coli MG1655 and Agrobacterium tumefaciens C58 and the experiment results validated the design.

  6. A salmonid EST genomic study: genes, duplications, phylogeny and microarrays

    PubMed Central

    Koop, Ben F; von Schalburg, Kristian R; Leong, Jong; Walker, Neil; Lieph, Ryan; Cooper, Glenn A; Robb, Adrienne; Beetz-Sargent, Marianne; Holt, Robert A; Moore, Richard; Brahmbhatt, Sonal; Rosner, Jamie; Rexroad, Caird E; McGowan, Colin R; Davidson, William S

    2008-01-01

    Background Salmonids are of interest because of their relatively recent genome duplication, and their extensive use in wild fisheries and aquaculture. A comprehensive gene list and a comparison of genes in some of the different species provide valuable genomic information for one of the most widely studied groups of fish. Results 298,304 expressed sequence tags (ESTs) from Atlantic salmon (69% of the total), 11,664 chinook, 10,813 sockeye, 10,051 brook trout, 10,975 grayling, 8,630 lake whitefish, and 3,624 northern pike ESTs were obtained in this study and have been deposited into the public databases. Contigs were built and putative full-length Atlantic salmon clones have been identified. A database containing ESTs, assemblies, consensus sequences, open reading frames, gene predictions and putative annotation is available. The overall similarity between Atlantic salmon ESTs and those of rainbow trout, chinook, sockeye, brook trout, grayling, lake whitefish, northern pike and rainbow smelt is 93.4, 94.2, 94.6, 94.4, 92.5, 91.7, 89.6, and 86.2% respectively. An analysis of 78 transcript sets show Salmo as a sister group to Oncorhynchus and Salvelinus within Salmoninae, and Thymallinae as a sister group to Salmoninae and Coregoninae within Salmonidae. Extensive gene duplication is consistent with a genome duplication in the common ancestor of salmonids. Using all of the available EST data, a new expanded salmonid cDNA microarray of 32,000 features was created. Cross-species hybridizations to this cDNA microarray indicate that this resource will be useful for studies of all 68 salmonid species. Conclusion An extensive collection and analysis of salmonid RNA putative transcripts indicate that Pacific salmon, Atlantic salmon and charr are 94–96% similar while the more distant whitefish, grayling, pike and smelt are 93, 92, 89 and 86% similar to salmon. The salmonid transcriptome reveals a complex history of gene duplication that is consistent with an ancestral

  7. Classification and immunohistochemical scoring of breast tissue microarray spots.

    PubMed

    Amaral, Telmo; McKenna, Stephen J; Robertson, Katherine; Thompson, Alastair

    2013-10-01

    Tissue microarrays (TMAs) facilitate the survey of very large numbers of tumors. However, the manual assessment of stained TMA sections constitutes a bottleneck in the pathologist's work flow. This paper presents a computational pipeline for automatically classifying and scoring breast cancer TMA spots that have been subjected to nuclear immunostaining. Spots are classified based on a bag of visual words approach. Immunohistochemical scoring is performed by computing spot features reflecting the proportion of epithelial nuclei that are stained and the strength of that staining. These are then mapped onto an ordinal scale used by pathologists. Multilayer perceptron classifiers are compared with latent topic models and support vector machines for spot classification, and with Gaussian process ordinal regression and linear models for scoring. Intraobserver variation is also reported. The use of posterior entropy to identify uncertain cases is demonstrated. Evaluation is performed using TMA images stained for progesterone receptor.

  8. Exhaustive Search for Fuzzy Gene Networks from Microarray Data

    SciTech Connect

    Sokhansanj, B A; Fitch, J P; Quong, J N; Quong, A A

    2003-07-07

    Recent technological advances in high-throughput data collection allow for the study of increasingly complex systems on the scale of the whole cellular genome and proteome. Gene network models are required to interpret large and complex data sets. Rationally designed system perturbations (e.g. gene knock-outs, metabolite removal, etc) can be used to iteratively re