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Sample records for large public microarray

  1. Navigating Public Microarray Databases

    PubMed Central

    Bähler, Jürg

    2004-01-01

    With the ever-escalating amount of data being produced by genome-wide microarray studies, it is of increasing importance that these data are captured in public databases so that researchers can use this information to complement and enhance their own studies. Many groups have set up databases of expression data, ranging from large repositories, which are designed to comprehensively capture all published data, through to more specialized databases. The public repositories, such as ArrayExpress at the European Bioinformatics Institute contain complete datasets in raw format in addition to processed data, whilst the specialist databases tend to provide downstream analysis of normalized data from more focused studies and data sources. Here we provide a guide to the use of these public microarray resources. PMID:18629145

  2. Navigating public microarray databases.

    PubMed

    Penkett, Christopher J; Bähler, Jürg

    2004-01-01

    With the ever-escalating amount of data being produced by genome-wide microarray studies, it is of increasing importance that these data are captured in public databases so that researchers can use this information to complement and enhance their own studies. Many groups have set up databases of expression data, ranging from large repositories, which are designed to comprehensively capture all published data, through to more specialized databases. The public repositories, such as ArrayExpress at the European Bioinformatics Institute contain complete datasets in raw format in addition to processed data, whilst the specialist databases tend to provide downstream analysis of normalized data from more focused studies and data sources. Here we provide a guide to the use of these public microarray resources. PMID:18629145

  3. Conceptual Aspects of Large Meta-Analyses with Publicly Available Microarray Data: A Case Study in Oncology

    PubMed Central

    Schmidberger, Markus; Lennert, Sabine; Mansmann, Ulrich

    2011-01-01

    Large public repositories of microarray experiments offer an abundance of biological data. It is of interest to use and to combine the available material to create new biological information and to develop a broader view on biological phenomena. Meta-analyses recombine similar information over a series of experiments to sketch scientific aspects which were not accessible by each of the single experiments. Meta-analysis of high-throughput experiments has to handle methodological as well as technical challenges. Methodological aspects concern the identification of homogeneous material which can be combined by appropriate statistical procedures. Technical challenges come from the data management of large amounts of high-dimensional data, long computation time, as well as the handling of the stored phenotype data. This paper compares in a meta-analysis of a large series of microarray experiments the interaction structure within selected pathways between different tumour entities. The feasibility of such a study is explored and a technical as well as a statistical framework for its completion is presented. Multiple obstacles were met during completion of this project. They are mainly related to the quality of the available data and influence the biological interpretation of the results derived. The sobering experience of our study asks for combined efforts to improve the data quality in public repositories of high-throughput data. The exploration of the available data in large meta-analyses is limited by incomplete documentation of essential aspects of experiments and studies, by technical deficiencies in the data stored, and by careless duplications of data. PMID:21423405

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  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. 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

  7. 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. PMID:16098712

  8. 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...

  9. A large field CCD system for quantitative imaging of microarrays

    PubMed Central

    Hamilton, G.; Brown, N.; Oseroff, V.; Huey, B.; Segraves, R.; Sudar, D.; Kumler, J.; Albertson, D.; Pinkel, D.

    2006-01-01

    We describe a charge-coupled device (CCD) imaging system for microarrays capable of acquiring quantitative, high dynamic range images of very large fields. Illumination is supplied by an arc lamp, and filters are used to define excitation and emission bands. The system is linear down to fluorochrome densities ≪1 molecule/µm2. The ratios of the illumination intensity distributions for all excitation wavelengths have a maximum deviation ∼±4% over the object field, so that images can be analyzed without computational corrections for the illumination pattern unless higher accuracy is desired. Custom designed detection optics produce achromatic images of the spectral region from ∼ 450 to ∼750 nm. Acquisition of a series of images of multiple fluorochromes from multiple arrays occurs under computer control. The version of the system described in detail provides images of 20 mm square areas using a 27 mm square, 2K × 2K pixel, cooled CCD chip with a well depth of ∼105 electrons, and provides ratio measurements accurate to a few percent over a dynamic range in intensity >1000. Resolution referred to the sample is 10 µm, sufficient for obtaining quantitative multicolor images from >30 000 array elements in an 18 mm × 18 mm square. PMID:16670425

  10. 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. PMID:19965979

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

    PubMed

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

    2016-07-01

    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

  12. A Tool for Sheep Product Quality: Custom Microarrays from Public Databases

    PubMed Central

    Bongiorni, Silvia; Chillemi, Giovanni; Prosperini, Gianluca; Bueno, Susana; Valentini, Alessio; Pariset, Lorraine

    2009-01-01

    Milk and dairy products are an essential food and an economic resource in many countries. Milk component synthesis and secretion by the mammary gland involve expression of a large number of genes whose nutritional regulation remains poorly defined. The purpose of this study was to gain an understanding of the genomic influence on milk quality and synthesis by comparing two sheep breeds with different milking attitude (Sarda and Gentile di Puglia) using sheep-specific microarray technology. From sheep ESTs deposited at NCBI, we have generated the first annotated microarray developed for sheep with a coverage of most of the genome. PMID:22253981

  13. Query Large Scale Microarray Compendium Datasets Using a Model-Based Bayesian Approach with Variable Selection

    PubMed Central

    Hu, Ming; Qin, Zhaohui S.

    2009-01-01

    In microarray gene expression data analysis, it is often of interest to identify genes that share similar expression profiles with a particular gene such as a key regulatory protein. Multiple studies have been conducted using various correlation measures to identify co-expressed genes. While working well for small datasets, the heterogeneity introduced from increased sample size inevitably reduces the sensitivity and specificity of these approaches. This is because most co-expression relationships do not extend to all experimental conditions. With the rapid increase in the size of microarray datasets, identifying functionally related genes from large and diverse microarray gene expression datasets is a key challenge. We develop a model-based gene expression query algorithm built under the Bayesian model selection framework. It is capable of detecting co-expression profiles under a subset of samples/experimental conditions. In addition, it allows linearly transformed expression patterns to be recognized and is robust against sporadic outliers in the data. Both features are critically important for increasing the power of identifying co-expressed genes in large scale gene expression datasets. Our simulation studies suggest that this method outperforms existing correlation coefficients or mutual information-based query tools. When we apply this new method to the Escherichia coli microarray compendium data, it identifies a majority of known regulons as well as novel potential target genes of numerous key transcription factors. PMID:19214232

  14. ArrayExpress--a public repository for microarray gene expression data at the EBI.

    PubMed

    Brazma, Alvis; Parkinson, Helen; Sarkans, Ugis; Shojatalab, Mohammadreza; Vilo, Jaak; Abeygunawardena, Niran; Holloway, Ele; Kapushesky, Misha; Kemmeren, Patrick; Lara, Gonzalo Garcia; Oezcimen, Ahmet; Rocca-Serra, Philippe; Sansone, Susanna-Assunta

    2003-01-01

    ArrayExpress is a new public database of microarray gene expression data at the EBI, which is a generic gene expression database designed to hold data from all microarray platforms. ArrayExpress uses the annotation standard Minimum Information About a Microarray Experiment (MIAME) and the associated XML data exchange format Microarray Gene Expression Markup Language (MAGE-ML) and it is designed to store well annotated data in a structured way. The ArrayExpress infrastructure consists of the database itself, data submissions in MAGE-ML format or via an online submission tool MIAMExpress, online database query interface, and the Expression Profiler online analysis tool. ArrayExpress accepts three types of submission, arrays, experiments and protocols, each of these is assigned an accession number. Help on data submission and annotation is provided by the curation team. The database can be queried on parameters such as author, laboratory, organism, experiment or array types. With an increasing number of organisations adopting MAGE-ML standard, the volume of submissions to ArrayExpress is increasing rapidly. The database can be accessed at http://www.ebi.ac.uk/arrayexpress. PMID:12519949

  15. 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

  16. 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. PMID:26942917

  17. 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

  18. Differentially Expressed RNA from Public Microarray Data Identifies Serum Protein Biomarkers for Cross-Organ Transplant Rejection and Other Conditions

    PubMed Central

    Chen, Rong; Sigdel, Tara K.; Li, Li; Kambham, Neeraja; Dudley, Joel T.; Hsieh, Szu-chuan; Klassen, R. Bryan; Chen, Amery; Caohuu, Tuyen; Morgan, Alexander A.; Valantine, Hannah A.; Khush, Kiran K.; Sarwal, Minnie M.; Butte, Atul J.

    2010-01-01

    Serum proteins are routinely used to diagnose diseases, but are hard to find due to low sensitivity in screening the serum proteome. Public repositories of microarray data, such as the Gene Expression Omnibus (GEO), contain RNA expression profiles for more than 16,000 biological conditions, covering more than 30% of United States mortality. We hypothesized that genes coding for serum- and urine-detectable proteins, and showing differential expression of RNA in disease-damaged tissues would make ideal diagnostic protein biomarkers for those diseases. We showed that predicted protein biomarkers are significantly enriched for known diagnostic protein biomarkers in 22 diseases, with enrichment significantly higher in diseases for which at least three datasets are available. We then used this strategy to search for new biomarkers indicating acute rejection (AR) across different types of transplanted solid organs. We integrated three biopsy-based microarray studies of AR from pediatric renal, adult renal and adult cardiac transplantation and identified 45 genes upregulated in all three. From this set, we chose 10 proteins for serum ELISA assays in 39 renal transplant patients, and discovered three that were significantly higher in AR. Interestingly, all three proteins were also significantly higher during AR in the 63 cardiac transplant recipients studied. Our best marker, serum PECAM1, identified renal AR with 89% sensitivity and 75% specificity, and also showed increased expression in AR by immunohistochemistry in renal, hepatic and cardiac transplant biopsies. Our results demonstrate that integrating gene expression microarray measurements from disease samples and even publicly-available data sets can be a powerful, fast, and cost-effective strategy for the discovery of new diagnostic serum protein biomarkers. PMID:20885780

  19. A large-area hemispherical perforated bead microarray for monitoring bead based aptamer and target protein interaction

    PubMed Central

    Choi, Jong Seob; Bae, Sunwoong; Kim, Kyung Hoon; Seo, Tae Seok

    2014-01-01

    Herein, we present a large-area 3D hemispherical perforated microwell structure for a bead based bioassay. Such a unique microstructure enables us to perform the rapid and stable localization of the beads at the single bead level and the facile manipulation of the bead capture and retrieval with high speed and efficiency. The fabrication process mainly consisted of three steps: the convex micropatterned nickel (Ni) mold production from the concave micropatterned silicon (Si) wafer, hot embossing on the polymer matrix to generate the concave micropattened acrylate sheet, and reactive ion etching to make the bottom holes. The large-area hemispherical perforated micropatterned acrylate sheet was sandwiched between two polydimethylsiloxane (PDMS) microchannel layers. The bead solution was injected and recovered in the top PDMS microchannel, while the bottom PDMS microchannel was connected with control lines to exert the hydrodynamic force in order to alter the flow direction of the bead solution for the bead capture and release operation. The streptavidin-coated microbead capture was achieved with almost 100% yield within 1 min, and all the beads were retrieved in 10 s. Lysozyme or thrombin binding aptamer labelled microbeads were trapped on the proposed bead microarray, and the in situ fluorescence signal of the bead array was monitored after aptamer-target protein interaction. The protein-aptamer conjugated microbeads were recovered, and the aptamer was isolated for matrix assisted laser desorption/ionization time-of-flight mass spectrometry analysis to confirm the identity of the aptamer. PMID:25587373

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

    DOE PAGESBeta

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

    2016-03-25

    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

  1. 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. PMID:27015116

  2. Components of the endocannabinoid and dopamine systems are dysregulated in Huntington's disease: analysis of publicly available microarray datasets

    PubMed Central

    Laprairie, Robert B; Bagher, Amina M; Precious, Sophie V; Denovan-Wright, Eileen M

    2015-01-01

    The endocannabinoid system (ECS) and the dopaminergic system (DAS) are two major regulators of basal ganglia function. During Huntington's disease (HD) pathogenesis, the expression of genes in both the ECS and DAS is dysregulated. The purpose of this study was to determine the changes that were consistently observed in the ECS and DAS during HD progression in the central nervous system (CNS) and in the periphery in different models of HD and human HD tissue. To do this, we conducted a meta-analysis of differential gene expression in the ECS and DAS using publicly available microarray data. The consolidated data were summarized as observed changes in gene expression (OCGE) using a weighted sum for each gene. In addition, consolidated data were compared to previously published studies that were not available in the gene expression omnibus (GEO) database. The resulting data confirm gene expression changes observed using different approaches and provide novel insights into the consistency between changes observed in human tissue and various models, as well as disease stage- and tissue-specific transcriptional dysregulation in HD. The major implication of the systems-wide data presented here is that therapeutic strategies targeting the ECS or DAS must consider the dynamic changes in gene expression over time and in different body areas, which occur during HD progression and the interconnectedness of the two systems. PMID:25692022

  3. CancerMA: a web-based tool for automatic meta-analysis of public cancer microarray data

    PubMed Central

    Feichtinger, Julia; McFarlane, Ramsay J.; Larcombe, Lee D.

    2012-01-01

    The identification of novel candidate markers is a key challenge in the development of cancer therapies. This can be facilitated by putting accessible and automated approaches analysing the current wealth of ‘omic’-scale data in the hands of researchers who are directly addressing biological questions. Data integration techniques and standardized, automated, high-throughput analyses are needed to manage the data available as well as to help narrow down the excessive number of target gene possibilities presented by modern databases and system-level resources. Here we present CancerMA, an online, integrated bioinformatic pipeline for automated identification of novel candidate cancer markers/targets; it operates by means of meta-analysing expression profiles of user-defined sets of biologically significant and related genes across a manually curated database of 80 publicly available cancer microarray datasets covering 13 cancer types. A simple-to-use web interface allows bioinformaticians and non-bioinformaticians alike to initiate new analyses as well as to view and retrieve the meta-analysis results. The functionality of CancerMA is shown by means of two validation datasets. Database URL: http://www.cancerma.org.uk PMID:23241162

  4. DNA Microarrays

    NASA Astrophysics Data System (ADS)

    Nguyen, C.; Gidrol, X.

    Genomics has revolutionised biological and biomedical research. This revolution was predictable on the basis of its two driving forces: the ever increasing availability of genome sequences and the development of new technology able to exploit them. Up until now, technical limitations meant that molecular biology could only analyse one or two parameters per experiment, providing relatively little information compared with the great complexity of the systems under investigation. This gene by gene approach is inadequate to understand biological systems containing several thousand genes. It is essential to have an overall view of the DNA, RNA, and relevant proteins. A simple inventory of the genome is not sufficient to understand the functions of the genes, or indeed the way that cells and organisms work. For this purpose, functional studies based on whole genomes are needed. Among these new large-scale methods of molecular analysis, DNA microarrays provide a way of studying the genome and the transcriptome. The idea of integrating a large amount of data derived from a support with very small area has led biologists to call these chips, borrowing the term from the microelectronics industry. At the beginning of the 1990s, the development of DNA chips on nylon membranes [1, 2], then on glass [3] and silicon [4] supports, made it possible for the first time to carry out simultaneous measurements of the equilibrium concentration of all the messenger RNA (mRNA) or transcribed RNA in a cell. These microarrays offer a wide range of applications, in both fundamental and clinical research, providing a method for genome-wide characterisation of changes occurring within a cell or tissue, as for example in polymorphism studies, detection of mutations, and quantitative assays of gene copies. With regard to the transcriptome, it provides a way of characterising differentially expressed genes, profiling given biological states, and identifying regulatory channels.

  5. Protein Microarrays

    NASA Astrophysics Data System (ADS)

    Ricard-Blum, S.

    Proteins are key actors in the life of the cell, involved in many physiological and pathological processes. Since variations in the expression of messenger RNA are not systematically correlated with variations in the protein levels, the latter better reflect the way a cell functions. Protein microarrays thus supply complementary information to DNA chips. They are used in particular to analyse protein expression profiles, to detect proteins within complex biological media, and to study protein-protein interactions, which give information about the functions of those proteins [3-9]. They have the same advantages as DNA microarrays for high-throughput analysis, miniaturisation, and the possibility of automation. Section 18.1 gives a brief overview of proteins. Following this, Sect. 18.2 describes how protein microarrays can be made on flat supports, explaining how proteins can be produced and immobilised on a solid support, and discussing the different kinds of substrate and detection method. Section 18.3 discusses the particular format of protein microarrays in suspension. The diversity of protein microarrays and their applications are then reported in Sect. 18.4, with applications to therapeutics (protein-drug interactions) and diagnostics. The prospects for future developments of protein microarrays are then outlined in the conclusion. The bibliography provides an extensive list of reviews and detailed references for those readers who wish to go further in this area. Indeed, the aim of the present chapter is not to give an exhaustive or detailed analysis of the state of the art, but rather to provide the reader with the basic elements needed to understand how proteins are designed and used.

  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. Communicating Chemistry--From Large Classes to the Larger Public

    ERIC Educational Resources Information Center

    Harpp, David N.

    2004-01-01

    This article is a general summary of the James Flack Norris Award Lecture given in November 2003. It chronicles various events leading up to the award centering on teaching chemistry to very large classes and providing information to the general public through a unique University Office for Science and Society.

  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. PMID:27276104

  9. Microarray Analysis of Microbial Weathering

    NASA Astrophysics Data System (ADS)

    Olsson-Francis, K.; van Houdt, R.; Leys, N.; Mergeay, M.; Cockell, C. S.

    2010-04-01

    Microarray analysis of the heavy metal resistant bacterium, Cupriavidus metallidurans CH34 was used to investigate the genes involved in the weathering. The results demonstrated that large porin and membrane transporter genes were unregulated.

  10. 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.

  11. Meta-Analysis of Public Microarray Datasets Reveals Voltage-Gated Calcium Gene Signatures in Clinical Cancer Patients

    PubMed Central

    Wang, Chih-Yang; Lai, Ming-Derg; Phan, Nam Nhut; Sun, Zhengda; Lin, Yen-Chang

    2015-01-01

    Voltage-gated calcium channels (VGCCs) are well documented to play roles in cell proliferation, migration, and apoptosis; however, whether VGCCs regulate the onset and progression of cancer is still under investigation. The VGCC family consists of five members, which are L-type, N-type, T-type, R-type and P/Q type. To date, no holistic approach has been used to screen VGCC family genes in different types of cancer. We analyzed the transcript expression of VGCCs in clinical cancer tissue samples by accessing ONCOMINE (www.oncomine.org), a web-based microarray database, to perform a systematic analysis. Every member of the VGCCs was examined across 21 different types of cancer by comparing mRNA expression in cancer to that in normal tissue. A previous study showed that altered expression of mRNA in cancer tissue may play an oncogenic role and promote tumor development; therefore, in the present findings, we focus only on the overexpression of VGCCs in different types of cancer. This bioinformatics analysis revealed that different subtypes of VGCCs (CACNA1C, CACNA1D, CACNA1B, CACNA1G, and CACNA1I) are implicated in the development and progression of diverse types of cancer and show dramatic up-regulation in breast cancer. CACNA1F only showed high expression in testis cancer, whereas CACNA1A, CACNA1C, and CACNA1D were highly expressed in most types of cancer. The current analysis revealed that specific VGCCs likely play essential roles in specific types of cancer. Collectively, we identified several VGCC targets and classified them according to different cancer subtypes for prospective studies on the underlying carcinogenic mechanisms. The present findings suggest that VGCCs are possible targets for prospective investigation in cancer treatment. PMID:26147197

  12. Meta-Analysis of Public Microarray Datasets Reveals Voltage-Gated Calcium Gene Signatures in Clinical Cancer Patients.

    PubMed

    Wang, Chih-Yang; Lai, Ming-Derg; Phan, Nam Nhut; Sun, Zhengda; Lin, Yen-Chang

    2015-01-01

    Voltage-gated calcium channels (VGCCs) are well documented to play roles in cell proliferation, migration, and apoptosis; however, whether VGCCs regulate the onset and progression of cancer is still under investigation. The VGCC family consists of five members, which are L-type, N-type, T-type, R-type and P/Q type. To date, no holistic approach has been used to screen VGCC family genes in different types of cancer. We analyzed the transcript expression of VGCCs in clinical cancer tissue samples by accessing ONCOMINE (www.oncomine.org), a web-based microarray database, to perform a systematic analysis. Every member of the VGCCs was examined across 21 different types of cancer by comparing mRNA expression in cancer to that in normal tissue. A previous study showed that altered expression of mRNA in cancer tissue may play an oncogenic role and promote tumor development; therefore, in the present findings, we focus only on the overexpression of VGCCs in different types of cancer. This bioinformatics analysis revealed that different subtypes of VGCCs (CACNA1C, CACNA1D, CACNA1B, CACNA1G, and CACNA1I) are implicated in the development and progression of diverse types of cancer and show dramatic up-regulation in breast cancer. CACNA1F only showed high expression in testis cancer, whereas CACNA1A, CACNA1C, and CACNA1D were highly expressed in most types of cancer. The current analysis revealed that specific VGCCs likely play essential roles in specific types of cancer. Collectively, we identified several VGCC targets and classified them according to different cancer subtypes for prospective studies on the underlying carcinogenic mechanisms. The present findings suggest that VGCCs are possible targets for prospective investigation in cancer treatment. PMID:26147197

  13. The Stanford Tissue Microarray Database.

    PubMed

    Marinelli, Robert J; Montgomery, Kelli; Liu, Chih Long; Shah, Nigam H; Prapong, Wijan; Nitzberg, Michael; Zachariah, Zachariah K; Sherlock, Gavin J; Natkunam, Yasodha; West, Robert B; van de Rijn, Matt; Brown, Patrick O; Ball, Catherine A

    2008-01-01

    The Stanford Tissue Microarray Database (TMAD; http://tma.stanford.edu) is a public resource for disseminating annotated tissue images and associated expression data. Stanford University pathologists, researchers and their collaborators worldwide use TMAD for designing, viewing, scoring and analyzing their tissue microarrays. The use of tissue microarrays allows hundreds of human tissue cores to be simultaneously probed by antibodies to detect protein abundance (Immunohistochemistry; IHC), or by labeled nucleic acids (in situ hybridization; ISH) to detect transcript abundance. TMAD archives multi-wavelength fluorescence and bright-field images of tissue microarrays for scoring and analysis. As of July 2007, TMAD contained 205 161 images archiving 349 distinct probes on 1488 tissue microarray slides. Of these, 31 306 images for 68 probes on 125 slides have been released to the public. To date, 12 publications have been based on these raw public data. TMAD incorporates the NCI Thesaurus ontology for searching tissues in the cancer domain. Image processing researchers can extract images and scores for training and testing classification algorithms. The production server uses the Apache HTTP Server, Oracle Database and Perl application code. Source code is available to interested researchers under a no-cost license. PMID:17989087

  14. Optics in large-scale architectural projects: public aquariums

    NASA Astrophysics Data System (ADS)

    Tesar, John C.

    2002-09-01

    Submersed aquatic vegetation can survive to a depth of approximately 20% of surface water irradiance. Large displays featured in public aquariums are often open to the sky, but the building roof acts as an aperture and obscures much of the direct solar path. Side-walls within the tank often absorb more than they reflect or scatter and as a result plants and fish get little more than the diffuse solar component without supplemental illumination. The loss mechanisms are detailed and design suggestions are considered, including heliostats, lightpipes and tracked parabolic reflectors with fiber optics.

  15. Tissue microarrays: applications in genomic research.

    PubMed

    Watanabe, Aprill; Cornelison, Robert; Hostetter, Galen

    2005-03-01

    The widespread application of tissue microarrays in cancer research and the clinical pathology laboratory demonstrates a versatile and portable technology. The rapid integration of tissue microarrays into biomarker discovery and validation processes reflects the forward thinking of researchers who have pioneered the high-density tissue microarray. The precise arrangement of hundreds of archival clinical tissue samples into a composite tissue microarray block is now a proven method for the efficient and standardized analysis of molecular markers. With applications in cancer research, tissue microarrays are a valuable tool in validating candidate markers discovered in highly sensitive genome-wide microarray experiments. With applications in clinical pathology, tissue microarrays are used widely in immunohistochemistry quality control and quality assurance. The timeline of a biomarker implicated in prostate neoplasia, which was identified by complementary DNA expression profiling, validated by tissue microarrays and is now used as a prognostic immunohistochemistry marker, is reviewed. The tissue microarray format provides opportunities for digital imaging acquisition, image processing and database integration. Advances in digital imaging help to alleviate previous bottlenecks in the research pipeline, permit computer image scoring and convey telepathology opportunities for remote image analysis. The tissue microarray industry now includes public and private sectors with varying degrees of research utility and offers a range of potential tissue microarray applications in basic research, prognostic oncology and drug discovery. PMID:15833047

  16. 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.

  17. 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

  18. Aptamer Microarrays

    SciTech Connect

    Angel-Syrett, Heather; Collett, Jim; Ellington, Andrew D.

    2009-01-02

    In vitro selection can yield specific, high-affinity aptamers. We and others have devised methods for the automated selection of aptamers, and have begun to use these reagents for the construction of arrays. Arrayed aptamers have proven to be almost as sensitive as their solution phase counterparts, and when ganged together can provide both specific and general diagnostic signals for proteins and other analytes. We describe here technical details regarding the production and processing of aptamer microarrays, including blocking, washing, drying, and scanning. We will also discuss the challenges involved in developing standardized and reproducible methods for binding and quantitating protein targets. While signals from fluorescent analytes or sandwiches are typically captured, it has proven possible for immobilized aptamers to be uniquely coupled to amplification methods not available to protein reagents, thus allowing for protein-binding signals to be greatly amplified. Into the future, many of the biosensor methods described in this book can potentially be adapted to array formats, thus further expanding the utility of and applications for aptamer arrays.

  19. 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.

  20. 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.

  1. BAFF, APRIL, TWEAK, BCMA, TACI and Fn14 Proteins Are Related to Human Glioma Tumor Grade: Immunohistochemistry and Public Microarray Data Meta-Analysis

    PubMed Central

    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. PMID:24376672

  2. The Gaia-ESO Large Public Spectroscopic Survey

    NASA Astrophysics Data System (ADS)

    Randich, S.; Gilmore, G.; Gaia-ESO Consortium

    2013-12-01

    The Gaia-ESO Public Spectroscopic Survey has completed about one third of the data taking and continues to acquire high-quality spectroscopy, with both Giraffe and UVES, of representative samples of all Galactic stellar populations, including open clusters — young and old, nearby and distant, interior and exterior to the Sun — and field stars in the Galactic Halo, the thick Disc, the thin Disc and the Galactic Bulge. A large sample of stars in the Solar Neighbourhood, selected to include all possible ages and metallicities, is also being observed with UVES. This will be the first such large internally homogeneous study of the Milky Way stellar populations. Besides the intrinsic range of exciting scientific results, the Gaia-ESO Survey is also a pathfinder for future massive Gaia follow-up. Equally importantly, we are building an ESO-wide community of stellar spectroscopists, sharing, optimising, refining and cross-calibrating complementary approaches, strengths and experience. Internal Science Verification (SV) has started with several results demonstrating the huge potential of the survey and the first release of spectra to ESO has occurred.

  3. 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.…

  4. 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

  5. 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

  6. Microarrays, Integrated Analytical Systems

    NASA Astrophysics Data System (ADS)

    Combinatorial chemistry is used to find materials that form sensor microarrays. This book discusses the fundamentals, and then proceeds to the many applications of microarrays, from measuring gene expression (DNA microarrays) to protein-protein interactions, peptide chemistry, carbodhydrate chemistry, electrochemical detection, and microfluidics.

  7. 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.

  8. Living-Cell Microarrays

    PubMed Central

    Yarmush, Martin L.; King, Kevin R.

    2011-01-01

    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. PMID:19413510

  9. Microarrays in hematology.

    PubMed

    Walker, Josef; Flower, Darren; Rigley, Kevin

    2002-01-01

    Microarrays are fast becoming routine tools for the high-throughput analysis of gene expression in a wide range of biologic systems, including hematology. Although a number of approaches can be taken when implementing microarray-based studies, all are capable of providing important insights into biologic function. Although some technical issues have not been resolved, microarrays will continue to make a significant impact on hematologically important research. PMID:11753074

  10. An annotated cDNA library and microarray for large-scale gene-expression studies in the ant Solenopsis invicta

    PubMed Central

    Wang, John; Jemielity, Stephanie; Uva, Paolo; Wurm, Yannick; Gräff, Johannes; Keller, Laurent

    2007-01-01

    Ants display a range of fascinating behaviors, a remarkable level of intra-species phenotypic plasticity and many other interesting characteristics. Here we present a new tool to study the molecular mechanisms underlying these traits: a tentatively annotated expressed sequence tag (EST) resource for the fire ant Solenopsis invicta. From a normalized cDNA library we obtained 21,715 ESTs, which represent 11,864 putatively different transcripts with very diverse molecular functions. All ESTs were used to construct a cDNA microarray. PMID:17224046

  11. 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…

  12. 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

  13. 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

  14. Phenotypic MicroRNA Microarrays

    PubMed Central

    Kwon, Yong-Jun; Heo, Jin Yeong; Kim, Hi Chul; Kim, Jin Yeop; Liuzzi, Michel; Soloveva, Veronica

    2013-01-01

    Microarray technology has become a very popular approach in cases where multiple experiments need to be conducted repeatedly or done with a variety of samples. In our lab, we are applying our high density spots microarray approach to microscopy visualization of the effects of transiently introduced siRNA or cDNA on cellular morphology or phenotype. In this publication, we are discussing the possibility of using this micro-scale high throughput process to study the role of microRNAs in the biology of selected cellular models. After reverse-transfection of microRNAs and siRNA, the cellular phenotype generated by microRNAs regulated NF-κB expression comparably to the siRNA. The ability to print microRNA molecules for reverse transfection into cells is opening up the wide horizon for the phenotypic high content screening of microRNA libraries using cellular disease models.

  15. Quality Visualization of Microarray Datasets Using Circos

    PubMed Central

    Koch, Martin; Wiese, Michael

    2012-01-01

    Quality control and normalization is considered the most important step in the analysis of microarray data. At present there are various methods available for quality assessments of microarray datasets. However there seems to be no standard visualization routine, which also depicts individual microarray quality. Here we present a convenient method for visualizing the results of standard quality control tests using Circos plots. In these plots various quality measurements are drawn in a circular fashion, thus allowing for visualization of the quality and all outliers of each distinct array within a microarray dataset. The proposed method is intended for use with the Affymetrix Human Genome platform (i.e., GPL 96, GPL570 and GPL571). Circos quality measurement plots are a convenient way for the initial quality estimate of Affymetrix datasets that are stored in publicly available databases.

  16. Microarrays: an overview.

    PubMed

    Lee, Norman H; Saeed, Alexander I

    2007-01-01

    Gene expression microarrays are being used widely to address a myriad of complex biological questions. To gather meaningful expression data, it is crucial to have a firm understanding of the steps involved in the application of microarrays. The available microarray platforms are discussed along with their advantages and disadvantages. Additional considerations include study design, quality control and systematic assessment of microarray performance, RNA-labeling strategies, sample allocation, signal amplification schemes, defining the number of appropriate biological replicates, data normalization, statistical approaches to identify differentially regulated genes, and clustering algorithms for data visualization. In this chapter, the underlying principles regarding microarrays are reviewed, to serve as a guide when navigating through this powerful technology. PMID:17332646

  17. Microarrays--status and prospects.

    PubMed

    Venkatasubbarao, Srivatsa

    2004-12-01

    Microarrays have become an extremely important research tool for life science researchers and are also beginning to be used in diagnostic, treatment and monitoring applications. This article provides a detailed description of microarrays prepared by in situ synthesis, deposition using microspotting methods, nonplanar bead arrays, flow-through microarrays, optical fiber bundle arrays and nanobarcodes. The problems and challenges in the development of microarrays, development of standards and diagnostic microarrays are described. Tables summarizing the vendor list of various derivatized microarray surfaces, commercially sold premade microarrays, bead arrays and unique microarray products in development are also included. PMID:15542153

  18. Microarray Analysis in Glioblastomas.

    PubMed

    Bhawe, Kaumudi M; Aghi, Manish K

    2016-01-01

    Microarray analysis in glioblastomas is done using either cell lines or patient samples as starting material. A survey of the current literature points to transcript-based microarrays and immunohistochemistry (IHC)-based tissue microarrays as being the preferred methods of choice in cancers of neurological origin. Microarray analysis may be carried out for various purposes including the following: i. To correlate gene expression signatures of glioblastoma cell lines or tumors with response to chemotherapy (DeLay et al., Clin Cancer Res 18(10):2930-2942, 2012). ii. To correlate gene expression patterns with biological features like proliferation or invasiveness of the glioblastoma cells (Jiang et al., PLoS One 8(6):e66008, 2013). iii. To discover new tumor classificatory systems based on gene expression signature, and to correlate therapeutic response and prognosis with these signatures (Huse et al., Annu Rev Med 64(1):59-70, 2013; Verhaak et al., Cancer Cell 17(1):98-110, 2010). While investigators can sometimes use archived tumor gene expression data available from repositories such as the NCBI Gene Expression Omnibus to answer their questions, new arrays must often be run to adequately answer specific questions. Here, we provide a detailed description of microarray methodologies, how to select the appropriate methodology for a given question, and analytical strategies that can be used. Experimental methodology for protein microarrays is outside the scope of this chapter, but basic sample preparation techniques for transcript-based microarrays are included here. PMID:26113463

  19. Optimisation algorithms for microarray biclustering.

    PubMed

    Perrin, Dimitri; Duhamel, Christophe

    2013-01-01

    In providing simultaneous information on expression profiles for thousands of genes, microarray technologies have, in recent years, been largely used to investigate mechanisms of gene expression. Clustering and classification of such data can, indeed, highlight patterns and provide insight on biological processes. A common approach is to consider genes and samples of microarray datasets as nodes in a bipartite graphs, where edges are weighted e.g. based on the expression levels. In this paper, using a previously-evaluated weighting scheme, we focus on search algorithms and evaluate, in the context of biclustering, several variations of Genetic Algorithms. We also introduce a new heuristic "Propagate", which consists in recursively evaluating neighbour solutions with one more or one less active conditions. The results obtained on three well-known datasets show that, for a given weighting scheme, optimal or near-optimal solutions can be identified. PMID:24109756

  20. Retrieving relevant experiments: The case of microRNA microarrays.

    PubMed

    Açıcı, Koray; Terzi, Yunus Kasım; Oğul, Hasan

    2015-08-01

    Content-based retrieval of biological experiments in large public repositories is a recent challenge in computational biology and bioinformatics. The task is, in general, to search in a database using a query-by-example without any experimental meta-data annotation. Here, we consider a more specific problem that seeks a solution for retrieving relevant microRNA experiments from microarray repositories. A computational framework is proposed with this objective. The framework adapts a normal-uniform mixture model for identifying differentially expressed microRNAs in microarray profiling experiments. A rank-based thresholding scheme is offered to binarize real-valued experiment fingerprints based on differential expression. An effective similarity metric is introduced to compare categorical fingerprints, which in turn infers the relevance between two experiments. Two different views of experimental relevance are evaluated, one for disease association and another for embryonic germ layer, to discern the retrieval ability of the proposed model. To the best of our knowledge, the experiment retrieval task is investigated for the first time in the context of microRNA microarrays. PMID:26116091

  1. BRCA-Monet: a breast cancer specific drug treatment mode-of-action network for treatment effective prediction using large scale microarray database

    PubMed Central

    2013-01-01

    Background Connectivity map (cMap) is a recent developed dataset and algorithm for uncovering and understanding the treatment effect of small molecules on different cancer cell lines. It is widely used but there are still remaining challenges for accurate predictions. Method Here, we propose BRCA-MoNet, a network of drug mode of action (MoA) specific to breast cancer, which is constructed based on the cMap dataset. A drug signature selection algorithm fitting the characteristic of cMap data, a quality control scheme as well as a novel query algorithm based on BRCA-MoNet are developed for more effective prediction of drug effects. Result BRCA-MoNet was applied to three independent data sets obtained from the GEO database: Estrodial treated MCF7 cell line, BMS-754807 treated MCF7 cell line, and a breast cancer patient microarray dataset. In the first case, BRCA-MoNet could identify drug MoAs likely to share same and reverse treatment effect. In the second case, the result demonstrated the potential of BRCA-MoNet to reposition drugs and predict treatment effects for drugs not in cMap data. In the third case, a possible procedure of personalized drug selection is showcased. Conclusions The results clearly demonstrated that the proposed BRCA-MoNet approach can provide increased prediction power to cMap and thus will be useful for identification of new therapeutic candidates. Website: The web based application is developed and can be access through the following link http://compgenomics.utsa.edu/BRCAMoNet/ PMID:24564956

  2. 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.

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

    PubMed

    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. 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

  5. Biclustering of microarray data with MOSPO based on crowding distance

    PubMed Central

    Liu, Junwan; Li, Zhoujun; Hu, Xiaohua; Chen, Yiming

    2009-01-01

    Background High-throughput microarray technologies have generated and accumulated massive amounts of gene expression datasets that contain expression levels of thousands of genes under hundreds of different experimental conditions. The microarray datasets are usually presented in 2D matrices, where rows represent genes and columns represent experimental conditions. The analysis of such datasets can discover local structures composed by sets of genes that show coherent expression patterns under subsets of experimental conditions. It leads to the development of sophisticated algorithms capable of extracting novel and useful knowledge from a biomedical point of view. In the medical domain, these patterns are useful for understanding various diseases, and aid in more accurate diagnosis, prognosis, treatment planning, as well as drug discovery. Results In this work we present the CMOPSOB (Crowding distance based Multi-objective Particle Swarm Optimization Biclustering), a novel clustering approach for microarray datasets to cluster genes and conditions highly related in sub-portions of the microarray data. The objective of biclustering is to find sub-matrices, i.e. maximal subgroups of genes and subgroups of conditions where the genes exhibit highly correlated activities over a subset of conditions. Since these objectives are mutually conflicting, they become suitable candidates for multi-objective modelling. Our approach CMOPSOB is based on a heuristic search technique, multi-objective particle swarm optimization, which simulates the movements of a flock of birds which aim to find food. In the meantime, the nearest neighbour search strategies based on crowding distance and ϵ-dominance can rapidly converge to the Pareto front and guarantee diversity of solutions. We compare the potential of this methodology with other biclustering algorithms by analyzing two common and public datasets of gene expression profiles. In all cases our method can find localized structures

  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. 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. PMID:26039143

  8. Data Integration for Microarrays: Enhanced Inference for Gene Regulatory Networks

    PubMed Central

    Sîrbu, Alina; Crane, Martin; Ruskin, Heather J.

    2015-01-01

    Microarray technologies have been the basis of numerous important findings regarding gene expression in the few last decades. Studies have generated large amounts of data describing various processes, which, due to the existence of public databases, are widely available for further analysis. Given their lower cost and higher maturity compared to newer sequencing technologies, these data continue to be produced, even though data quality has been the subject of some debate. However, given the large volume of data generated, integration can help overcome some issues related, e.g., to noise or reduced time resolution, while providing additional insight on features not directly addressed by sequencing methods. Here, we present an integration test case based on public Drosophila melanogaster datasets (gene expression, binding site affinities, known interactions). Using an evolutionary computation framework, we show how integration can enhance the ability to recover transcriptional gene regulatory networks from these data, as well as indicating which data types are more important for quantitative and qualitative network inference. Our results show a clear improvement in performance when multiple datasets are integrated, indicating that microarray data will remain a valuable and viable resource for some time to come.

  9. 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. PMID:17567852

  10. 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…

  11. Expansion of the Public Library Card Catalog in a Large Library

    ERIC Educational Resources Information Center

    Hamann, Edmund

    1972-01-01

    Expanding a large card catalog is a complex process requiring careful planning of procedure, judicious allocation of labor, and simplified techniques. The conclusion is reached that a major catalog expansion can be undertaken economically and without disruption of regular technical and public service activities. (6 references) (Author)

  12. 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…

  13. 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…

  14. Anomaly-Based Change in Higher Education: The Case of a Large, Turkish Public University.

    ERIC Educational Resources Information Center

    Simsek, Hasan; Aytemiz, Dilkan

    This paper analyzes an institutional change in a large, Turkish public university, the Middle East Technical University (METU), by using an anomaly-based organizational change model. The model explains change as an organizational response to anomalies caused by internal and external organizational conditions. The study used a qualitative case…

  15. 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…

  16. 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...

  17. 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, ...

  18. PERFORMANCE CHARACTERISTICS OF 65-MER OLIGONUCLEOTIDE MICROARRAYS

    PubMed Central

    Lee, Myoyong; Xiang, Charlie C.; Trent, Jeffrey M.; Bittner, Michael L.

    2009-01-01

    Microarray fabrication using pre-synthesized long oligonucleotide is becoming increasingly important, but a study of large-scale array productions is not published yet. We addressed the issue of fabricating oligonucleotide microarrays by spotting commercial, pre-synthesized 65-mers with 5′ amines representing 7500 murine genes. Amine-modified oligonucleotides were immobilized on glass slides having aldehyde groups via transient Schiff base formation followed by reduction to produce a covalent conjugate. When RNA derived from the same source was used for Cy3 and Cy5 labeling and hybridized to the same array, signal intensities spanning three orders of magnitude were observed, and the coefficient of variation between the two channels for all spots was 8–10%. To ascertain the reproducibility of ratio determination of these arrays, two triplicate hybridizations (with fluorochrome reversal) comparing RNAs from a fibroblast (NIH3T3) and a breast cancer (JC) cell line were carried out. The 95% confidence interval for all spots in the six hybridizations was 0.60 – 1.66. This level of reproducibility allows use of the full range of pattern finding and discriminant analysis typically applied to cDNA microarrays. Further comparative testing was carried out with oligonucleotide microarrays, cDNA microarrays and RT-PCR assays to examine the comparability of results across these different methodologies. PMID:17617369

  19. Protein microarrays for parasite antigen discovery.

    PubMed

    Driguez, Patrick; Doolan, Denise L; Molina, Douglas M; Loukas, Alex; Trieu, Angela; Felgner, Phil L; McManus, Donald P

    2015-01-01

    The host serological profile to a parasitic infection, such as schistosomiasis, can be used to define potential vaccine and diagnostic targets. Determining the host antibody response using traditional approaches is hindered by the large number of putative antigens in any parasite proteome. Parasite protein microarrays offer the potential for a high-throughput host antibody screen to simplify this task. In order to construct the array, parasite proteins are selected from available genomic sequence and protein databases using bioinformatic tools. Selected open reading frames are PCR amplified, incorporated into a vector for cell-free protein expression, and printed robotically onto glass slides. The protein microarrays can be probed with antisera from infected/immune animals or humans and the antibody reactivity measured with fluorophore labeled antibodies on a confocal laser microarray scanner to identify potential targets for diagnosis or therapeutic or prophylactic intervention. PMID:25388117

  20. Applications of protein microarrays for biomarker discovery

    PubMed Central

    Ramachandran, Niroshan; Srivastava, Sanjeeva; LaBaer, Joshua

    2011-01-01

    The search for new biomarkers for diagnosis, prognosis and therapeutic monitoring of diseases continues in earnest despite dwindling success at finding novel reliable markers. Some of the current markers in clinical use do not provide optimal sensitivity and specificity, with the prostate cancer antigen (PSA) being one of many such examples. The emergence of proteomic techniques and systems approaches to study disease pathophysiology has rekindled the quest for new biomarkers. In particular the use of protein microarrays has surged as a powerful tool for large scale testing of biological samples. Approximately half the reports on protein microarrays have been published in the last two years especially in the area of biomarker discovery. In this review, we will discuss the application of protein microarray technologies that offer unique opportunities to find novel biomarkers. PMID:21136793

  1. 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.

  2. Microarray profiling for differential gene expression in PMSG-hCG stimulated preovulatory ovarian follicles of Chinese Taihu and Large White sows

    PubMed Central

    2011-01-01

    Background The Chinese Taihu is one of the most prolific pig breeds in the world, which farrows at least five more piglets per litter than Western pig breeds partly due to a greater ovulation rate. Variation of ovulation rate maybe associated with the differences in the transcriptome of Chinese Taihu and Large White ovaries. In order to understand the molecular basis of the greater ovulation rate of Chinese Taihu sows, expression profiling experiments were conducted to identify differentially expressed genes in ovarian follicles at the preovulatory stage of a PMSG-hCG stimulated estrous cycle from 3 Chinese Taihu and 3 Large White cycling sows by using the Affymetrix Porcine Genechip™. Results One hundred and thirty-three differentially expressed genes were identified between Chinese Taihu and Large White sows by using Affymetrix porcine GeneChip (p ≤ 0.05, Fold change ≥ 2 or ≤ 0.5). Gene Ontology (GO) analysis revealed that these genes belonged to the class of genes that participated in regulation of cellular process, regulation of biological process, biological regulation, developmental process, cell communication and signal transduction and so on. Significant differential expression of 6 genes including WNT10B and DKK2 in the WNT signaling pathway was detected. Real-time RT-PCR confirmed the expression pattern in seven of eight selected genes. A search of chromosomal location revealed that 92 differentially expressed transcripts located to the intervals of quantitative trait loci (QTLs) for reproduction traits. Furthermore, SNPs of two differentially expressed genes- BAX and BMPR1B were showed to be associated with litter size traits in Large White pigs and Chinese DIV line pigs (p ≤ 0.1 or p ≤ 0.05). Conclusions Our study detected many genes that showed differential expression between ovary follicles of two divergent breeds of pigs. Genes involved with regulation of cellular process, regulation of biological process, in addition to several genes not

  3. Photoelectrochemical synthesis of DNA microarrays

    PubMed Central

    Chow, Brian Y.; Emig, Christopher J.; Jacobson, Joseph M.

    2009-01-01

    Optical addressing of semiconductor electrodes represents a powerful technology that enables the independent and parallel control of a very large number of electrical phenomena at the solid-electrolyte interface. To date, it has been used in a wide range of applications including electrophoretic manipulation, biomolecule sensing, and stimulating networks of neurons. Here, we have adapted this approach for the parallel addressing of redox reactions, and report the construction of a DNA microarray synthesis platform based on semiconductor photoelectrochemistry (PEC). An amorphous silicon photoconductor is activated by an optical projection system to create virtual electrodes capable of electrochemically generating protons; these PEC-generated protons then cleave the acid-labile dimethoxytrityl protecting groups of DNA phosphoramidite synthesis reagents with the requisite spatial selectivity to generate DNA microarrays. Furthermore, a thin-film porous glass dramatically increases the amount of DNA synthesized per chip by over an order of magnitude versus uncoated glass. This platform demonstrates that PEC can be used toward combinatorial bio-polymer and small molecule synthesis. PMID:19706433

  4. Microarrays under the microscope.

    PubMed

    Wildsmith, S E; Elcock, F J

    2001-02-01

    Microarray technology is a rapidly advancing area, which is gaining popularity in many biological disciplines from drug target identification to predictive toxicology. Over the past few years, there has been a dramatic increase in the number of methods and techniques available for carrying out this form of gene expression analysis. The techniques and associated peripherals, such as slide types, deposition methods, robotics, and scanning equipment, are undergoing constant improvement, helping to drive the technology forward in terms of robustness and ease of use. These rapid developments, combined with the number of options available and the associated hyperbole, can prove daunting for the new user. This review aims to guide the researcher through the various steps of conducting microarray experiments, from initial strategy to analysing the data, with critical examination of the benefits and disadvantages along the way. PMID:11212888

  5. A hybrid imputation approach for microarray missing value estimation

    PubMed Central

    2015-01-01

    Background Missing data is an inevitable phenomenon in gene expression microarray experiments due to instrument failure or human error. It has a negative impact on performance of downstream analysis. Technically, most existing approaches suffer from this prevalent problem. Imputation is one of the frequently used methods for processing missing data. Actually many developments have been achieved in the research on estimating missing values. The challenging task is how to improve imputation accuracy for data with a large missing rate. Methods In this paper, induced by the thought of collaborative training, we propose a novel hybrid imputation method, called Recursive Mutual Imputation (RMI). Specifically, RMI exploits global correlation information and local structure in the data, captured by two popular methods, Bayesian Principal Component Analysis (BPCA) and Local Least Squares (LLS), respectively. Mutual strategy is implemented by sharing the estimated data sequences at each recursive process. Meanwhile, we consider the imputation sequence based on the number of missing entries in the target gene. Furthermore, a weight based integrated method is utilized in the final assembling step. Results We evaluate RMI with three state-of-art algorithms (BPCA, LLS, Iterated Local Least Squares imputation (ItrLLS)) on four publicly available microarray datasets. Experimental results clearly demonstrate that RMI significantly outperforms comparative methods in terms of Normalized Root Mean Square Error (NRMSE), especially for datasets with large missing rates and less complete genes. Conclusions It is noted that our proposed hybrid imputation approach incorporates both global and local information of microarray genes, which achieves lower NRMSE values against to any single approach only. Besides, this study highlights the need for considering the imputing sequence of missing entries for imputation methods. PMID:26330180

  6. 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

  7. Microarray data classified by artificial neural networks.

    PubMed

    Linder, Roland; Richards, Tereza; Wagner, Mathias

    2007-01-01

    Systems biology has enjoyed explosive growth in both the number of people participating in this area of research and the number of publications on the topic. The field of systems biology encompasses the in silico analysis of high-throughput data as provided by DNA or protein microarrays. Along with the increasing availability of microarray data, attention is focused on methods of analyzing the expression rates. One important type of analysis is the classification task, for example, distinguishing different types of cell functions or tumors. Recently, interest has been awakened toward artificial neural networks (ANN), which have many appealing characteristics such as an exceptional degree of accuracy. Nonlinear relationships or independence from certain assumptions regarding the data distribution are also considered. The current work reviews advantages as well as disadvantages of neural networks in the context of microarray analysis. Comparisons are drawn to alternative methods. Selected solutions are discussed, and finally algorithms for the effective combination of multiple ANNs are presented. The development of approaches to use ANN-processed microarray data applicable to run cell and tissue simulations may be slated for future investigation. PMID:18220242

  8. 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. PMID:26973235

  9. 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

  10. Tiling Microarray Analysis Tools

    SciTech Connect

    Nix, Davis Austin

    2005-05-04

    TiMAT is a package of 23 command line Java applications for use in the analysis of Affymetrix tiled genomic microarray data. TiMAT enables: 1) Rebuilding the genome annotation for entire tiled arrays (repeat filtering, chromosomal coordinate assignment). 2) Post processing of oligo intensity values (quantile normalization, median scaling, PMMM transformation), 3) Significance testing (Wilcoxon rank sum and signed rank tests, intensity difference and ratio tests) and Interval refinement (filtering based on multiple statistics, overlap comparisons), 4) Data visualization (detailed thumbnail/zoomed view with Interval Plots and data export to Affymetrix's Integrated Genome Browser) and Data reports (spreadsheet summaries and detailed profiles)

  11. Facilitating functional annotation of chicken microarray data

    PubMed Central

    2009-01-01

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

  12. Compressive Sensing DNA Microarrays

    PubMed Central

    2009-01-01

    Compressive sensing microarrays (CSMs) are DNA-based sensors that operate using group testing and compressive sensing (CS) principles. In contrast to conventional DNA microarrays, in which each genetic sensor is designed to respond to a single target, in a CSM, each sensor responds to a set of targets. We study the problem of designing CSMs that simultaneously account for both the constraints from CS theory and the biochemistry of probe-target DNA hybridization. An appropriate cross-hybridization model is proposed for CSMs, and several methods are developed for probe design and CS signal recovery based on the new model. Lab experiments suggest that in order to achieve accurate hybridization profiling, consensus probe sequences are required to have sequence homology of at least 80% with all targets to be detected. Furthermore, out-of-equilibrium datasets are usually as accurate as those obtained from equilibrium conditions. Consequently, one can use CSMs in applications in which only short hybridization times are allowed. PMID:19158952

  13. A Conceptual Framework for Allocation of Federally Stockpiled Ventilators During Large-Scale Public Health Emergencies.

    PubMed

    Zaza, Stephanie; Koonin, Lisa M; Ajao, Adebola; Nystrom, Scott V; Branson, Richard; Patel, Anita; Bray, Bruce; Iademarco, Michael F

    2016-01-01

    Some types of public health emergencies could result in large numbers of patients with respiratory failure who need mechanical ventilation. Federal public health planning has included needs assessment and stockpiling of ventilators. However, additional federal guidance is needed to assist states in further allocating federally supplied ventilators to individual hospitals to ensure that ventilators are shipped to facilities where they can best be used during an emergency. A major consideration in planning is a hospital's ability to absorb additional ventilators, based on available space and staff expertise. A simple pro rata plan that does not take these factors into account might result in suboptimal use or unused scarce resources. This article proposes a conceptual framework that identifies the steps in planning and an important gap in federal guidance regarding the distribution of stockpiled mechanical ventilators during an emergency. PMID:26828799

  14. 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. PMID:18563243

  15. 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. PMID:26614075

  16. Public health concerns for neighbors of large-scale swine production operations.

    PubMed

    Thu, K M

    2002-05-01

    This article provides a review and critical synthesis of research related to public health concerns for neighbors exposed to emissions from large-scale swine production operations. The rapid industrialization of pork production in the 1990s produced a generation of confined animal feeding operations (CAFOs) of a size previously unseen in the U.S. Recent research and results from federally sponsored scientific symposia consistently indicate that neighbors of large-scale swine CAFOs can experience health problems at significantly higher rates than controlled comparison populations. Symptoms experienced by swine CAFO neighbors are generally oriented toward irritation of the respiratory tract and are consistent with the types of symptoms among interior confinement workers thathave been well documented in the occupational health literature. However, additional exposure assessment research is required to elucidate the relationship of reported symptoms among swine CAFO neighbors and CAFO emissions. PMID:12046804

  17. 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

  18. Tiling Microarray Analysis Tools

    Energy Science and Technology Software Center (ESTSC)

    2005-05-04

    TiMAT is a package of 23 command line Java applications for use in the analysis of Affymetrix tiled genomic microarray data. TiMAT enables: 1) Rebuilding the genome annotation for entire tiled arrays (repeat filtering, chromosomal coordinate assignment). 2) Post processing of oligo intensity values (quantile normalization, median scaling, PMMM transformation), 3) Significance testing (Wilcoxon rank sum and signed rank tests, intensity difference and ratio tests) and Interval refinement (filtering based on multiple statistics, overlap comparisons),more » 4) Data visualization (detailed thumbnail/zoomed view with Interval Plots and data export to Affymetrix's Integrated Genome Browser) and Data reports (spreadsheet summaries and detailed profiles)« less

  19. 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? PMID:24581699

  20. Plant protein kinase substrates identification using protein microarrays.

    PubMed

    Ma, Shisong; Dinesh-Kumar, Savithramma P

    2015-01-01

    Protein kinases regulate signaling pathways by phosphorylating their targets. They play critical roles in plant signaling networks. Although many important protein kinases have been identified in plants, their substrates are largely unknown. We have developed and produced plant protein microarrays with more than 15,000 purified plant proteins. Here, we describe a detailed protocol to use these microarrays to identify plant protein kinase substrates via in vitro phosphorylation assays on these arrays. PMID:25930701

  1. 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.

  2. AMIC@: All MIcroarray Clusterings @ once

    PubMed Central

    Geraci, Filippo; Pellegrini, Marco; Renda, M. Elena

    2008-01-01

    The AMIC@ Web Server offers a light-weight multi-method clustering engine for microarray gene-expression data. AMIC@ is a highly interactive tool that stresses user-friendliness and robustness by adopting AJAX technology, thus allowing an effective interleaved execution of different clustering algorithms and inspection of results. Among the salient features AMIC@ offers, there are: (i) automatic file format detection, (ii) suggestions on the number of clusters using a variant of the stability-based method of Tibshirani et al. (iii) intuitive visual inspection of the data via heatmaps and (iv) measurements of the clustering quality using cluster homogeneity. Large data sets can be processed efficiently by selecting algorithms (such as FPF-SB and k-Boost), specifically designed for this purpose. In case of very large data sets, the user can opt for a batch-mode use of the system by means of the Clustering wizard that runs all algorithms at once and delivers the results via email. AMIC@ is freely available and open to all users with no login requirement at the following URL http://bioalgo.iit.cnr.it/amica. PMID:18477631

  3. AMIC@: All MIcroarray Clusterings @ once.

    PubMed

    Geraci, Filippo; Pellegrini, Marco; Renda, M Elena

    2008-07-01

    The AMIC@ Web Server offers a light-weight multi-method clustering engine for microarray gene-expression data. AMIC@ is a highly interactive tool that stresses user-friendliness and robustness by adopting AJAX technology, thus allowing an effective interleaved execution of different clustering algorithms and inspection of results. Among the salient features AMIC@ offers, there are: (i) automatic file format detection, (ii) suggestions on the number of clusters using a variant of the stability-based method of Tibshirani et al. (iii) intuitive visual inspection of the data via heatmaps and (iv) measurements of the clustering quality using cluster homogeneity. Large data sets can be processed efficiently by selecting algorithms (such as FPF-SB and k-Boost), specifically designed for this purpose. In case of very large data sets, the user can opt for a batch-mode use of the system by means of the Clustering wizard that runs all algorithms at once and delivers the results via email. AMIC@ is freely available and open to all users with no login requirement at the following URL http://bioalgo.iit.cnr.it/amica. PMID:18477631

  4. DNA microarrays in prostate cancer.

    PubMed

    Ho, Shuk-Mei; Lau, Kin-Mang

    2002-02-01

    DNA microarray technology provides a means to examine large numbers of molecular changes related to a biological process in a high throughput manner. This review discusses plausible utilities of this technology in prostate cancer research, including definition of prostate cancer predisposition, global profiling of gene expression patterns associated with cancer initiation and progression, identification of new diagnostic and prognostic markers, and discovery of novel patient classification schemes. The technology, at present, has only been explored in a limited fashion in prostate cancer research. Some hurdles to be overcome are the high cost of the technology, insufficient sample size and repeated experiments, and the inadequate use of bioinformatics. With the completion of the Human Genome Project and the advance of several highly complementary technologies, such as laser capture microdissection, unbiased RNA amplification, customized functional arrays (eg, single-nucleotide polymorphism chips), and amenable bioinformatics software, this technology will become widely used by investigators in the field. The large amount of novel, unbiased hypotheses and insights generated by this technology is expected to have a significant impact on the diagnosis, treatment, and prevention of prostate cancer. Finally, this review emphasizes existing, but currently underutilized, data-mining tools, such as multivariate statistical analyses, neural networking, and machine learning techniques, to stimulate wider usage. PMID:12084220

  5. 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. PMID:26134183

  6. Microarray platform for omics analysis

    NASA Astrophysics Data System (ADS)

    Mecklenburg, Michael; Xie, Bin

    2001-09-01

    Microarray technology has revolutionized genetic analysis. However, limitations in genome analysis has lead to renewed interest in establishing 'omic' strategies. As we enter the post-genomic era, new microarray technologies are needed to address these new classes of 'omic' targets, such as proteins, as well as lipids and carbohydrates. We have developed a microarray platform that combines self- assembling monolayers with the biotin-streptavidin system to provide a robust, versatile immobilization scheme. A hydrophobic film is patterned on the surface creating an array of tension wells that eliminates evaporation effects thereby reducing the shear stress to which biomolecules are exposed to during immobilization. The streptavidin linker layer makes it possible to adapt and/or develop microarray based assays using virtually any class of biomolecules including: carbohydrates, peptides, antibodies, receptors, as well as them ore traditional DNA based arrays. Our microarray technology is designed to furnish seamless compatibility across the various 'omic' platforms by providing a common blueprint for fabricating and analyzing arrays. The prototype microarray uses a microscope slide footprint patterned with 2 by 96 flat wells. Data on the microarray platform will be presented.

  7. RNAi microarray analysis in cultured mammalian cells.

    PubMed

    Mousses, Spyro; Caplen, Natasha J; Cornelison, Robert; Weaver, Don; Basik, Mark; Hautaniemi, Sampsa; Elkahloun, Abdel G; Lotufo, Roberto A; Choudary, Ashish; Dougherty, Edward R; Suh, Ed; Kallioniemi, Olli

    2003-10-01

    RNA interference (RNAi) mediated by small interfering RNAs (siRNAs) is a powerful new tool for analyzing gene knockdown phenotypes in living mammalian cells. To facilitate large-scale, high-throughput functional genomics studies using RNAi, we have developed a microarray-based technology for highly parallel analysis. Specifically, siRNAs in a transfection matrix were first arrayed on glass slides, overlaid with a monolayer of adherent cells, incubated to allow reverse transfection, and assessed for the effects of gene silencing by digital image analysis at a single cell level. Validation experiments with HeLa cells stably expressing GFP showed spatially confined, sequence-specific, time- and dose-dependent inhibition of green fluorescence for those cells growing directly on microspots containing siRNA targeting the GFP sequence. Microarray-based siRNA transfections analyzed with a custom-made quantitative image analysis system produced results that were identical to those from traditional well-based transfection, quantified by flow cytometry. Finally, to integrate experimental details, image analysis, data display, and data archiving, we developed a prototype information management system for high-throughput cell-based analyses. In summary, this RNAi microarray platform, together with ongoing efforts to develop large-scale human siRNA libraries, should facilitate genomic-scale cell-based analyses of gene function. PMID:14525932

  8. [Genomic medicine. Polymorphisms and microarray applications].

    PubMed

    Spalvieri, Mónica P; Rotenberg, Rosa G

    2004-01-01

    This update shows new concepts related to the significance of DNA variations among individuals, as well as to their detection by using a new technology. The sequencing of the human genome is only the beginning of what will enable us to understand genetic diversity. The unit of DNA variability is the polymorphism of a single nucleotide (SNP). At present, studies on SNPs are restricted to basic research but the large number of papers on this subject makes feasible their entrance into clinical practice. We illustrate here the use of SNPs as molecular markers in ethnical genotyping, gene expression in some diseases and as potential targets in pharmacological response, and also introduce the technology of arrays. Microarrays experiments allow the quantification and comparison of gene expression on a large scale, at the same time, by using special chips and array designs. Conventional methods provide data from up to 20 genes, while a single microarray may provide information about thousands of them simultaneously, leading to a more rapid and accurate genotyping. Biotechnology improvements will facilitate our knowledge of each gene sequence, the frequency and exact location of SNPs and their influence on cellular behavior. Although experimental efficiency and validity of results from microarrays are still controversial, the knowledge and characterization of a patient's genetic profile will lead, undoubtedly, to advances in prevention, diagnosis, prognosis and treatment of human diseases. PMID:15637833

  9. Integrating data from heterogeneous DNA microarray platforms.

    PubMed

    Valente, Eduardo; Rocha, Miguel

    2015-01-01

    DNA microarrays are one of the most used technologies for gene expression measurement. However, there are several distinct microarray platforms, from different manufacturers, each with its own measurement protocol, resulting in data that can hardly be compared or directly integrated. Data integration from multiple sources aims to improve the assertiveness of statistical tests, reducing the data dimensionality problem. The integration of heterogeneous DNA microarray platforms comprehends a set of tasks that range from the re-annotation of the features used on gene expression, to data normalization and batch effect elimination. In this work, a complete methodology for gene expression data integration and application is proposed, which comprehends a transcript-based re-annotation process and several methods for batch effect attenuation. The integrated data will be used to select the best feature set and learning algorithm for a brain tumor classification case study. The integration will consider data from heterogeneous Agilent and Affymetrix platforms, collected from public gene expression databases, such as The Cancer Genome Atlas and Gene Expression Omnibus. PMID:26673932

  10. 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.

  11. Dynamic biclustering of microarray data by multi-objective immune optimization

    PubMed Central

    2011-01-01

    Abstract Background Newly microarray technologies yield large-scale datasets. The microarray datasets are usually presented in 2D matrices, where rows represent genes and columns represent experimental conditions. Systematic analysis of those datasets provides the increasing amount of information, which is urgently needed in the post-genomic era. Biclustering, which is a technique developed to allow simultaneous clustering of rows and columns of a dataset, might be useful to extract more accurate information from those datasets. Biclustering requires the optimization of two conflicting objectives (residue and volume), and a multi-objective artificial immune system capable of performing a multi-population search. As a heuristic search technique, artificial immune systems (AISs) can be considered a new computational paradigm inspired by the immunological system of vertebrates and designed to solve a wide range of optimization problems. During biclustering several objectives in conflict with each other have to be optimized simultaneously, so multi-objective optimization model is suitable for solving biclustering problem. Results Based on dynamic population, this paper proposes a novel dynamic multi-objective immune optimization biclustering (DMOIOB) algorithm to mine coherent patterns from microarray data. Experimental results on two common and public datasets of gene expression profiles show that our approach can effectively find significant localized structures related to sets of genes that show consistent expression patterns across subsets of experimental conditions. The mined patterns present a significant biological relevance in terms of related biological processes, components and molecular functions in a species-independent manner. Conclusions The proposed DMOIOB algorithm is an efficient tool to analyze large microarray datasets. It achieves a good diversity and rapid convergence. PMID:21989068

  12. A centroid-based gene selection method for microarray data classification.

    PubMed

    Guo, Shun; Guo, Donghui; Chen, Lifei; Jiang, Qingshan

    2016-07-01

    For classification problems based on microarray data, the data typically contains a large number of irrelevant and redundant features. In this paper, a new gene selection method is proposed to choose the best subset of features for microarray data with the irrelevant and redundant features removed. We formulate the selection problem as a L1-regularized optimization problem, based on a newly defined linear discriminant analysis criterion. Instead of calculating the mean of the samples, a kernel-based approach is used to estimate the class centroid to define both the between-class separability and the within-class compactness for the criterion. Theoretical analysis indicates that the global optimal solution of the L1-regularized criterion can be reached with a general condition, on which an efficient algorithm is derived to the feature selection problem in a linear time complexity with respect to the number of features and the number of samples. The experimental results on ten publicly available microarray datasets demonstrate that the proposed method performs effectively and competitively compared with state-of-the-art methods. PMID:27056739

  13. 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.

  14. 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.

  15. 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

  16. The Perils of SNP Microarray Testing: Uncovering Unexpected Consanguinity

    PubMed Central

    Tarini, Beth A.; Konczal, Laura; Goldenberg, Aaron J.; Goldman, Edward B.; McCandless, Shawn E.

    2013-01-01

    Background While single nucleotide polymorphism (SNP) chromosomal microarrays identify areas of small genetic deletions/duplications, they can also reveal regions of homozygosity indicative of consanguinity. As more non-geneticists order SNP microarrays, they must prepare for the potential ethical, legal and social issues that result from revelation of unanticipated consanguinity. Patient An infant with multiple congenital anomalies underwent SNP microarray testing. Results The results of the SNP microarray revealed several large regions of homozygosity that indicated identity by descent most consistent with a second or third degree relative mating (e.g., uncle/ niece, half brother/sister, first cousins). Mother was not aware of the test's potential to reveal consanguinity. When informed of the test results, she reluctantly admitted to being raped by her half-brother around the time of conception. Conclusions During the pre-testing consent process, providers should inform parents that SNP microarray testing could reveal consanguinity. Providers must also understand the psychological implications, as well as the legal and moral obligations, that accompany SNP microarray results that indicate consanguinity. PMID:23827427

  17. Gene expression profiling in peanut using oligonucleotide microarrays

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  18. 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.

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

    DOE PAGESBeta

    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.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

    2015-01-01

    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

  2. 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.

  3. On the use of standards for microarray lossless image compression.

    PubMed

    Pinho, Armando J; Paiva, António R C; Neves, António J R

    2006-03-01

    The interest in methods that are able to efficiently compress microarray images is relatively new. This is not surprising, since the appearance and fast growth of the technology responsible for producing these images is also quite recent. In this paper, we present a set of compression results obtained with 49 publicly available images, using three image coding standards: lossless JPEG2000, JBIG, and JPEG-LS. We concluded that the compression technology behind JBIG seems to be the one that offers the best combination of compression efficiency and flexibility for microarray image compression. PMID:16532784

  4. Consensus gene regulatory networks: combining multiple microarray gene expression datasets

    NASA Astrophysics Data System (ADS)

    Peeling, Emma; Tucker, Allan

    2007-09-01

    In this paper we present a method for modelling gene regulatory networks by forming a consensus Bayesian network model from multiple microarray gene expression datasets. Our method is based on combining Bayesian network graph topologies and does not require any special pre-processing of the datasets, such as re-normalisation. We evaluate our method on a synthetic regulatory network and part of the yeast heat-shock response regulatory network using publicly available yeast microarray datasets. Results are promising; the consensus networks formed provide a broader view of the potential underlying network, obtaining an increased true positive rate over networks constructed from a single data source.

  5. Mining microarray expression data by literature profiling

    PubMed Central

    Chaussabel, Damien; Sher, Alan

    2002-01-01

    Background The rapidly expanding fields of genomics and proteomics have prompted the development of computational methods for managing, analyzing and visualizing expression data derived from microarray screening. Nevertheless, the lack of efficient techniques for assessing the biological implications of gene-expression data remains an important obstacle in exploiting this information. Results To address this need, we have developed a mining technique based on the analysis of literature profiles generated by extracting the frequencies of certain terms from thousands of abstracts stored in the Medline literature database. Terms are then filtered on the basis of both repetitive occurrence and co-occurrence among multiple gene entries. Finally, clustering analysis is performed on the retained frequency values, shaping a coherent picture of the functional relationship among large and heterogeneous lists of genes. Such data treatment also provides information on the nature and pertinence of the associations that were formed. Conclusions The analysis of patterns of term occurrence in abstracts constitutes a means of exploring the biological significance of large and heterogeneous lists of genes. This approach should contribute to optimizing the exploitation of microarray technologies by providing investigators with an interface between complex expression data and large literature resources. PMID:12372143

  6. Characteristic attributes in cancer microarrays.

    PubMed

    Sarkar, I N; Planet, P J; Bael, T E; Stanley, S E; Siddall, M; DeSalle, R; Figurski, D H

    2002-04-01

    Rapid advances in genome sequencing and gene expression microarray technologies are providing unprecedented opportunities to identify specific genes involved in complex biological processes, such as development, signal transduction, and disease. The vast amount of data generated by these technologies has presented new challenges in bioinformatics. To help organize and interpret microarray data, new and efficient computational methods are needed to: (1) distinguish accurately between different biological or clinical categories (e.g., malignant vs. benign), and (2) identify specific genes that play a role in determining those categories. Here we present a novel and simple method that exhaustively scans microarray data for unambiguous gene expression patterns. Such patterns of data can be used as the basis for classification into biological or clinical categories. The method, termed the Characteristic Attribute Organization System (CAOS), is derived from fundamental precepts in systematic biology. In CAOS we define two types of characteristic attributes ('pure' and 'private') that may exist in gene expression microarray data. We also consider additional attributes ('compound') that are composed of expression states of more than one gene that are not characteristic on their own. CAOS was tested on three well-known cancer DNA microarray data sets for its ability to classify new microarray samples. We found CAOS to be a highly accurate and robust class prediction technique. In addition, CAOS identified specific genes, not emphasized in other analyses, that may be crucial to the biology of certain types of cancer. The success of CAOS in this study has significant implications for basic research and the future development of reliable methods for clinical diagnostic tools. PMID:12474425

  7. Microarrayed Materials for Stem Cells

    PubMed Central

    Mei, Ying

    2013-01-01

    Stem cells hold remarkable promise for applications in disease modeling, cancer therapy and regenerative medicine. Despite the significant progress made during the last decade, designing materials to control stem cell fate remains challenging. As an alternative, materials microarray technology has received great attention because it allows for high throughput materials synthesis and screening at a reasonable cost. Here, we discuss recent developments in materials microarray technology and their applications in stem cell engineering. Future opportunities in the field will also be reviewed. PMID:24311967

  8. Immunoprofiling Using NAPPA Protein Microarrays

    PubMed Central

    Sibani, Sahar; LaBaer, Joshua

    2012-01-01

    Protein microarrays provide an efficient method to immunoprofile patients in an effort to rapidly identify disease immunosignatures. The validity of using autoantibodies in diagnosis has been demonstrated in type 1 diabetes, rheumatoid arthritis, and systemic lupus, and is now being strongly considered in cancer. Several types of protein microarrays exist including antibody and antigen arrays. In this chapter, we describe the immunoprofiling application for one type of antigen array called NAPPA (nucleic acids programmable protein array). We provide a guideline for setting up the screening study and designing protein arrays to maximize the likelihood of obtaining quality data. PMID:21370064

  9. Publications.

    ERIC Educational Resources Information Center

    Aviation/Space, 1980

    1980-01-01

    Presents a variety of publications available from government and nongovernment sources. The government publications are from the Federal Aviation Administration (FAA) and the National Aeronautics and Space Administration (NASA) and are designed for educators, students, and the public. (Author/SA)

  10. Microfluidic microarray systems and methods thereof

    DOEpatents

    West, Jay A. A.; Hukari, Kyle W.; Hux, Gary A.

    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.

  11. Microarray analysis: Uses and Limitations

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The use of microarray technology has exploded in resent years. All areas of biological research have found application for this powerful platform. From human disease studies to microbial detection systems, a plethora of uses for this technology are currently in place with new uses being developed ...

  12. Microarray Developed on Plastic Substrates.

    PubMed

    Bañuls, María-José; Morais, Sergi B; Tortajada-Genaro, Luis A; Maquieira, Ángel

    2016-01-01

    There is a huge potential interest to use synthetic polymers as versatile solid supports for analytical microarraying. Chemical modification of polycarbonate (PC) for covalent immobilization of probes, micro-printing of protein or nucleic acid probes, development of indirect immunoassay, and development of hybridization protocols are described and discussed. PMID:26614067

  13. 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

  14. 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.

  15. Modeling Retention at a Large Public University: Can At-Risk Students Be Identified Early Enough to Treat?

    ERIC Educational Resources Information Center

    Singell, Larry D.; Waddell, Glen R.

    2010-01-01

    We examine the extent to which readily available data at a large public university can be used to a priori identify at-risk students who may benefit from targeted retention efforts. Although it is possible to identify such students, there remains an inevitable tradeoff in any resource allocation between not treating the students who are likely to…

  16. 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…

  17. 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…

  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. Come and Stay a While: Does Financial Aid Effect Enrollment and Retention at a Large Public University?

    ERIC Educational Resources Information Center

    Singell, Larry D., Jr.

    Few studies have examined whether financial aid affects college retention. This paper models the decision to enroll and re-enroll in college, which yields a bivariate probit model that is estimated using detailed individual data from a large public university. The analysis uses the unique detail of institution-specific data to examine the effect…

  20. 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

  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 mRNAs.

    PubMed

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

    2003-04-01

    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-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. PMID:27563305

  3. 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

  4. 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,…

  5. Using The Affymetrix Wheat Microarray As An Oat Expression Platform

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Recent advances in sequencing have resulted in the sequence of a large number of plant expressed sequence tags (ESTs) to entire plant genomes. Using these EST sequences, oligonucleotide microarray chips have been developed for several species including barley (Hordeum vulgare), maize (Zea mays), ric...

  6. 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.

  7. A biomimetic algorithm for the improved detection of microarray features

    NASA Astrophysics Data System (ADS)

    Nicolau, Dan V., Jr.; Nicolau, Dan V.; Maini, Philip K.

    2007-02-01

    One the major difficulties of microarray technology relate to the processing of large and - importantly - error-loaded images of the dots on the chip surface. Whatever the source of these errors, those obtained in the first stage of data acquisition - segmentation - are passed down to the subsequent processes, with deleterious results. As it has been demonstrated recently that biological systems have evolved algorithms that are mathematically efficient, this contribution attempts to test an algorithm that mimics a bacterial-"patented" algorithm for the search of available space and nutrients to find, "zero-in" and eventually delimitate the features existent on the microarray surface.

  8. 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.

  9. An automated method for gridding in microarray images.

    PubMed

    Giannakeas, Nikolaos; Fotiadis, Dimitrios I; Politou, Anastasia S

    2006-01-01

    Microarray technology is a powerful tool for analyzing the expression of a large number of genes in parallel. A typical microarray image consists of a few thousands of spots which determine the level of gene expression in the sample. In this paper we propose a method which automatically addresses each spot area in the image. Initially, a preliminary segmentation of the image is produced using a template matching algorithm. Next, grid and spot finding are realized. The position of non-expressed spots is located and finally a Voronoi diagram is employed to fit the grid on the image. Our method has been evaluated in a set of five images consisting of 45960 spots, from the Stanford microarray database and the reported accuracy for spot detection was 93% PMID:17946343

  10. Exploring the feasibility of next-generation sequencing and microarray data meta-analysis

    PubMed Central

    Wu, Po-Yen; Phan, John H.; Wang, May D.

    2016-01-01

    Emerging next-generation sequencing (NGS) technology potentially resolves many issues that prevent widespread clinical use of gene expression microarrays. However, the number of publicly available NGS datasets is still smaller than that of microarrays. This paper explores the possibilities for combining information from both microarray and NGS gene expression datasets for the discovery of differentially expressed genes (DEGs). We evaluate several existing methods in detecting DEGs using individual datasets as well as combined NGS and microarray datasets. Results indicate that analysis of combined NGS and microarray data is feasible, but successful detection of DEGs may depend on careful selection of algorithms as well as on data normalization and pre-processing. PMID:22256102

  11. Caryoscope: An Open Source Java application for viewing microarray data in a genomic context

    PubMed Central

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

    2004-01-01

    Background 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. Results 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. Conclusion Caryoscope is a useful tool that can aid in the visualization, exploration and interpretation of microarray data in a genomic context. PMID:15488149

  12. 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

  13. Wagering on a large scale: Relationships between public gambling and game manipulations in two state lotteries

    PubMed Central

    Lyons, Charles A.; Ghezzi, Patrick M.

    1995-01-01

    Public wagering was examined in relation to game adjustments during the first 523 draws of Oregon's “Megabucks” lottery and the first 540 draws of Arizona's “The Pick” lottery. Oregon's lottery was modified five times during this period, and Arizona's lottery underwent four modifications. Public wagering was not related to decreases in the odds of winning in either state. Wagering increased in both states following the introduction of a minimum $1 million jackpot. Wagering also increased following a change in game frequency from weekly to semiweekly draws. Sales trends in both states suggest that over the period examined, larger jackpots were required to maintain previous levels of lottery play. These data suggest that public participation in gambling can be manipulated by state lottery commissions through adjustments in lottery contingencies. PMID:16795861

  14. Biclustering of time series microarray data.

    PubMed

    Meng, Jia; Huang, Yufei

    2012-01-01

    Clustering is a popular data exploration technique widely used in microarray data analysis. In this chapter, we review ideas and algorithms of bicluster and its applications in time series microarray analysis. We introduce first the concept and importance of biclustering and its different variations. We then focus our discussion on the popular iterative signature algorithm (ISA) for searching biclusters in microarray dataset. Next, we discuss in detail the enrichment constraint time-dependent ISA (ECTDISA) for identifying biologically meaningful temporal transcription modules from time series microarray dataset. In the end, we provide an example of ECTDISA application to time series microarray data of Kaposi's Sarcoma-associated Herpesvirus (KSHV) infection. PMID:22130875

  15. Multiple criteria optimization joint analyses of microarray experiments in lung cancer: from existing microarray data to new knowledge.

    PubMed

    Camacho-Cáceres, Katia I; Acevedo-Díaz, Juan C; Pérez-Marty, Lynn M; Ortiz, Michael; Irizarry, Juan; Cabrera-Ríos, Mauricio; Isaza, Clara E

    2015-12-01

    Microarrays can provide large amounts of data for genetic relative expression in illnesses of interest such as cancer in short time. These data, however, are stored and often times abandoned when new experimental technologies arrive. This work reexamines lung cancer microarray data with a novel multiple criteria optimization-based strategy aiming to detect highly differentially expressed genes. This strategy does not require any adjustment of parameters by the user and is capable to handle multiple and incommensurate units across microarrays. In the analysis, groups of samples from patients with distinct smoking habits (never smoker, current smoker) and different gender are contrasted to elicit sets of highly differentially expressed genes, several of which are already associated to lung cancer and other types of cancer. The list of genes is provided with a discussion of their role in cancer, as well as the possible research directions for each of them. PMID:26471143

  16. Routes to Roots: Acquiring Genealogical and Local History Materials in a Large Canadian Public Library

    ERIC Educational Resources Information Center

    McClelland, Arthur G. W.

    2004-01-01

    Using the London Room of the London Public Library in London, Ontario, Canada, as an example, this article will examine the nature of local collections, the sources and methods of acquiring genealogical and local history materials and the constraints related to such acquisitions. This article will also present a brief history of the London Room…

  17. Service Quality: An Unobtrusive Investigation of Interlibrary Loan in Large Public Libraries in Canada.

    ERIC Educational Resources Information Center

    Hebert, Francoise

    1994-01-01

    Describes a study that investigated the quality of interlibrary loan services in Canadian public libraries from the library's and the user's perspectives and then compared results. Measures of interlibrary loan performance are reviewed; an alternative conceptualization of service quality is discussed; and SERVQUAL, a measure of service quality, is…

  18. 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

  19. 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. PMID:27076594

  20. Self-Assembling Protein Microarrays

    NASA Astrophysics Data System (ADS)

    Ramachandran, Niroshan; Hainsworth, Eugenie; Bhullar, Bhupinder; Eisenstein, Samuel; Rosen, Benjamin; Lau, Albert Y.; C. Walter, Johannes; LaBaer, Joshua

    2004-07-01

    Protein microarrays provide a powerful tool for the study of protein function. However, they are not widely used, in part because of the challenges in producing proteins to spot on the arrays. We generated protein microarrays by printing complementary DNAs onto glass slides and then translating target proteins with mammalian reticulocyte lysate. Epitope tags fused to the proteins allowed them to be immobilized in situ. This obviated the need to purify proteins, avoided protein stability problems during storage, and captured sufficient protein for functional studies. We used the technology to map pairwise interactions among 29 human DNA replication initiation proteins, recapitulate the regulation of Cdt1 binding to select replication proteins, and map its geminin-binding domain.

  1. 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. PMID:26705309

  2. 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.

  3. Food Microbial Pathogen Detection and Analysis Using DNA Microarray Technologies

    PubMed Central

    Herold, Keith E.

    2008-01-01

    Abstract Culture-based methods used for microbial detection and identification are simple to use, relatively inexpensive, and sensitive. However, culture-based methods are too time-consuming for high-throughput testing and too tedious for analysis of samples with multiple organisms and provide little clinical information regarding the pathogen (e.g., antibiotic resistance genes, virulence factors, or strain subtype). DNA-based methods, such as polymerase chain reaction (PCR), overcome some these limitations since they are generally faster and can provide more information than culture-based methods. One limitation of traditional PCR-based methods is that they are normally limited to the analysis of a single pathogen, a small group of related pathogens, or a small number of relevant genes. Microarray technology enables a significant expansion of the capability of DNA-based methods in terms of the number of DNA sequences that can be analyzed simultaneously, enabling molecular identification and characterization of multiple pathogens and many genes in a single array assay. Microarray analysis of microbial pathogens has potential uses in research, food safety, medical, agricultural, regulatory, public health, and industrial settings. In this article, we describe the main technical elements of microarray technology and the application and potential use of DNA microarrays for food microbial analysis. PMID:18673074

  4. 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…

  5. 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…

  6. 78 FR 61227 - Public Assistance Cost Estimating Format for Large Projects

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-10-03

    ...-Bound Percentile of Factor C.1 (Preliminary Engineering Analysis Stage) Should Be Revised To More... Results for Each Large Project Estimated by the CEF 8. The Engineering and Design Services Curves (A and B... and Engineering AASHTO American Association of State and Highway Transportation Officials...

  7. 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

  8. Enzyme family-specific and activity-based screening of chemical libraries using enzyme microarrays.

    PubMed

    Funeriu, Daniel P; Eppinger, Jörg; Denizot, Lucile; Miyake, Masato; Miyake, Jun

    2005-05-01

    The potential of protein microarrays in high-throughput screening (HTS) still remains largely unfulfilled, essentially because of the difficulty of extracting meaningful, quantitative data from such experiments. In the particular case of enzyme microarrays, low-molecular-weight fluorescent affinity labels (FALs) can function as ideally suited activity probes of the microarrayed enzymes. FALs form covalent bonds with enzymes in an activity-dependent manner and therefore can be used to characterize enzyme activity at each enzyme's address, as predetermined by the microarraying process. Relying on this principle, we introduce herein thematic enzyme microarrays (TEMA). In a kinetic setup we used TEMAs to determine the full set of kinetic constants and the reaction mechanism between the microarrayed enzymes (the theme of the microarray) and a family-wide FAL. Based on this kinetic understanding, in an HTS setup we established the practical and theoretical methodology for quantitative, multiplexed determination of the inhibition profile of compounds from a chemical library against each microarrayed enzyme. Finally, in a validation setup, K(i)(app) values and inhibitor profiles were confirmed and refined. PMID:15821728

  9. 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

  10. Making a new technology work: the standardization and regulation of microarrays.

    PubMed

    Rogers, Susan; Cambrosio, Alberto

    2007-12-01

    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

  11. 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

  12. Coexpression analysis of human genes across many microarray data sets.

    PubMed

    Lee, Homin K; Hsu, Amy K; Sajdak, Jon; Qin, Jie; Pavlidis, Paul

    2004-06-01

    We present a large-scale analysis of mRNA coexpression based on 60 large human data sets containing a total of 3924 microarrays. We sought pairs of genes that were reliably coexpressed (based on the correlation of their expression profiles) in multiple data sets, establishing a high-confidence network of 8805 genes connected by 220,649 "coexpression links" that are observed in at least three data sets. Confirmed positive correlations between genes were much more common than confirmed negative correlations. We show that confirmation of coexpression in multiple data sets is correlated with functional relatedness, and show how cluster analysis of the network can reveal functionally coherent groups of genes. Our findings demonstrate how the large body of accumulated microarray data can be exploited to increase the reliability of inferences about gene function. PMID:15173114

  13. Integrated Amplification Microarrays for Infectious Disease Diagnostics

    PubMed Central

    Chandler, Darrell P.; Bryant, Lexi; Griesemer, Sara B.; Gu, Rui; Knickerbocker, Christopher; Kukhtin, Alexander; Parker, Jennifer; Zimmerman, Cynthia; George, Kirsten St.; Cooney, Christopher G.

    2012-01-01

    This overview describes microarray-based tests that combine solution-phase amplification chemistry and microarray hybridization within a single microfluidic chamber. The integrated biochemical approach improves microarray workflow for diagnostic applications by reducing the number of steps and minimizing the potential for sample or amplicon cross-contamination. Examples described herein illustrate a basic, integrated approach for DNA and RNA genomes, and a simple consumable architecture for incorporating wash steps while retaining an entirely closed system. It is anticipated that integrated microarray biochemistry will provide an opportunity to significantly reduce the complexity and cost of microarray consumables, equipment, and workflow, which in turn will enable a broader spectrum of users to exploit the intrinsic multiplexing power of microarrays for infectious disease diagnostics.

  14. 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

  15. 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…

  16. 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…

  17. 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

  18. 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...

  19. Living Cell Microarrays: An Overview of Concepts.

    PubMed

    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

  20. 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

  1. 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.

  2. Protein microarrays as tools for functional proteomics.

    PubMed

    LaBaer, Joshua; Ramachandran, Niroshan

    2005-02-01

    Protein microarrays present an innovative and versatile approach to study protein abundance and function at an unprecedented scale. Given the chemical and structural complexity of the proteome, the development of protein microarrays has been challenging. Despite these challenges there has been a marked increase in the use of protein microarrays to map interactions of proteins with various other molecules, and to identify potential disease biomarkers, especially in the area of cancer biology. In this review, we discuss some of the promising advances made in the development and use of protein microarrays. PMID:15701447

  3. Impact of microarray technology in nutrition and food research.

    PubMed

    Spielbauer, Bettina; Stahl, Frank

    2005-10-01

    Microarrays have become standard tools for gene expression profiling as the mRNA levels of a large number of genes can be measured in a single assay. Many technical aspects concerning microarray production and laboratory usage have been addressed in great detail, but it remains still crucial to establish this technology in new research fields such as human nutrition and food-related areas. The correlation between diet and inter-individual variation in gene expression is an important and relatively unexplored issue in human nutrition. Therefore, nutritionists changed their research field dramatically from epidemiology and physiology towards the "omics" sciences. Nutrigenomics as a field of research is based on the complete knowledge of the human genome and refers to the entire spectrum of human genes that determine the interactions of nutrition with the organism. Nutrigenetics is based on the inter-individual, genetically determined differences in metabolism. Nutrigenomics and nutrigenetics carry the hope that individualized diet can improve human health and prevent nutrition-related diseases. In this article we give an overview of current DNA and protein microarray techniques (including fabrication, experimental procedure and data analysis), we describe their applications to nutrition and food research and point out the limitations, problems and pitfalls of microarray experiments. PMID:16189797

  4. Single nucleotide polymorphism genotyping using BeadChip microarrays.

    PubMed

    Lambert, Gilliam; Tsinajinnie, Darwin; Duggan, David

    2013-07-01

    The genotyping of single nucleotide polymorphisms (SNPs) has successfully contributed to the study of complex diseases more than any other technology to date. Genome-wide association studies (GWAS) using 10,000s to >1,000,000 SNPs have identified 1000s of statistically significant SNPs pertaining to 17 different human disease and trait categories. Post-GWAS fine-mapping studies using 10,000s to 100,000s SNPs on a microarray have narrowed the region of interest for many of these GWAS findings; in addition, independent signals within the original GWAS region have been identified. Focused content, SNP-based microarrays such as the human exome, for example, have too been used successfully to identify novel disease associations. Success has come to studies where 100s to 10,000s (mostly) to >100,000 samples were genotyped. For the time being, SNP-based microarrays remain cost-effective especially when studying large numbers of samples compared to other "genotyping" technologies including next generation sequencing. In this unit, protocols for manual (LIMS-free), semi-manual, and automated processing of BeadChip microarrays are presented. Lower throughput studies will find value in the manual and semi-manual protocols, while all types of studies--low-, medium-, and high-throughput--will find value in the semi-manual and automated protocols. PMID:23853082

  5. A Microarray-Based Gene Expression Analysis to Identify Diagnostic Biomarkers for Unknown Primary Cancer

    PubMed Central

    Kurahashi, Issei; Fujita, Yoshihiko; Arao, Tokuzo; Kurata, Takayasu; Koh, Yasuhiro; Sakai, Kazuko; Matsumoto, Koji; Tanioka, Maki; Takeda, Koji; Takiguchi, Yuichi; Yamamoto, Nobuyuki; Tsuya, Asuka; Matsubara, Nobuaki; Mukai, Hirofumi; Minami, Hironobu; Chayahara, Naoko; Yamanaka, Yasuhiro; Miwa, Keisuke; Takahashi, Shin; Takahashi, Shunji; Nakagawa, Kazuhiko; Nishio, Kazuto

    2013-01-01

    Background The biological basis for cancer of unknown primary (CUP) at the molecular level remains largely unknown, with no evidence of whether a common biological entity exists. Here, we assessed the possibility of identifying a common diagnostic biomarker for CUP using a microarray gene expression analysis. Methods Tumor mRNA samples from 60 patients with CUP were analyzed using the Affymetrix U133A Plus 2.0 GeneChip and were normalized by asinh (hyperbolic arc sine) transformation to construct a mean gene-expression profile specific to CUP. A gene-expression profile specific to non-CUP group was constructed using publicly available raw microarray datasets. The t-tests were performed to compare the CUP with non-CUP groups and the top 59 CUP specific genes with the highest fold change were selected (p-value<0.001). Results Among the 44 genes that were up-regulated in the CUP group, 6 genes for ribosomal proteins were identified. Two of these genes (RPS7 and RPL11) are known to be involved in the Mdm2–p53 pathway. We also identified several genes related to metastasis and apoptosis, suggesting a biological attribute of CUP. Conclusions The protein products of the up-regulated and down-regulated genes identified in this study may be clinically useful as unique biomarkers for CUP. PMID:23671674

  6. 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...

  7. 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...

  8. 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

  9. 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. PMID:25968554

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

    PubMed Central

    Thompson, Jeffrey A.; Tan, Jie

    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 log2 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. PMID:26844019

  11. 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. PMID:26844019

  12. Clinical Utility of Microarrays: Current Status, Existing Challenges and Future Outlook

    PubMed Central

    Li, Xinmin; Quigg, Richard J; Zhou, Jian; Gu, Weikuan; Nagesh Rao, P; Reed, Elaine F

    2008-01-01

    Microarray-based clinical tests have become powerful tools in the diagnosis and treatment of diseases. In contrast to traditional DNA-based tests that largely focus on single genes associated with rare conditions, microarray-based tests are ideal for the study of diseases with underlying complex genetic causes. Several microarray based tests have been translated into clinical practice such as MammaPrint and AmpliChip CYP450. Additional cancer-related microarray-based tests are either in the process of FDA review or under active development, including Tissue of Tumor Origin and AmpliChip p53. All diagnostic microarray testing is ordered by physicians and tested by a Clinical Laboratories Improvement Amendment-certified (CLIA) reference laboratory. Recently, companies offering consumer based microarray testing have emerged. Individuals can order tests online and service providers deliver the results directly to the clients via a password-protected secure website. Navigenics, 23andMe and deCODE Genetics represent pioneering companies in this field. Although the progress of these microarray-based tests is extremely encouraging with the potential to revolutionize the recognition and treatment of common diseases, these tests are still in their infancy and face technical, clinical and marketing challenges. In this article, we review microarray-based tests which are currently approved or under review by the FDA, as well as the consumer-based testing. We also provide a summary of the challenges and strategic solutions in the development and clinical use of the microarray-based tests. Finally, we present a brief outlook for the future of microarray-based clinical applications. PMID:19506735

  13. 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…

  14. 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.

  15. Advances in spotted microarray resources for expression profiling.

    PubMed

    Lyons, Paul

    2003-04-01

    The new millennium has ushered in a new era in human biology. The elucidation of the human genome sequence, together with those of model organisms, provides us with an unprecedented insight into the makeup of our genetic blueprint. The challenge now is to figure out how all the constituent pieces fit together to form the whole picture, and the consequences of what happens when the process goes awry. One experimental tool that has the potential to provide enormous insights into this complex process is expression profiling using microarrays. The past few years have seen a considerable growth in the availability and use of microarrays. Fuelled in part by the many genome projects currently underway, there has been a large increase in the number of organisms for which microarray reagents are available from both commercial and academic sources. In addition to the increasing number of genome-wide probe sets that are available, a significant amount of attention has been focussed on generating more targeted probe sets that focus in on specific pathways or biological processes. Finally, the microarray field is starting to see a shift away from the use of cDNAs or polymerase chain reaction (PCR) products as probes towards the use of 50-70mer oligonucleotide probes with all of the potential advantages that they offer. The aim of this review is to provide an overview of what is currently available in terms of spotted microarray reagents both with respect to pre-made arrays and to probe sets available for arraying. PMID:15239940

  16. 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

  17. Review of the literature examining the correlation among DNA microarray technologies

    PubMed Central

    Yauk, Carole L; Berndt, M Lynn

    2007-01-01

    DNA microarray technologies are used in a variety of biological disciplines. The diversity of platforms and analytical methods employed has raised concerns over the reliability, reproducibility and correlation of data produced across the different approaches. Initial investigations (years 2000–2003) found discrepancies in the gene expression measures produced by different microarray technologies. Increasing knowledge and control of the factors that result in poor correlation among the technologies has led to much higher levels of correlation among more recent publications (years 2004 to present). Here, we review the studies examining the correlation among microarray technologies. We find that with improvements in the technology (optimization and standardization of methods, including data analysis) and annotation, analysis across platforms yields highly correlated and reproducible results. We suggest several key factors that should be controlled in comparing across technologies, and are good microarray practice in general. Environ. Mol. Mutagen. 48:380–394, 2007. © 2007 Wiley-Liss, Inc. PMID:17370338

  18. Protein-Based Microarray for the Detection of Pathogenic Bacteria

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Microarrays have been used for gene expression and protein interaction studies, but recently, multianalyte diagnostic assays have employed the microarray platform. We developed a microarray immunoassay for bacteria, with biotinylated capture antibodies on streptavidin slides. To complete the fluor...

  19. 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

  20. ArrayPipe: a flexible processing pipeline for microarray data.

    PubMed

    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

    2004-07-01

    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

  1. DNA Microarrays for Identifying Fishes

    PubMed Central

    Nölte, M.; Weber, H.; Silkenbeumer, N.; Hjörleifsdottir, S.; Hreggvidsson, G. O.; Marteinsson, V.; Kappel, K.; Planes, S.; Tinti, F.; Magoulas, A.; Garcia Vazquez, E.; Turan, C.; Hervet, C.; Campo Falgueras, D.; Antoniou, A.; Landi, M.; Blohm, D.

    2008-01-01

    In many cases marine organisms and especially their diverse developmental stages are difficult to identify by morphological characters. DNA-based identification methods offer an analytically powerful addition or even an alternative. In this study, a DNA microarray has been developed to be able to investigate its potential as a tool for the identification of fish species from European seas based on mitochondrial 16S rDNA sequences. Eleven commercially important fish species were selected for a first prototype. Oligonucleotide probes were designed based on the 16S rDNA sequences obtained from 230 individuals of 27 fish species. In addition, more than 1200 sequences of 380 species served as sequence background against which the specificity of the probes was tested in silico. Single target hybridisations with Cy5-labelled, PCR-amplified 16S rDNA fragments from each of the 11 species on microarrays containing the complete set of probes confirmed their suitability. True-positive, fluorescence signals obtained were at least one order of magnitude stronger than false-positive cross-hybridisations. Single nontarget hybridisations resulted in cross-hybridisation signals at approximately 27% of the cases tested, but all of them were at least one order of magnitude lower than true-positive signals. This study demonstrates that the 16S rDNA gene is suitable for designing oligonucleotide probes, which can be used to differentiate 11 fish species. These data are a solid basis for the second step to create a “Fish Chip” for approximately 50 fish species relevant in marine environmental and fisheries research, as well as control of fisheries products. PMID:18270778

  2. Using Pre-existing Microarray Datasets to Increase Experimental Power: Application to Insulin Resistance

    PubMed Central

    Daigle, Bernie J.; Deng, Alicia; McLaughlin, Tracey; Cushman, Samuel W.; Cam, Margaret C.; Reaven, Gerald; Tsao, Philip S.; Altman, Russ B.

    2010-01-01

    Although they have become a widely used experimental technique for identifying differentially expressed (DE) genes, DNA microarrays are notorious for generating noisy data. A common strategy for mitigating the effects of noise is to perform many experimental replicates. This approach is often costly and sometimes impossible given limited resources; thus, analytical methods are needed which increase accuracy at no additional cost. One inexpensive source of microarray replicates comes from prior work: to date, data from hundreds of thousands of microarray experiments are in the public domain. Although these data assay a wide range of conditions, they cannot be used directly to inform any particular experiment and are thus ignored by most DE gene methods. We present the SVD Augmented Gene expression Analysis Tool (SAGAT), a mathematically principled, data-driven approach for identifying DE genes. SAGAT increases the power of a microarray experiment by using observed coexpression relationships from publicly available microarray datasets to reduce uncertainty in individual genes' expression measurements. We tested the method on three well-replicated human microarray datasets and demonstrate that use of SAGAT increased effective sample sizes by as many as 2.72 arrays. We applied SAGAT to unpublished data from a microarray study investigating transcriptional responses to insulin resistance, resulting in a 50% increase in the number of significant genes detected. We evaluated 11 (58%) of these genes experimentally using qPCR, confirming the directions of expression change for all 11 and statistical significance for three. Use of SAGAT revealed coherent biological changes in three pathways: inflammation, differentiation, and fatty acid synthesis, furthering our molecular understanding of a type 2 diabetes risk factor. We envision SAGAT as a means to maximize the potential for biological discovery from subtle transcriptional responses, and we provide it as a freely available

  3. 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

  4. 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. PMID:27190571

  5. 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

  6. 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. PMID:25863787

  7. 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

  8. Pipeline for macro- and microarray analyses.

    PubMed

    Vicentini, R; Menossi, M

    2007-05-01

    The pipeline for macro- and microarray analyses (PMmA) is a set of scripts with a web interface developed to analyze DNA array data generated by array image quantification software. PMmA is designed for use with single- or double-color array data and to work as a pipeline in five classes (data format, normalization, data analysis, clustering, and array maps). It can also be used as a plugin in the BioArray Software Environment, an open-source database for array analysis, or used in a local version of the web service. All scripts in PMmA were developed in the PERL programming language and statistical analysis functions were implemented in the R statistical language. Consequently, our package is a platform-independent software. Our algorithms can correctly select almost 90% of the differentially expressed genes, showing a superior performance compared to other methods of analysis. The pipeline software has been applied to 1536 expressed sequence tags macroarray public data of sugarcane exposed to cold for 3 to 48 h. PMmA identified thirty cold-responsive genes previously unidentified in this public dataset. Fourteen genes were up-regulated, two had a variable expression and the other fourteen were down-regulated in the treatments. These new findings certainly were a consequence of using a superior statistical analysis approach, since the original study did not take into account the dependence of data variability on the average signal intensity of each gene. The web interface, supplementary information, and the package source code are available, free, to non-commercial users at http://ipe.cbmeg.unicamp.br/pub/PMmA. PMID:17464422

  9. 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.

  10. 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

  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. 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.

  13. 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

  14. Microarray: an approach for current drug targets.

    PubMed

    Gomase, Virendra S; Tagore, Somnath; Kale, Karbhari V

    2008-03-01

    Microarrays are a powerful tool has multiple applications both in clinical and cellular and molecular biology arenas. Early assessment of the probable biological importance of drug targets, pharmacogenomics, toxicogenomics and single nucleotide polymorphisms (SNPs). A list of new drug candidates along with proposed targets for intervention is described. Recent advances in the knowledge of microarrays analysis of organisms and the availability of the genomics sequences provide a wide range of novel targets for drug design. This review gives different process of microarray technologies; methods for comparative gene expression study, applications of microarrays in medicine and pharmacogenomics and current drug targets in research, which are relevant to common diseases as they relate to clinical and future perspectives. PMID:18336225

  15. 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. PMID:25971913

  16. Comprehensive network analysis of anther-expressed genes in rice by the combination of 33 laser microdissection and 143 spatiotemporal microarrays.

    PubMed

    Aya, Koichiro; Suzuki, Go; Suwabe, Keita; Hobo, Tokunori; Takahashi, Hirokazu; Shiono, Katsuhiro; Yano, Kentaro; Tsutsumi, Nobuhiro; Nakazono, Mikio; Nagamura, Yoshiaki; Matsuoka, Makoto; Watanabe, Masao

    2011-01-01

    Co-expression networks systematically constructed from large-scale transcriptome data reflect the interactions and functions of genes with similar expression patterns and are a powerful tool for the comprehensive understanding of biological events and mining of novel genes. In Arabidopsis (a model dicot plant), high-resolution co-expression networks have been constructed from very large microarray datasets and these are publicly available as online information resources. However, the available transcriptome data of rice (a model monocot plant) have been limited so far, making it difficult for rice researchers to achieve reliable co-expression analysis. In this study, we performed co-expression network analysis by using combined 44 K agilent microarray datasets of rice, which consisted of 33 laser microdissection (LM)-microarray datasets of anthers, and 143 spatiotemporal transcriptome datasets deposited in RicexPro. The entire data of the rice co-expression network, which was generated from the 176 microarray datasets by the Pearson correlation coefficient (PCC) method with the mutual rank (MR)-based cut-off, contained 24,258 genes and 60,441 genes pairs. Using these datasets, we constructed high-resolution co-expression subnetworks of two specific biological events in the anther, "meiosis" and "pollen wall synthesis". The meiosis network contained many known or putative meiotic genes, including genes related to meiosis initiation and recombination. In the pollen wall synthesis network, several candidate genes involved in the sporopollenin biosynthesis pathway were efficiently identified. Hence, these two subnetworks are important demonstrations of the efficiency of co-expression network analysis in rice. Our co-expression analysis included the separated transcriptomes of pollen and tapetum cells in the anther, which are able to provide precise information on transcriptional regulation during male gametophyte development in rice. The co-expression network data

  17. Comprehensive Network Analysis of Anther-Expressed Genes in Rice by the Combination of 33 Laser Microdissection and 143 Spatiotemporal Microarrays

    PubMed Central

    Takahashi, Hirokazu; Shiono, Katsuhiro; Yano, Kentaro; Tsutsumi, Nobuhiro; Nakazono, Mikio; Nagamura, Yoshiaki; Matsuoka, Makoto; Watanabe, Masao

    2011-01-01

    Co-expression networks systematically constructed from large-scale transcriptome data reflect the interactions and functions of genes with similar expression patterns and are a powerful tool for the comprehensive understanding of biological events and mining of novel genes. In Arabidopsis (a model dicot plant), high-resolution co-expression networks have been constructed from very large microarray datasets and these are publicly available as online information resources. However, the available transcriptome data of rice (a model monocot plant) have been limited so far, making it difficult for rice researchers to achieve reliable co-expression analysis. In this study, we performed co-expression network analysis by using combined 44 K agilent microarray datasets of rice, which consisted of 33 laser microdissection (LM)-microarray datasets of anthers, and 143 spatiotemporal transcriptome datasets deposited in RicexPro. The entire data of the rice co-expression network, which was generated from the 176 microarray datasets by the Pearson correlation coefficient (PCC) method with the mutual rank (MR)-based cut-off, contained 24,258 genes and 60,441 genes pairs. Using these datasets, we constructed high-resolution co-expression subnetworks of two specific biological events in the anther, “meiosis” and “pollen wall synthesis”. The meiosis network contained many known or putative meiotic genes, including genes related to meiosis initiation and recombination. In the pollen wall synthesis network, several candidate genes involved in the sporopollenin biosynthesis pathway were efficiently identified. Hence, these two subnetworks are important demonstrations of the efficiency of co-expression network analysis in rice. Our co-expression analysis included the separated transcriptomes of pollen and tapetum cells in the anther, which are able to provide precise information on transcriptional regulation during male gametophyte development in rice. The co-expression network

  18. 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…

  19. 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.

  20. 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

  1. Autonomous system for Web-based microarray image analysis.

    PubMed

    Bozinov, Daniel

    2003-12-01

    Software-based feature extraction from DNA microarray images still requires human intervention on various levels. Manual adjustment of grid and metagrid parameters, precise alignment of superimposed grid templates and gene spots, or simply identification of large-scale artifacts have to be performed beforehand to reliably analyze DNA signals and correctly quantify their expression values. Ideally, a Web-based system with input solely confined to a single microarray image and a data table as output containing measurements for all gene spots would directly transform raw image data into abstracted gene expression tables. Sophisticated algorithms with advanced procedures for iterative correction function can overcome imminent challenges in image processing. Herein is introduced an integrated software system with a Java-based interface on the client side that allows for decentralized access and furthermore enables the scientist to instantly employ the most updated software version at any given time. This software tool is extended from PixClust as used in Extractiff incorporated with Java Web Start deployment technology. Ultimately, this setup is destined for high-throughput pipelines in genome-wide medical diagnostics labs or microarray core facilities aimed at providing fully automated service to its users. PMID:15376911

  2. 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

  3. Genopal™: A Novel Hollow Fibre Array for Focused Microarray Analysis

    PubMed Central

    Okuzaki, Daisuke; Fukushima, Tatsunobu; Tougan, Takahiro; Ishii, Tomonori; Kobayashi, Shigeto; Yoshizaki, Kazuyuki; Akita, Takashi; Nojima, Hiroshi

    2010-01-01

    Expression profiling of target genes in patient blood is a powerful tool for RNA diagnosis. Here, we describe Genopal™, a novel platform ideal for efficient focused microarray analysis. Genopal™, which consists of gel-filled fibres, is advantageous for high-quality mass production via large-scale slicing of the Genopal™ block. We prepared two arrays, infectant and autoimmunity, that provided highly reliable data in terms of repetitive scanning of the same and/or distinct microarrays. Moreover, we demonstrated that Genopal™ had sensitivity sufficient to yield signals in short hybridization times (0.5 h). Application of the autoimmunity array to blood samples allowed us to identify an expression pattern specific to Takayasu arteritis based on the Spearman rank correlation by comparing the reference profile with those of several autoimmune diseases and healthy volunteers (HVs). The comparison of these data with those obtained by other methods revealed that they exhibited similar expression profiles of many target genes. Taken together, these data demonstrate that Genopal™ is an advantageous platform for focused microarrays with regard to its low cost, rapid results and reliable quality. PMID:21059707

  4. Chromosome microarrays in diagnostic testing: interpreting the genomic data.

    PubMed

    Peters, Greg B; Pertile, Mark D

    2014-01-01

    DNA-based Chromosome MicroArrays (CMAs) are now well established as diagnostic tools in clinical genetics laboratories. Over the last decade, the primary application of CMAs has been the genome-wide detection of a particular class of mutation known as copy number variants (CNVs). Since 2010, CMA testing has been recommended as a first-tier test for detection of CNVs associated with intellectual disability, autism spectrum disorders, and/or multiple congenital anomalies…in the post-natal setting. CNVs are now regarded as pathogenic in 14-18 % of patients referred for these (and related) disorders.Through consideration of clinical examples, and several microarray platforms, we attempt to provide an appreciation of microarray diagnostics, from the initial inspection of the microarray data, to the composing of the patient report. In CMA data interpretation, a major challenge comes from the high frequency of clinically irrelevant CNVs observed within "patient" and "normal" populations. As might be predicted, the more common and clinically insignificant CNVs tend to be the smaller ones <100 kb in length, involving few or no known genes. However, this relationship is not at all straightforward: CNV length and gene content are only very imperfect indicators of CNV pathogenicity. Presently, there are no reliable means of separating, a priori, the benign from the pathological CNV classes.This chapter also considers sources of technical "noise" within CMA data sets. Some level of noise is inevitable in diagnostic genomics, given the very large number of data points generated in any one test. Noise further limits CMA resolution, and some miscalling of CNVs is unavoidable. In this, there is no ideal solution, but various strategies for handling noise are available. Even without solutions, consideration of these diagnostic problems per se is informative, as they afford critical insights into the biological and technical underpinnings of CNV discovery. These are indispensable

  5. Variations in the Quality of Care at Large Public Hospitals in Beijing, China: A Condition-Based Outcome Approach

    PubMed Central

    Xu, Ye; Liu, Yuanli; Shu, Ting; Yang, Wei; Liang, Minghui

    2015-01-01

    Background Public hospitals deliver over ninety percent of all outpatient and inpatient services in China. Their quality is graded into three levels (A, B, and C) largely based on structural resources, but empirical evidence on the quality of process and outcome of care is extremely scarce. As expectations for quality care rise with higher living standards and cost of care, such evidence is urgently needed and vital to improve care and to inform future health reforms. Methods We compiled and analyzed a multicenter database of over 4 million inpatient discharge summary records to provide a comprehensive assessment of the level and variations in clinical outcomes of hospitalization at 39 tertiary hospitals in Beijing. We assessed six outcome measures of clinical quality: in-hospital mortality rates (RSMR) for AMI, stroke, pneumonia and CABG, post-procedural complication rate (RS-CR), and failure-to-rescue rate (RS-FTR). The measures were adjusted for pre-admission patient case-mix using indirect standardization method with hierarchical linear mixed models. Results We found good overall quality with large variations by hospital and condition (mean/range, in %): RSMR-AMI: 6.23 (2.37–14.48), RSMR-stroke: 4.18 (3.58–4.44), RSMR-pneumonia: 7.78 (7.20–8.59), RSMR-CABG: 1.93 (1.55–2.23), RS-CR: 11.38 (9.9–12.88), and RS-FTR: 6.41 (5.17–7.58). Hospital grade was not significantly associated with any risk-adjusted outcome measures. Conclusions Going to a higher grade public hospital does not always lead to better patient outcome because hospital grade only contains information about hospital structural resources. A hospital report card with some outcome measures of quality would provide valuable information to patients in choosing providers, and for regulators to identify gaps in health care quality. Reducing the variations in clinical practice and patient outcome should be a focus for policy makers in the next round of health sector reforms in China. PMID

  6. A Visual Aid for Statisticians and Molecular Biologists Working With Microarray Experiments

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The use of microarrays to measure the expression of large numbers of genes simultaneously is increasing in agriculture. Statisticians are expected to help biologists analyze these large data sets to identify biologically important genes that are differentially regulated in the samples under investig...

  7. 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. PMID:21083822

  8. 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. PMID:26188129

  9. A microarray system for Y chromosomal and mitochondrial single nucleotide polymorphism analysis in chimpanzee populations.

    PubMed

    Andrés, Olga; Rönn, Ann-Charlotte; Bonhomme, Maxime; Kellermann, Thomas; Crouau-Roy, Brigitte; Doxiadis, Gaby; Verschoor, Ernst J; Goossens, Benoît; Domingo-Roura, Xavier; Bruford, Michael W; Bosch, Montserrat; Syvänen, Ann-Christine

    2008-05-01

    Chimpanzee populations are diminishing as a consequence of human activities, and as a result this species is now endangered. In the context of conservation programmes, genetic data can add vital information, for instance on the genetic diversity and structure of threatened populations. Single nucleotide polymorphisms (SNP) are biallelic markers that are widely used in human molecular studies and can be implemented in efficient microarray systems. This technology offers the potential of robust, multiplexed SNP genotyping at low reagent cost in other organisms than humans, but it is not commonly used yet in wild population studies. Here, we describe the characterization of new SNPs in Y-chromosomal intronic regions in chimpanzees and also identify SNPs from mitochondrial genes, with the aim of developing a microarray system that permits the simultaneous study of both paternal and maternal lineages. Our system consists of 42 SNPs for the Y chromosome and 45 SNPs for the mitochondrial genome. We demonstrate the applicability of this microarray in a captive population where genotypes accurately reflected its large pedigree. Two wild-living populations were also analysed and the results show that the microarray will be a useful tool alongside microsatellite markers, since it supplies complementary information about population structure and ecology. SNP genotyping using microarray technology, therefore, is a promising approach and may become an essential tool in conservation genetics to help in the management and study of captive and wild-living populations. Moreover, microarrays that combine SNPs from different genomic regions could replace microsatellite typing in the future. PMID:21585830

  10. 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

  11. Erratum: Colorectal Cancer Cell Surface Protein Profiling Using an Antibody Microarray and Fluorescence Multiplexing.

    PubMed

    2015-01-01

    The author's email has been corrected in the publication of Colorectal Cancer Cell Surface Protein Profiling Using an Antibody Microarray and Fluorescence Multiplexing. There was an error with the author, Jerry Zhou's, email. The author's email has been updated to: j.zhou@uws.edu.au from: jzho7551@mail.usyd.edu.au. PMID:26167960

  12. An Update on Soybean Functional Genomics and Microarray Resources for Gene Discovery and Crop Improvement

    Technology Transfer Automated Retrieval System (TEKTRAN)

    DNA microarrays are powerful tools to analyze the expression patterns of thousands of genes simultaneously. We review recent soybean genomics projects that have produced public-sector resources for this important legume crop. As part of the NSF-sponsored “Soybean Functional Genomics Program”, we hav...

  13. 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

  14. 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

  15. Development of low-density oligonucleotide microarrays for detecting mutations causing Wilson's disease

    PubMed Central

    Mathur, Manjula; Singh, Ekta; Poduval, T.B.; Rao, Akkipeddi V.S.S.N.

    2015-01-01

    Background & objectives: Wilson's disease (WD) is an autosomal recessive disorder caused by mutations in ATP7B, a copper transporter gene, leading to hepatic and neuropsychiatric manifestations due to copper accumulation. If diagnosed early, WD patients can be managed by medicines reducing morbidity and mortality. Diagnosis of this disease requires a combination of tests and at times is inconclusive due to overlap of the symptoms with other disorders. Genetic testing is the preferred alternative in such cases particularly for individuals with a family history. Use of DNA microarray for detecting mutations in ATP7B gene is gaining popularity because of the advantages it offers in terms of throughput and sensitivity. This study attempts to establish the quality analysis procedures for microarray based diagnosis of Wilson's disease. Methods: A home-made microarrayer was used to print oligonucleotide based low-density microarrays for addressing 62 mutations causing Wilson's disease reported from Indian population. Inter- and intra- array comparisons were used to study quality of the arrays. The arrays were validated by using mutant samples generated by site directed mutagenesis. Results: The hybridization reaction were found to be consistent across the surface of a given microarray. Our results have shown that 52 °C post-hybridization wash yields better reproducibility across experiments compared to 42 °C. Our arrays have shown > 80 per cent sensitivity in detecting these 62 mutations. Interpretation & conclusions: The present results demonstrate the design and evaluation of a low-density microarray for the detection of 62 mutations in ATP7B gene, and show that a microarray based approach can be cost-effective for detecting a large number of mutations simultaneously. This study also provides information on some of the important parameters required for microarray based diagnosis of genetic disorders. PMID:25900953

  16. 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. PMID:23110046

  17. Quantifying the Antibody Binding on Protein Microarrays using Microarray Nonlinear Calibration

    PubMed Central

    Yu, Xiaobo; Wallstrom, Garrick; Magee, Dewey Mitchell; Qiu, Ji; Mendoza, D. Eliseo A.; Wang, Jie; Bian, Xiaofang; Graves, Morgan; LaBaer, Joshua

    2015-01-01

    To address the issue of quantification for antibody assays with protein microarrays, we firstly developed a Microarray Nonlinear Calibration (MiNC) method that applies in the quantification of antibody binding to the surface of microarray spots. We found that MiNC significantly increased the linear dynamic range and reduced assay variations. A serological analysis of guinea pig Mycobacterium tuberculosis models showed that a larger number of putative antigen targets were identified with MiNC, which is consistent with the improved assay performance of protein microarrays. We expect that our cumulative results will provide scientists with a new appreciation of antibody assays with protein microarrays. Our MiNC method has the potential to be employed in biomedical research with multiplex antibody assays which need quantitation, including the discovery of antibody biomarkers, clinical diagnostics with multi-antibody signatures and construction of immune mathematical models. PMID:23662896

  18. 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

  19. Advancing microarray assembly with acoustic dispensing technology.

    PubMed

    Wong, E Y; Diamond, S L

    2009-01-01

    In the assembly of microarrays and microarray-based chemical assays and enzymatic bioassays, most approaches use pins for contact spotting. Acoustic dispensing is a technology capable of nanoliter transfers by using acoustic energy to eject liquid sample from an open source well. Although typically used for well plate transfers, when applied to microarraying, it avoids the drawbacks of undesired physical contact with the sample; difficulty in assembling multicomponent reactions on a chip by readdressing, a rigid mode of printing that lacks patterning capabilities; and time-consuming wash steps. We demonstrated the utility of acoustic dispensing by delivering human cathepsin L in a drop-on-drop fashion into individual 50-nanoliter, prespotted reaction volumes to activate enzyme reactions at targeted positions on a microarray. We generated variable-sized spots ranging from 200 to 750 microm (and higher) and handled the transfer of fluorescent bead suspensions with increasing source well concentrations of 0.1 to 10 x 10(8) beads/mL in a linear fashion. There are no tips that can clog, and liquid dispensing CVs are generally below 5%. This platform expands the toolbox for generating analytical arrays and meets needs associated with spatially addressed assembly of multicomponent microarrays on the nanoliter scale. PMID:19035650

  20. A Synthetic Kinome Microarray Data Generator

    PubMed Central

    Maleki, Farhad; Kusalik, Anthony

    2015-01-01

    Cellular pathways involve the phosphorylation and dephosphorylation of proteins. Peptide microarrays called kinome arrays facilitate the measurement of the phosphorylation activity of hundreds of proteins in a single experiment. Analyzing the data from kinome microarrays is a multi-step process. Typically, various techniques are possible for a particular step, and it is necessary to compare and evaluate them. Such evaluations require data for which correct analysis results are known. Unfortunately, such kinome data is not readily available in the community. Further, there are no established techniques for creating artificial kinome datasets with known results and with the same characteristics as real kinome datasets. In this paper, a methodology for generating synthetic kinome array data is proposed. The methodology relies on actual intensity measurements from kinome microarray experiments and preserves their subtle characteristics. The utility of the methodology is demonstrated by evaluating methods for eliminating heterogeneous variance in kinome microarray data. Phosphorylation intensities from kinome microarrays often exhibit such heterogeneous variance and its presence can negatively impact downstream statistical techniques that rely on homogeneity of variance. It is shown that using the output from the proposed synthetic data generator, it is possible to critically compare two variance stabilization methods.

  1. A software framework for microarray and gene expression object model (MAGE-OM) array design annotation

    PubMed Central

    Qureshi, Matloob; Ivens, Alasdair

    2008-01-01

    Background The MIAME and MAGE-OM standards defined by the MGED society provide a specification and implementation of a software infrastructure to facilitate the submission and sharing of data from microarray studies via public repositories. However, although the MAGE object model is flexible enough to support different annotation strategies, the annotation of array descriptions can be complex. Results We have developed a graphical Java-based application (Adamant) to assist with submission of Microarray designs to public repositories. Output of the application is fully compliant with the standards prescribed by the various public data repositories. Conclusion Adamant will allow researchers to annotate and submit their own array designs to public repositories without requiring programming expertise, knowledge of the MAGE-OM or XML. The application has been used to submit a number of ArrayDesigns to the Array Express database. PMID:18366695

  2. 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

  3. Evaluation of two outlier-detection-based methods for detecting tissue-selective genes from microarray data.

    PubMed

    Kadota, Koji; Konishi, Tomokazu; Shimizu, Kentaro

    2007-01-01

    Large-scale expression profiling using DNA microarrays enables identification of tissue-selective genes for which expression is considerably higher and/or lower in some tissues than in others. Among numerous possible methods, only two outlier-detection-based methods (an AIC-based method and Sprent's non-parametric method) can treat equally various types of selective patterns, but they produce substantially different results. We investigated the performance of these two methods for different parameter settings and for a reduced number of samples. We focused on their ability to detect selective expression patterns robustly. We applied them to public microarray data collected from 36 normal human tissue samples and analyzed the effects of both changing the parameter settings and reducing the number of samples. The AIC-based method was more robust in both cases. The findings confirm that the use of the AIC-based method in the recently proposed ROKU method for detecting tissue-selective expression patterns is correct and that Sprent's method is not suitable for ROKU. PMID:19936074

  4. Integrating Colon Cancer Microarray Data: Associating Locus-Specific Methylation Groups to Gene Expression-Based Classifications

    PubMed Central

    Barat, Ana; Ruskin, Heather J.; Byrne, Annette T.; Prehn, Jochen H. M.

    2015-01-01

    Recently, considerable attention has been paid to gene expression-based classifications of colorectal cancers (CRC) and their association with patient prognosis. In addition to changes in gene expression, abnormal DNA-methylation is known to play an important role in cancer onset and development, and colon cancer is no exception to this rule. Large-scale technologies, such as methylation microarray assays and specific sequencing of methylated DNA, have been used to determine whole genome profiles of CpG island methylation in tissue samples. In this article, publicly available microarray-based gene expression and methylation data sets are used to characterize expression subtypes with respect to locus-specific methylation. A major objective was to determine whether integration of these data types improves previously characterized subtypes, or provides evidence for additional subtypes. We used unsupervised clustering techniques to determine methylation-based subgroups, which are subsequently annotated with three published expression-based classifications, comprising from three to six subtypes. Our results showed that, while methylation profiles provide a further basis for segregation of certain (Inflammatory and Goblet-like) finer-grained expression-based subtypes, they also suggest that other finer-grained subtypes are not distinctive and can be considered as a single subtype.

  5. 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

  6. Long synthetic oligonucleotides for microarray expression measurement

    NASA Astrophysics Data System (ADS)

    Li, Jiong; Wang, Hong; Liu, Heping; Zhang, M.; Zhang, Chunxiu; Lu, Zu-Hong; Gao, Xiang; Kong, Dong

    2001-09-01

    There are generally two kinds of DNA microarray used for genomic-scale gene expression profiling of mRNA: cDNA and DNA chip, but both of them suffer from some drawbacks. To meet more requirements, another oligonucleotide microarray with long was produced. This type of microarray had the advantages of low cost, minimal Cross-hybridization, flexible and easy to make, which is most fit for small laboratories with special purposes. In this paper, we devised different probes with different probe lengths, GC contents and gene positions to optimization the probe design. Experiments showed 70 mer probes are suitable for both sufficient sensitivity and reasonable costs. Higher G-C content produces stronger signal intensity thus better sensitivity and probes designed at 3 untranslated region of gene within the range of 300 pb should be best for both sensitivity and specificity.

  7. 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

  8. 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).

  9. 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. PMID:23288464

  10. 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. PMID:26504573

  11. 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

  12. 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.

  13. 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

  14. Pineal function: impact of microarray analysis.

    PubMed

    Klein, David C; Bailey, Michael J; Carter, David A; Kim, Jong-so; Shi, Qiong; Ho, Anthony K; Chik, Constance L; Gaildrat, Pascaline; Morin, Fabrice; Ganguly, Surajit; Rath, Martin F; Møller, Morten; Sugden, David; Rangel, Zoila G; Munson, Peter J; Weller, Joan L; Coon, Steven L

    2010-01-27

    Microarray analysis has provided a new understanding of pineal function by identifying genes that are highly expressed in this tissue relative to other tissues and also by identifying over 600 genes that are expressed on a 24-h schedule. This effort has highlighted surprising similarity to the retina and has provided reason to explore new avenues of study including intracellular signaling, signal transduction, transcriptional cascades, thyroid/retinoic acid hormone signaling, metal biology, RNA splicing, and the role the pineal gland plays in the immune/inflammation response. The new foundation that microarray analysis has provided will broadly support future research on pineal function. PMID:19622385

  15. 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. PMID:23666707

  16. An efficient algorithm for the stochastic simulation of the hybridization of DNA to microarrays

    PubMed Central

    2009-01-01

    Background Although oligonucleotide microarray technology is ubiquitous in genomic research, reproducibility and standardization of expression measurements still concern many researchers. Cross-hybridization between microarray probes and non-target ssDNA has been implicated as a primary factor in sensitivity and selectivity loss. Since hybridization is a chemical process, it may be modeled at a population-level using a combination of material balance equations and thermodynamics. However, the hybridization reaction network may be exceptionally large for commercial arrays, which often possess at least one reporter per transcript. Quantification of the kinetics and equilibrium of exceptionally large chemical systems of this type is numerically infeasible with customary approaches. Results In this paper, we present a robust and computationally efficient algorithm for the simulation of hybridization processes underlying microarray assays. Our method may be utilized to identify the extent to which nucleic acid targets (e.g. cDNA) will cross-hybridize with probes, and by extension, characterize probe robustnessusing the information specified by MAGE-TAB. Using this algorithm, we characterize cross-hybridization in a modified commercial microarray assay. Conclusions By integrating stochastic simulation with thermodynamic prediction tools for DNA hybridization, one may robustly and rapidly characterize of the selectivity of a proposed microarray design at the probe and "system" levels. Our code is available at http://www.laurenzi.net. PMID:20003312

  17. CrossNorm: a novel normalization strategy for microarray data in cancers.

    PubMed

    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

  18. 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

  19. 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…

  20. (Re)designing and Implementing the Professional Doctorate in Education: Comparing Experiences of a Small Independent University and a Large Public University

    ERIC Educational Resources Information Center

    Taylor, Rosemarye; Storey, Valerie Anne

    2011-01-01

    Two diverse universities--one large public metropolitan and one small independent-- participate in the Carnegie Project on the Education Doctorate (CPED) the purpose of which is to clearly distinguish between the Ph. D. and the Ed. D. and their unique intended outcomes. These universities (re)designed and implemented the professional doctorate…

  1. 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…

  2. DNA MICROARRAYS: GENE EXPRESSION APPLICATIONS

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The advent of whole genome sequencing and the application of bioinformatics tools have heralded a new era in biology. The coming of age of these tools and techniques has engendered a shift from deductive question-specific research to an inductive large-scale analysis research approach. This shift ...

  3. 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...

  4. 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...

  5. 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 primary…

  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. Data Analysis Strategies for Protein Microarrays

    PubMed Central

    Díez, Paula; Dasilva, Noelia; González-González, María; Matarraz, Sergio; Casado-Vela, Juan; Orfao, Alberto; Fuentes, Manuel

    2012-01-01

    Microarrays constitute a new platform which allows the discovery and characterization of proteins. According to different features, such as content, surface or detection system, there are many types of protein microarrays which can be applied for the identification of disease biomarkers and the characterization of protein expression patterns. However, the analysis and interpretation of the amount of information generated by microarrays remain a challenge. Further data analysis strategies are essential to obtain representative and reproducible results. Therefore, the experimental design is key, since the number of samples and dyes, among others aspects, would define the appropriate analysis method to be used. In this sense, several algorithms have been proposed so far to overcome analytical difficulties derived from fluorescence overlapping and/or background noise. Each kind of microarray is developed to fulfill a specific purpose. Therefore, the selection of appropriate analytical and data analysis strategies is crucial to achieve successful biological conclusions. In the present review, we focus on current algorithms and main strategies for data interpretation.

  8. 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.

  9. 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.

  10. Pattern recognition techniques in microarray data analysis: a survey.

    PubMed

    Valafar, Faramarz

    2002-12-01

    Recent development of technologies (e.g., microarray technology) that are capable of producing massive amounts of genetic data has highlighted the need for new pattern recognition techniques that can mine and discover biologically meaningful knowledge in large data sets. Many researchers have begun an endeavor in this direction to devise such data-mining techniques. As such, there is a need for survey articles that periodically review and summarize the work that has been done in the area. This article presents one such survey. The first portion of the paper is meant to provide the basic biology (mostly for non-biologists) that is required in such a project. This part is only meant to be a starting point for those experts in the technical fields who wish to embark on this new area of bioinformatics. The second portion of the paper is a survey of various data-mining techniques that have been used in mining microarray data for biological knowledge and information (such as sequence information). This survey is not meant to be treated as complete in any form, since the area is currently one of the most active, and the body of research is very large. Furthermore, the applications of the techniques mentioned here are not meant to be taken as the most significant applications of the techniques, but simply as examples among many. PMID:12594081

  11. Cell-based microarrays: current progress, future prospects.

    PubMed

    Palmer, Ella; Freeman, Tom

    2005-07-01

    Cell-based microarrays were first described by Ziauddin and Sabatini in 2001 as a novel method for performing high-throughput screens of gene function. In this study, expression vectors containing the open reading frame of human genes were printed onto glass microscope slides to form a microarray. Transfection reagents were added pre- or post-spotting, and cells grown over the surface of the array. They demonstrated that cells growing in the immediate vicinity of the expression vectors underwent 'reverse transfection', and that subsequent alterations in cell function could then be detected by secondary assays performed on the array. Subsequent publications have adapted the technique to a variety of applications, and have also shown that the approach works when arrays are fabricated using short interfering RNAs and compounds. The potential of this method for performing analyses of gene function and for identifying novel therapeutic agents has been clearly demonstrated, and current efforts are focused on improving and harnessing this technology for high-throughput screening applications. PMID:16014002

  12. 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.

  13. Microarray analysis at single molecule resolution

    PubMed Central

    Mureşan, Leila; Jacak, Jarosław; Klement, Erich Peter; Hesse, Jan; Schütz, Gerhard J.

    2010-01-01

    Bioanalytical chip-based assays have been enormously improved in sensitivity in the recent years; detection of trace amounts of substances down to the level of individual fluorescent molecules has become state of the art technology. The impact of such detection methods, however, has yet not fully been exploited, mainly due to a lack in appropriate mathematical tools for robust data analysis. One particular example relates to the analysis of microarray data. While classical microarray analysis works at resolutions of two to 20 micrometers and quantifies the abundance of target molecules by determining average pixel intensities, a novel high resolution approach [1] directly visualizes individual bound molecules as diffraction limited peaks. The now possible quantification via counting is less susceptible to labeling artifacts and background noise. We have developed an approach for the analysis of high-resolution microarray images. It consists first of a single molecule detection step, based on undecimated wavelet transforms, and second, of a spot identification step via spatial statistics approach (corresponding to the segmentation step in the classical microarray analysis). The detection method was tested on simulated images with a concentration range of 0.001 to 0.5 molecules per square micron and signal-to-noise ratio (SNR) between 0.9 and 31.6. For SNR above 15 the false negatives relative error was below 15%. Separation of foreground/background proved reliable, in case foreground density exceeds background by a factor of 2. The method has also been applied to real data from high-resolution microarray measurements. PMID:20123580

  14. A flow-through holed PDMS membrane as a reusable microarray spotter for biomedical assays.

    PubMed

    Lamberti, A; Angelini, A; Ricciardi, S; Frascella, F

    2015-01-01

    We propose the exploitation of a holed-designed poly(dimethyl)siloxane (PDMS) membrane as an innovative microarray spotter. The membrane is fabricated by a simple technological approach and can be reused several times. A good level of reproducibility is found upon spotting fluorescent proteins at different concentrations over large areas. PMID:25360791

  15. Innovative instrumentation for microarray scanning and analysis: application for characterization of oligonucleotide duplexes behavior.

    PubMed

    Khomyakova, E B; Dreval, E V; Tran-Dang, M; Potier, M C; Soussaline, F P

    2004-05-01

    Accuracy in microarray technology requires new approaches to microarray reader development. A microarray reader system (optical scanning array or OSA reader) based on automated microscopy with large field of view, high speed 3 axis scanning at multiple narrow-band spectra of excitation light has been developed. It allows fast capture of high-resolution, multi-fluorescence images and is characterized by a linear dynamic range and sensitivity comparable to commonly used photo-multiplier tube (PMT)-based laser scanner. Controlled by high performance software, the instrument can be used for scanning and quantitative analysis of any type of dry microarray. Studies implying temperature-controlled hybridization chamber containing a microarray can also be performed. This enables the registration of kinetics and melting curves. This feature is required in a wide range of on-chip chemical and enzymatic reactions including on-chip PCR amplification. We used the OSA reader for the characterization of hybridization and melting behaviour of oligonucleotide:oligonucleotide duplexes on three-dimensional Code Link slides. PMID:15209342

  16. Analyzing Schizophrenia by DNA Microarrays

    PubMed Central

    Horváth, Szatmár; Janka, Zoltán; Mirnics, Károly

    2010-01-01

    To understand the pathological processes of schizophrenia we must embrace the analysis of the diseased human brain: we will never be able to recapitulate the pathology of uniquely human disorders in an animal model. Based on the outcome of the transcriptome profiling experiments performed to date it appears that schizophrenia is associated with a global gene expression disturbance across many cortical regions. In addition, transcriptome changes are present in multiple cell types, including specific subclasses of principal neurons, interneurons and oligodendrocytes. Furthermore, transcripts related to synaptic transmission, energy metabolism and inhibitory neurotransmission are routinely found underexpressed in the postmortem brain tissue of subjects with schizophrenia. To put these transcriptome data in biological context we must make our data publicly available and report our findings in a proper, expanded MIAME format. Cell type specific expression profiling and sequencing-based transcripts assessments should be expanded, with particular attention to understanding splice-variant changes in various mental disorders. Deciphering the pathophysiology of mental disorders depends on integrating data from across many research fields and techniques. Leads from postmortem transcriptome profiling will be essential to generate model animals, perform tissue culture experiments and develop or evaluate novel drugs to treat this devastating disorder. PMID:20801428

  17. A multivariate approach for high throughput pectin profiling by combining glycan microarrays with monoclonal antibodies.

    PubMed

    Sousa, António G; Ahl, Louise I; Pedersen, Henriette L; Fangel, Jonatan U; Sørensen, Susanne O; Willats, William G T

    2015-05-29

    Pectin-one of the most complex biomacromolecules in nature has been extensively studied using various techniques. This has been done so in an attempt to understand the chemical composition and conformation of pectin, whilst discovering and optimising new industrial applications of the polymer. For the last decade the emergence of glycan microarray technology has led to a growing capacity of acquiring simultaneous measurements related to various carbohydrate characteristics while generating large collections of data. Here we used a multivariate analysis approach in order to analyse a set of 359 pectin samples probed with 14 different monoclonal antibodies (mAbs). Principal component analysis (PCA) and partial least squares (PLS) regression were utilised to obtain the most optimal qualitative and quantitative information from the spotted microarrays. The potential use of microarray technology combined with chemometrics for the accurate determination of degree of methyl-esterification (DM) and degree of blockiness (DB) was assessed. PMID:25950120

  18. Glycan Profiling of Plant Cell Wall Polymers using Microarrays

    PubMed Central

    Moller, Isabel E.; Pettolino, Filomena A.; Hart, Charlie; Lampugnani, Edwin R.; Willats, William G.T.; Bacic, Antony

    2012-01-01

    Plant cell walls are complex matrixes of heterogeneous glycans which play an important role in the physiology and development of plants and provide the raw materials for human societies (e.g. wood, paper, textile and biofuel industries)1,2. However, understanding the biosynthesis and function of these components remains challenging. Cell wall glycans are chemically and conformationally diverse due to the complexity of their building blocks, the glycosyl residues. These form linkages at multiple positions and differ in ring structure, isomeric or anomeric configuration, and in addition, are substituted with an array of non-sugar residues. Glycan composition varies in different cell and/or tissue types or even sub-domains of a single cell wall3. Furthermore, their composition is also modified during development1, or in response to environmental cues4. In excess of 2,000 genes have Plant cell walls are complex matrixes of heterogeneous glycans been predicted to be involved in cell wall glycan biosynthesis and modification in Arabidopsis5. However, relatively few of the biosynthetic genes have been functionally characterized 4,5. Reverse genetics approaches are difficult because the genes are often differentially expressed, often at low levels, between cell types6. Also, mutant studies are often hindered by gene redundancy or compensatory mechanisms to ensure appropriate cell wall function is maintained7. Thus novel approaches are needed to rapidly characterise the diverse range of glycan structures and to facilitate functional genomics approaches to understanding cell wall biosynthesis and modification. Monoclonal antibodies (mAbs)8,9 have emerged as an important tool for determining glycan structure and distribution in plants. These recognise distinct epitopes present within major classes of plant cell wall glycans, including pectins, xyloglucans, xylans, mannans, glucans and arabinogalactans. Recently their use has been extended to large-scale screening experiments

  19. 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.…

  20. 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)

  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. 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

  3. Advancing translational research with next-generation protein microarrays.

    PubMed

    Yu, Xiaobo; Petritis, Brianne; LaBaer, Joshua

    2016-04-01

    Protein microarrays are a high-throughput technology used increasingly in translational research, seeking to apply basic science findings to enhance human health. In addition to assessing protein levels, posttranslational modifications, and signaling pathways in patient samples, protein microarrays have aided in the identification of potential protein biomarkers of disease and infection. In this perspective, the different types of full-length protein microarrays that are used in translational research are reviewed. Specific studies employing these microarrays are presented to highlight their potential in finding solutions to real clinical problems. Finally, the criteria that should be considered when developing next-generation protein microarrays are provided. PMID:26749402

  4. 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

  5. Microarrays for the evaluation of cell-biomaterial surface interactions

    NASA Astrophysics Data System (ADS)

    Thissen, H.; Johnson, G.; McFarland, G.; Verbiest, B. C. H.; Gengenbach, T.; Voelcker, N. H.

    2007-01-01

    The evaluation of cell-material surface interactions is important for the design of novel biomaterials which are used in a variety of biomedical applications. While traditional in vitro test methods have routinely used samples of relatively large size, microarrays representing different biomaterials offer many advantages, including high throughput and reduced sample handling. Here, we describe the simultaneous cell-based testing of matrices of polymeric biomaterials, arrayed on glass slides with a low cell-attachment background coating. Arrays were constructed using a microarray robot at 6 fold redundancy with solid pins having a diameter of 375 μm. Printed solutions contained at least one monomer, an initiator and a bifunctional crosslinker. After subsequent UV polymerisation, the arrays were washed and characterised by X-ray photoelectron spectroscopy. Cell culture experiments were carried out over 24 hours using HeLa cells. After labelling with CellTracker ® Green for the final hour of incubation and subsequent fixation, the arrays were scanned. In addition, individual spots were also viewed by fluorescence microscopy. The evaluation of cell-surface interactions in high-throughput assays as demonstrated here is a key enabling technology for the effective development of future biomaterials.

  6. 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

  7. Biocompatible Hydrogels for Microarray Cell Printing and Encapsulation.

    PubMed

    Datar, Akshata; Joshi, Pranav; Lee, Moo-Yeal

    2015-12-01

    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

  8. 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

  9. 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.

  10. Immobilization Techniques for Microarray: Challenges and Applications

    PubMed Central

    Nimse, Satish Balasaheb; Song, Keumsoo; Sonawane, Mukesh Digambar; Sayyed, Danishmalik Rafiq; Kim, Taisun

    2014-01-01

    The highly programmable positioning of molecules (biomolecules, nanoparticles, nanobeads, nanocomposites materials) on surfaces has potential applications in the fields of biosensors, biomolecular electronics, and nanodevices. However, the conventional techniques including self-assembled monolayers fail to position the molecules on the nanometer scale to produce highly organized monolayers on the surface. The present article elaborates different techniques for the immobilization of the biomolecules on the surface to produce microarrays and their diagnostic applications. The advantages and the drawbacks of various methods are compared. This article also sheds light on the applications of the different technologies for the detection and discrimination of viral/bacterial genotypes and the detection of the biomarkers. A brief survey with 115 references covering the last 10 years on the biological applications of microarrays in various fields is also provided. PMID:25429408

  11. Use of microarray technologies in toxicology research.

    PubMed

    Vrana, Kent E; Freeman, Willard M; Aschner, Michael

    2003-06-01

    Microarray technology provides a unique tool for the determination of gene expression at the level of messenger RNA (mRNA). The simultaneous measurement of the entire human genome (thousands of genes) will facilitate the uncovering of specific gene expression patterns that are associated with disease. One important application of microarray technology, within the context of neurotoxicological studies, is its use as a screening tool for the identification of molecular mechanisms of toxicity. Such approaches enable researchers to identify those genes and their products (either single or whole pathways) that are involved in conferring resistance or sensitivity to toxic substances. This review addresses: (1) the potential uses of array data; (2) the various array platforms, highlighting both their advantages and disadvantages; (3) insights into data analysis and presentation strategies; and (4) concrete examples of DNA array studies in neurotoxicological research. PMID:12782098

  12. A Flexible Microarray Data Simulation Model

    PubMed Central

    Dembélé, Doulaye

    2013-01-01

    Microarray technology allows monitoring of gene expression profiling at the genome level. This is useful in order to search for genes involved in a disease. The performances of the methods used to select interesting genes are most often judged after other analyzes (qPCR validation, search in databases...), which are also subject to error. A good evaluation of gene selection methods is possible with data whose characteristics are known, that is to say, synthetic data. We propose a model to simulate microarray data with similar characteristics to the data commonly produced by current platforms. The parameters used in this model are described to allow the user to generate data with varying characteristics. In order to show the flexibility of the proposed model, a commented example is given and illustrated. An R package is available for immediate use.

  13. Microarrays: how many do you need?

    PubMed

    Zien, Alexander; Fluck, Juliane; Zimmer, Ralf; Lengauer, Thomas

    2003-01-01

    We estimate the number of microarrays that is required in order to gain reliable results from a common type of study: the pairwise comparison of different classes of samples. We show that current knowledge allows for the construction of models that look realistic with respect to searches for individual differentially expressed genes and derive prototypical parameters from real data sets. Such models allow investigation of the dependence of the required number of samples on the relevant parameters: the biological variability of the samples within each class, the fold changes in expression that are desired to be detected, the detection sensitivity of the microarrays, and the acceptable error rates of the results. We supply experimentalists with general conclusions as well as a freely accessible Java applet at www.scai.fhg.de/special/bio/howmanyarrays/ for fine tuning simulations to their particular settings. PMID:12935350

  14. Glycan microarrays for decoding the glycome

    PubMed Central

    Rillahan, Cory D.; Paulson, James C.

    2011-01-01

    In the last decade glycan microarrays have revolutionized the analysis of the specificity of glycan binding proteins, providing information that simultaneously illuminates the biology mediated by them and decodes the information content of the glycome. Numerous methods have emerged for arraying glycans in a ‘chip’ format, and glycan libraries have been assembled that address the diversity of the human glycome. Such arrays have been successfully used for analysis of glycan binding proteins that mediate mammalian biology, host-pathogen interactions, immune recognition of glycans relevant to vaccine production and cancer antigens. This review covers the development of glycan microarrays and applications that have provided insights into the roles of mammalian and microbial glycan binding proteins. PMID:21469953

  15. 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.

  16. An evaluation of the impact of large-scale interventions to raise public awareness of a lung cancer symptom

    PubMed Central

    Ironmonger, L; Ohuma, E; Ormiston-Smith, N; Gildea, C; Thomson, C S; Peake, M D

    2015-01-01

    Introduction: Long-term lung cancer survival in England has improved little in recent years and is worse than many countries. The Department of Health funded a campaign to raise public awareness of persistent cough as a lung cancer symptom and encourage people with the symptom to visit their GP. This was piloted regionally within England before a nationwide rollout. Methods: To evaluate the campaign's impact, data were analysed for various metrics covering public awareness of symptoms and process measures, through to diagnosis, staging, treatment and 1-year survival (available for regional pilot only). Results: Compared with the same time in the previous year, there were significant increases in metrics including: public awareness of persistent cough as a lung cancer symptom; urgent GP referrals for suspected lung cancer; and lung cancers diagnosed. Most encouragingly, there was a 3.1 percentage point increase (P<0.001) in proportion of non-small cell lung cancer diagnosed at stage I and a 2.3 percentage point increase (P<0.001) in resections for patients seen during the national campaign, with no evidence these proportions changed during the control period (P=0.404, 0.425). Conclusions: To our knowledge, the data are the first to suggest a shift in stage distribution following an awareness campaign for lung cancer. It is possible a sustained increase in resections may lead to improved long-term survival. PMID:25461805

  17. 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

  18. 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. PMID:25821171

  19. An imputation approach for oligonucleotide microarrays.

    PubMed

    Li, Ming; Wen, Yalu; Lu, Qing; Fu, Wenjiang J

    2013-01-01

    Oligonucleotide microarrays are commonly adopted for detecting and qualifying the abundance of molecules in biological samples. Analysis of microarray data starts with recording and interpreting hybridization signals from CEL images. However, many CEL images may be blemished by noises from various sources, observed as "bright spots", "dark clouds", and "shadowy circles", etc. It is crucial that these image defects are correctly identified and properly processed. Existing approaches mainly focus on detecting defect areas and removing affected intensities. In this article, we propose to use a mixed effect model for imputing the affected intensities. The proposed imputation procedure is a single-array-based approach which does not require any biological replicate or between-array normalization. We further examine its performance by using Affymetrix high-density SNP arrays. The results show that this imputation procedure significantly reduces genotyping error rates. We also discuss the necessary adjustments for its potential extension to other oligonucleotide microarrays, such as gene expression profiling. The R source code for the implementation of approach is freely available upon request. PMID:23505547

  20. 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.

  1. 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.

  2. Application of wavelet-based neural network on DNA microarray data.

    PubMed

    Lee, Jack; Zee, Benny

    2008-01-01

    The advantage of using DNA microarray data when investigating human cancer gene expressions is its ability to generate enormous amount of information from a single assay in order to speed up the scientific evaluation process. The number of variables from the gene expression data coupled with comparably much less number of samples creates new challenges to scientists and statisticians. In particular, the problems include enormous degree of collinearity among genes expressions, likely violation of model assumptions as well as high level of noise with potential outliers. To deal with these problems, we propose a block wavelet shrinkage principal component (BWSPCA) analysis method to optimize the information during the noise reduction process. This paper firstly uses the National Cancer Institute database (NC160) as an illustration and shows a significant improvement in dimension reduction. Secondly we combine BWSPCA with an artificial neural network-based gene minimization strategy to establish a Block Wavelet-based Neural Network model in a robust and accurate cancer classification process (BWNN). Our extensive experiments on six public cancer datasets have shown that the method of BWNN for tumor classification performed well, especially on some difficult instances with large-class (more than two) expression data. This proposed method is extremely useful for data denoising and is competitiveness with respect to other methods such as BagBoost, RandomForest (RanFor), Support Vector Machines (SVM), K-Nearest Neighbor (KNN) and Artificial Neural Network (ANN). PMID:19255638

  3. 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

  4. 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

  5. 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…

  6. 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…

  7. Assessing Statistical Significance in Microarray Experiments Using the Distance Between Microarrays

    PubMed Central

    Hayden, Douglas; Lazar, Peter; Schoenfeld, David

    2009-01-01

    We propose permutation tests based on the pairwise distances between microarrays to compare location, variability, or equivalence of gene expression between two populations. For these tests the entire microarray or some pre-specified subset of genes is the unit of analysis. The pairwise distances only have to be computed once so the procedure is not computationally intensive despite the high dimensionality of the data. An R software package, permtest, implementing the method is freely available from the Comprehensive R Archive Network at http://cran.r-project.org. PMID:19529777

  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 refine hypothetical models, leading to a modeling-experiment cycle for high-throughput biological system analysis. We use fuzzy logic gene network models because they have greater resolution than Boolean logic models and do not require the precise parameter measurement needed for chemical kinetics-based modeling. The fuzzy gene network approach is tested by exhaustive search for network models describing cyclin gene interactions in yeast cell cycle microarray data, with preliminary success in recovering interactions predicted by previous biological knowledge and other analysis techniques. Our goal is to further develop this method in combination with experiments we are performing on bacterial regulatory networks.

  9. Visualization of Growth Curve Data from Phenotype MicroarrayExperiments

    SciTech Connect

    Jacobsen, Janet S.; Joyner, Dominique C.; Borglin, Sharon E.; Hazen, Terry C.; Arkin, Adam P.; Bethel, E. Wes

    2007-04-19

    Phenotype microarrays provide a technology to simultaneouslysurvey the response of an organism to nearly 2,000 substrates, includingcarbon, nitrogen and potassium sources; varying pH; varying saltconcentrations; and antibiotics. In order to more quickly and easily viewand compare the large number of growth curves produced by phenotypemicroarray experiments, we have developed software to produce and displaycolor images, each of which corresponds to a set of 96 growth curves.Using color images to represent growth curves data has proven to be avaluable way to assess experiment quality, compare replicates, facilitatecomparison of the responses of different organisms, and identifysignificant phenotypes. The color images are linked to traditional plotsof growth versus time, as well as to information about the experiment,organism, and substrate. In order to share and view information and dataproject-wide, all information, plots, and data are accessible using onlya Web browser.

  10. 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

  11. Analysis of microarray leukemia data using an efficient MapReduce-based K-nearest-neighbor classifier.

    PubMed

    Kumar, Mukesh; Rath, Nitish Kumar; Rath, Santanu Kumar

    2016-04-01

    Microarray-based gene expression profiling has emerged as an efficient technique for classification, prognosis, diagnosis, and treatment of cancer. Frequent changes in the behavior of this disease generates an enormous volume of data. Microarray data satisfies both the veracity and velocity properties of big data, as it keeps changing with time. Therefore, the analysis of microarray datasets in a small amount of time is essential. They often contain a large amount of expression, but only a fraction of it comprises genes that are significantly expressed. The precise identification of genes of interest that are responsible for causing cancer are imperative in microarray data analysis. Most existing schemes employ a two-phase process such as feature selection/extraction followed by classification. In this paper, various statistical methods (tests) based on MapReduce are proposed for selecting relevant features. After feature selection, a MapReduce-based K-nearest neighbor (mrKNN) classifier is also employed to classify microarray data. These algorithms are successfully implemented in a Hadoop framework. A comparative analysis is done on these MapReduce-based models using microarray datasets of various dimensions. From the obtained results, it is observed that these models consume much less execution time than conventional models in processing big data. PMID:26975600

  12. Identification of significant features in DNA microarray data

    PubMed Central

    Bair, Eric

    2013-01-01

    DNA microarrays are a relatively new technology that can simultaneously measure the expression level of thousands of genes. They have become an important tool for a wide variety of biological experiments. One of the most common goals of DNA microarray experiments is to identify genes associated with biological processes of interest. Conventional statistical tests often produce poor results when applied to microarray data owing to small sample sizes, noisy data, and correlation among the expression levels of the genes. Thus, novel statistical methods are needed to identify significant genes in DNA microarray experiments. This article discusses the challenges inherent in DNA microarray analysis and describes a series of statistical techniques that can be used to overcome these challenges. The problem of multiple hypothesis testing and its relation to microarray studies are also considered, along with several possible solutions. PMID:24244802

  13. High-throughput allogeneic antibody detection using protein microarrays.

    PubMed

    Paul, Jed; Sahaf, Bita; Perloff, Spenser; Schoenrock, Kelsi; Wu, Fang; Nakasone, Hideki; Coller, John; Miklos, David

    2016-05-01

    Enzyme-linked immunosorbent assays (ELISAs) have traditionally been used to detect alloantibodies in patient plasma samples post hematopoietic cell transplantation (HCT); however, protein microarrays have the potential to be multiplexed, more sensitive, and higher throughput than ELISAs. Here, we describe the development of a novel and sensitive microarray method for detection of allogeneic antibodies against minor histocompatibility antigens encoded on the Y chromosome, called HY antigens. Six microarray surfaces were tested for their ability to bind recombinant protein and peptide HY antigens. Significant allogeneic immune responses were determined in male patients with female donors by considering normal male donor responses as baseline. HY microarray results were also compared with our previous ELISA results. Our overall goal was to maximize antibody detection for both recombinant protein and peptide epitopes. For detection of HY antigens, the Epoxy (Schott) protein microarray surface was both most sensitive and reliable and has become the standard surface in our microarray platform. PMID:26902899

  14. Prenatal chromosomal microarray for the Catholic physician

    PubMed Central

    Bringman, Jay J.

    2014-01-01

    Prenatal chromosomal microarray (CMA) is a test that is used to diagnose certain genetic problems in the fetus. While the test has been used in the pediatric setting for several years, it is now being introduced for use in the prenatal setting. The test offers great hope for detection of certain genetic defects in the fetus so that early intervention can be performed to improve the outcome for that individual. As with many biotechnical advances, CMA comes with certain bioethical issues that need to be addressed prior to its implementation. This paper is intended to provide guidance to all those that provide counseling regarding genetic testing options during pregnancy. PMID:24899750

  15. Protein Microarrays--Without a Trace

    SciTech Connect

    Camarero, J A

    2007-04-05

    Many experimental approaches in biology and biophysics, as well as applications in diagnosis and drug discovery, require proteins to be immobilized on solid supports. Protein microarrays, for example, provide a high-throughput format to study biomolecular interactions. The technique employed for protein immobilization is a key to the success of these applications. Recent biochemical developments are allowing, for the first time, the selective and traceless immobilization of proteins generated by cell-free systems without the need for purification and/or reconcentration prior to the immobilization step.

  16. ProMAT: protein microarray analysis tool

    SciTech Connect

    White, Amanda M.; Daly, Don S.; Varnum, Susan M.; Anderson, Kevin K.; Bollinger, Nikki; Zangar, Richard C.

    2006-04-04

    Summary: ProMAT is a software tool for statistically analyzing data from ELISA microarray experiments. The software estimates standard curves, sample protein concentrations and their uncertainties for multiple assays. ProMAT generates a set of comprehensive figures for assessing results and diagnosing process quality. The tool is available for Windows or Mac, and is distributed as open-source Java and R code. Availability: ProMAT is available at http://www.pnl.gov/statistics/ProMAT. ProMAT requires Java version 1.5.0 and R version 1.9.1 (or more recent versions) which are distributed with the tool.

  17. Gene Features Selection for Three-Class Disease Classification via Multiple Orthogonal Partial Least Square Discriminant Analysis and S-Plot Using Microarray Data

    PubMed Central

    Yang, Mingxing; Li, Xiumin; Li, Zhibin; Ou, Zhimin; Liu, Ming; Liu, Suhuan; Li, Xuejun; Yang, Shuyu

    2013-01-01

    Motivation DNA microarray analysis is characterized by obtaining a large number of gene variables from a small number of observations. Cluster analysis is widely used to analyze DNA microarray data to make classification and diagnosis of disease. Because there are so many irrelevant and insignificant genes in a dataset, a feature selection approach must be employed in data analysis. The performance of cluster analysis of this high-throughput data depends on whether the feature selection approach chooses the most relevant genes associated with disease classes. Results Here we proposed a new method using multiple Orthogonal Partial Least Squares-Discriminant Analysis (mOPLS-DA) models and S-plots to select the most relevant genes to conduct three-class disease classification and prediction. We tested our method using Golub’s leukemia microarray data. For three classes with subtypes, we proposed hierarchical orthogonal partial least squares-discriminant analysis (OPLS-DA) models and S-plots to select features for two main classes and their subtypes. For three classes in parallel, we employed three OPLS-DA models and S-plots to choose marker genes for each class. The power of feature selection to classify and predict three-class disease was evaluated using cluster analysis. Further, the general performance of our method was tested using four public datasets and compared with those of four other feature selection methods. The results revealed that our method effectively selected the most relevant features for disease classification and prediction, and its performance was better than that of the other methods. PMID:24386356

  18. Assessing large-scale surveyor variability in the historic forest data of the original U.S. Public Land Survey

    USGS Publications Warehouse

    Manies, K.L.; Mladenoff, D.J.; Nordheim, E.V.

    2001-01-01

    The U.S. General Land Office Public Land Survey (PLS) records are a valuable resource for studying pre-European settlement vegetation. However, these data were taken for legal, not ecological, purposes. In turn, the instructions the surveyors followed affected the data collected. For this reason, it has been suggested that the PLS data may not truly represent the surveyed landscapes. This study examined the PLS data of northern Wisconsin, U.S.A., to determine the extent of variability among surveyors. We statistically tested for differences among surveyors in recorded tree species, size, location, and distance from the survey point. While we cannot rule out effects from other influences (e.g., environmental factors), we found evidence suggesting some level of surveyor bias for four of five variables, including tree species and size. The PLS data remain one of the best records of pre-European settlement vegetation available. However, based on our findings, we recommend that projects using PLS records examine these data carefully. This assessment should include not only the choice of variables to be studied but also the spatial extent at which the data will be examined.

  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. Refractive index change detection based on porous silicon microarray

    NASA Astrophysics Data System (ADS)

    Chen, Weirong; Jia, Zhenhong; Li, Peng; Lv, Guodong; Lv, Xiaoyi

    2016-05-01

    By combining photolithography with the electrochemical anodization method, a microarray device of porous silicon (PS) photonic crystal was fabricated on the crystalline silicon substrate. The optical properties of the microarray were analyzed with the transfer matrix method. The relationship between refractive index and reflectivity of each array element of the microarray at 633 nm was also studied, and the array surface reflectivity changes were observed through digital imaging. By means of the reflectivity measurement method, reflectivity changes below 10-3 can be observed based on PS microarray. The results of this study can be applied to the detection of biosensor arrays.

  1. Studying cellular processes and detecting disease with protein microarrays

    SciTech Connect

    Zangar, Richard C.; Varnum, Susan M.; Bollinger, Nikki

    2005-10-31

    Protein microarrays are a rapidly developing analytic tool with diverse applications in biomedical research. These applications include profiling of disease markers or autoimmune responses, understanding molecular pathways, protein modifications and protein activities. One factor that is driving this expanding usage is the wide variety of experimental formats that protein microarrays can take. In this review, we provide a short, conceptual overview of the different approaches for protein microarray. We then examine some of the most significant applications of these microarrays to date, with an emphasis on how global protein analyses can be used to facilitate biomedical research.

  2. New insights about host response to smallpox using microarray data

    PubMed Central

    Esteves, Gustavo H; Simoes, Ana CQ; Souza, Estevao; Dias, Rodrigo A; Ospina, Raydonal; Venancio, Thiago M

    2007-01-01

    Background Smallpox is a lethal disease that was endemic in many parts of the world until eradicated by massive immunization. Due to its lethality, there are serious concerns about its use as a bioweapon. Here we analyze publicly available microarray data to further understand survival of smallpox infected macaques, using systems biology approaches. Our goal is to improve the knowledge about the progression of this disease. Results We used KEGG pathways annotations to define groups of genes (or modules), and subsequently compared them to macaque survival times. This technique provided additional insights about the host response to this disease, such as increased expression of the cytokines and ECM receptors in the individuals with higher survival times. These results could indicate that these gene groups could influence an effective response from the host to smallpox. Conclusion Macaques with higher survival times clearly express some specific pathways previously unidentified using regular gene-by-gene approaches. Our work also shows how third party analysis of public datasets can be important to support new hypotheses to relevant biological problems. PMID:17718913

  3. [Assessment of job strain and its consequencies in a large public organisation. Findings from the SEMM Study].

    PubMed

    Ferrario, M M; Cimmino, L; Ganna, A; Cambiano, V; Borchini, R; Cesana, G

    2008-01-01

    The demand-control model originally developed by Robert Karasek is in Italy the preferred tool to investigate perceived work stress due to work-related organizational constrains. We wish to report the comprehensive results of the SEMM Study, carried on a wide sample of civil servants. N. 5271 women and 2601 men, employed at the Municipality of Milan in the years 1991-1996 were enrolled into the study. The overall participation rate was high in both gender group (75% or more), indicating a good compliance of employees for health prevention programmes carried out in work settings. Each participant, who has given consent, in addition to the medical examinations and biological tests related to the investigation of work exposures, underwent to a structured procedure to measure cardiovascular risk factors, according to the methods developed in the WHO MONICA Project, job strain adopting the Job Content Questionnaire (JCQ), and the Baecke Questionnaire to investigate major quotes of physical activity. In this contest the JCQ has shown an acceptable level of internal and external consistency as well as of acceptance, measured by employees compliance. Psychological job demand and decision latitude can be assessed with two different JCQ revisions available in Italian, which were validated with the contribution of the author, at different complexity, but with comparable results of weighted scores. For a comprehensive assessment of the working conditions social support at work is also of relevance. In the work public sector considered, the JCQ major scores resulted to be valid descriptors of key aspects of the work organization. The concurrent assessment of sick leaves, known marker of burnout, allows to identify work- and individual-related determinants and, in a specific work setting, to give indications for coping actions which may improve workers' integration. In addition, the assessment of cardiovascular risk factors, carried out with standardised and then reliable

  4. High-Throughput Nano-Biofilm Microarray for Antifungal Drug Discovery

    PubMed Central

    Srinivasan, Anand; Leung, Kai P.; Lopez-Ribot, Jose L.; Ramasubramanian, Anand K.

    2013-01-01

    ABSTRACT Micro- and nanoscale technologies have radically transformed biological research from genomics to tissue engineering, with the relative exception of microbial cell culture, which is still largely performed in microtiter plates and petri dishes. Here, we present nanoscale culture of the opportunistic fungal pathogen Candida albicans on a microarray platform. The microarray consists of 1,200 individual cultures of 30 nl of C. albicans biofilms (“nano-biofilms”) encapsulated in an inert alginate matrix. We demonstrate that these nano-biofilms are similar to conventional macroscopic biofilms in their morphological, architectural, growth, and phenotypic characteristics. We also demonstrate that the nano-biofilm microarray is a robust and efficient tool for accelerating the drug discovery process: (i) combinatorial screening against a collection of 28 antifungal compounds in the presence of immunosuppressant FK506 (tacrolimus) identified six drugs that showed synergistic antifungal activity, and (ii) screening against the NCI challenge set small-molecule library identified three heretofore-unknown hits. This cell-based microarray platform allows for miniaturization of microbial cell culture and is fully compatible with other high-throughput screening technologies. PMID:23800397

  5. Evaluation of Solid Supports for Slide- and Well-Based Recombinant Antibody Microarrays

    PubMed Central

    Gerdtsson, Anna S.; Dexlin-Mellby, Linda; Delfani, Payam; Berglund, Erica; Borrebaeck, Carl A. K.; Wingren, Christer

    2016-01-01

    Antibody microarrays have emerged as an important tool within proteomics, enabling multiplexed protein expression profiling in both health and disease. The design and performance of antibody microarrays and how they are processed are dependent on several factors, of which the interplay between the antibodies and the solid surfaces plays a central role. In this study, we have taken on the first comprehensive view and evaluated the overall impact of solid surfaces on the recombinant antibody microarray design. The results clearly demonstrated the importance of the surface-antibody interaction and showed the effect of the solid supports on the printing process, the array format of planar arrays (slide- and well-based), the assay performance (spot features, reproducibility, specificity and sensitivity) and assay processing (degree of automation). In the end, two high-end recombinant antibody microarray technology platforms were designed, based on slide-based (black polymer) and well-based (clear polymer) arrays, paving the way for future large-scale protein expression profiling efforts. PMID:27600082

  6. Knowledge-based analysis of microarrays for the discovery of transcriptional regulation relationships

    PubMed Central

    2010-01-01

    Background The large amount of high-throughput genomic data has facilitated the discovery of the regulatory relationships between transcription factors and their target genes. While early methods for discovery of transcriptional regulation relationships from microarray data often focused on the high-throughput experimental data alone, more recent approaches have explored the integration of external knowledge bases of gene interactions. Results In this work, we develop an algorithm that provides improved performance in the prediction of transcriptional regulatory relationships by supplementing the analysis of microarray data with a new method of integrating information from an existing knowledge base. Using a well-known dataset of yeast microarrays and the Yeast Proteome Database, a comprehensive collection of known information of yeast genes, we show that knowledge-based predictions demonstrate better sensitivity and specificity in inferring new transcriptional interactions than predictions from microarray data alone. We also show that comprehensive, direct and high-quality knowledge bases provide better prediction performance. Comparison of our results with ChIP-chip data and growth fitness data suggests that our predicted genome-wide regulatory pairs in yeast are reasonable candidates for follow-up biological verification. Conclusion High quality, comprehensive, and direct knowledge bases, when combined with appropriate bioinformatic algorithms, can significantly improve the discovery of gene regulatory relationships from high throughput gene expression data. PMID:20122245

  7. Development of a sandwiched microarray platform for studying the interactions of antibiotics with Staphylococcus aureus.

    PubMed

    Liu, Xia; Lei, Zhen; Liu, Dianjun; Wang, Zhenxin

    2016-04-21

    It still confronts an outstanding challenge to screen efficient antibacterial drugs from millions of potential antibiotic candidates. In this regard, a sandwiched microarray platform has been developed to culture live bacteria and carry out high-throughput screening antibacterial drugs. The optimized lectin-hydrogel microarray can be used as an efficient bacterial capturing and culturing platform, which is beneficial to identify spots and collect data. At the same time, a matching drug-laden polyacrylamide microarray with Luria-Bertani (LB) culture medium can be generated automatically and accurately by using a standard non-contacting procedure. A large number of microscale culture chambers (more than 100 individual samples) between two microarrays can be formed by linking two aligned hydrogel spots using LB culture medium, where live bacteria can be co-cultured with drug candidates. Using Staphylococcus aureus (S. aureus) and four well-known antibiotics (amoxicillin, vancomycin, streptomycin and chloramphenicol) as model system, the MIC (minimum inhibitory concentration) values of the antibiotics can be determined by the drug induced change of bacterial growth, and the results demonstrate that the MIC values of amoxicillin, vancomycin and streptomycin are 1.7 μg mL(-1), 3.3 μg mL(-1) and 10.3 μg mL(-1), respectively. PMID:27026605

  8. Evaluation of Solid Supports for Slide- and Well-Based Recombinant Antibody Microarrays.

    PubMed

    Gerdtsson, Anna S; Dexlin-Mellby, Linda; Delfani, Payam; Berglund, Erica; Borrebaeck, Carl A K; Wingren, Christer

    2016-01-01

    Antibody microarrays have emerged as an important tool within proteomics, enabling multiplexed protein expression profiling in both health and disease. The design and performance of antibody microarrays and how they are processed are dependent on several factors, of which the interplay between the antibodies and the solid surfaces plays a central role. In this study, we have taken on the first comprehensive view and evaluated the overall impact of solid surfaces on the recombinant antibody microarray design. The results clearly demonstrated the importance of the surface-antibody interaction and showed the effect of the solid supports on the printing process, the array format of planar arrays (slide- and well-based), the assay performance (spot features, reproducibility, specificity and sensitivity) and assay processing (degree of automation). In the end, two high-end recombinant antibody microarray technology platforms were designed, based on slide-based (black polymer) and well-based (clear polymer) arrays, paving the way for future large-scale protein expression profiling efforts. PMID:27600082

  9. GPR-Analyzer: a simple tool for quantitative analysis of hierarchical multispecies microarrays.

    PubMed

    Dittami, Simon M; Edvardsen, Bente

    2013-10-01

    Monitoring of marine microalgae is important to predict and manage harmful algae blooms. It currently relies mainly on light-microscopic identification and enumeration of algal cells, yet several molecular tools are currently being developed to complement traditional methods. MIcroarray Detection of Toxic ALgae (MIDTAL) is an FP7-funded EU project aiming to establish a hierarchical multispecies microarray as one of these tools. Prototype arrays are currently being tested with field samples, yet the analysis of the large quantities of data generated by these arrays presents a challenge as suitable analysis tools or protocols are scarce. This paper proposes a two-part protocol for the analysis of the MIDTAL and other hierarchical multispecies arrays: Signal-to-noise ratios can be used to determine the presence or absence of signals and to identify potential false-positives considering parallel and hierarchical probes. In addition, normalized total signal intensities are recommended for comparisons between microarrays and in order to relate signals for specific probes to cell concentrations using external calibration curves. Hybridization- and probe-specific detection limits can be calculated to help evaluate negative results. The suggested analyses were implemented in "GPR-Analyzer", a platform-independent and graphical user interface-based application, enabling non-specialist users to quickly and quantitatively analyze hierarchical multispecies microarrays. It is available online at http://folk.uio.no/edvardse/gpranalyzer . PMID:22767354

  10. Effect of data normalization on fuzzy clustering of DNA microarray data

    PubMed Central

    Kim, Seo Young; Lee, Jae Won; Bae, Jong Sung

    2006-01-01

    Background Microarray technology has made it possible to simultaneously measure the expression levels of large numbers of genes in a short time. Gene expression data is information rich; however, extensive data mining is required to identify the patterns that characterize the underlying mechanisms of action. Clustering is an important tool for finding groups of genes with similar expression patterns in microarray data analysis. However, hard clustering methods, which assign each gene exactly to one cluster, are poorly suited to the analysis of microarray datasets because in such datasets the clusters of genes frequently overlap. Results In this study we applied the fuzzy partitional clustering method known as Fuzzy C-Means (FCM) to overcome the limitations of hard clustering. To identify the effect of data normalization, we used three normalization methods, the two common scale and location transformations and Lowess normalization methods, to normalize three microarray datasets and three simulated datasets. First we determined the optimal parameters for FCM clustering. We found that the optimal fuzzification parameter in the FCM analysis of a microarray dataset depended on the normalization method applied to the dataset during preprocessing. We additionally evaluated the effect of normalization of noisy datasets on the results obtained when hard clustering or FCM clustering was applied to those datasets. The effects of normalization were evaluated using both simulated datasets and microarray datasets. A comparative analysis showed that the clustering results depended on the normalization method used and the noisiness of the data. In particular, the selection of the fuzzification parameter value for the FCM method was sensitive to the normalization method used for datasets with large variations across samples. Conclusion Lowess normalization is more robust for clustering of genes from general microarray data than the two common scale and location adjustment methods

  11. Scientific Symposium “Small Solution for Big Water-Related Problems: Innovative Microarrays and Small Sensors to Cope with Water Quality and Food Security”

    PubMed Central

    Marcheggiani, Stefania; Spurio, Roberto; Cimarelli, Lucia; Tito, Duarte; Mancini, Laura

    2015-01-01

    This issue presents the conclusive results of two European Commission funded Projects, namely Universal Microarrays for the Evaluation of Fresh-water Quality Based on Detection of Pathogens and their Toxins (MicroAQUA) and Rationally Designed Aquatic Receptors (RADAR). These projects focused their activities on the quality of drinking water as an extremely important factor for public health of humans and animals. The MicroAQUA Project aimed at developing a universal microarray chip for the detection of various pathogens (cyanobacteria, bacteria, viruses and parasitic protozoa) and their toxins in waters. In addition, the project included the detection of select species of diatoms, which represent reliable bio-indicators to assess overall water quality. Large numbers of compounds are released into the environment; some of these are toxins such as endocrine disrupting compounds (EDCs) and can affect the endocrine, immune and nervous systems of a wide range of animals causing alterations such as reproductive disorders and cancer. Detection of these contaminants in water systems is important to protect sensitive environmental sites and reduce the risk of toxins entering the food chain. A modular platform for monitoring toxins in water and food production facilities, using biosensors derived from aquatic organisms, was the main goal of RADAR Project.

  12. A Maximum A Posteriori Probability and Time-Varying Approach for Inferring Gene Regulatory Networks from Time Course Gene Microarray Data.

    PubMed

    Chan, Shing-Chow; Zhang, Li; Wu, Ho-Chun; Tsui, Kai-Man

    2015-01-01

    Unlike most conventional techniques with static model assumption, this paper aims to estimate the time-varying model parameters and identify significant genes involved at different timepoints from time course gene microarray data. We first formulate the parameter identification problem as a new maximum a posteriori probability estimation problem so that prior information can be incorporated as regularization terms to reduce the large estimation variance of the high dimensional estimation problem. Under this framework, sparsity and temporal consistency of the model parameters are imposed using L1-regularization and novel continuity constraints, respectively. The resulting problem is solved using the L-BFGS method with the initial guess obtained from the partial least squares method. A novel forward validation measure is also proposed for the selection of regularization parameters, based on both forward and current prediction errors. The proposed method is evaluated using a synthetic benchmark testing data and a publicly available yeast Saccharomyces cerevisiae cell cycle microarray data. For the latter particularly, a number of significant genes identified at different timepoints are found to be biological significant according to previous findings in biological experiments. These suggest that the proposed approach may serve as a valuable tool for inferring time-varying gene regulatory networks in biological studies. PMID:26357083

  13. Enzyme Microarrays Assembled by Acoustic Dispensing Technology

    PubMed Central

    Wong, E. Y.; Diamond, S. L.

    2008-01-01

    Miniaturizing bioassays to the nanoliter scale for high-throughput screening reduces the consumption of reagents that are expensive or difficult to handle. Utilizing acoustic dispensing technology, nanodroplets containing 10 µM ATP (3 µCi/µL 32P) and reaction buffer in 10% glycerol were positionally dispensed to the surface of glass slides to form 40 nL compartments (100 droplets/slide) for Pim1 (Proviral integration site 1) kinase reactions. The reactions were activated by dispensing 4 nL of various levels of a pyridocarbazolo-cyclopentadienyl ruthenium-complex Pim1 inhibitor, followed by dispensing 4 nL of a Pim1 kinase and peptide substrate solution to achieve final concentrations of 150 nM enzyme and 10 µM substrate. The microarray was incubated at 30°C (97% Rh) for 1.5 hr. The spots were then blotted to phosphocellulose membranes to capture phosphorylated substrate. Using phosphor imaging to quantify the washed membranes, the assay showed that, for doses of inhibitor from 0.75 µM to 3 µM, Pim1 was increasingly inhibited. Signal-to-background ratios were as high as 165 and average coefficients of variation (CVs) for the assay were ~20%. CVs for dispensing typical working buffers were under 5%. Thus, microarrays assembled by acoustic dispensing are promising as cost-effective tools that can be used in protein assay development. PMID:18616925

  14. Laser direct writing of biomolecule microarrays

    NASA Astrophysics Data System (ADS)

    Serra, P.; Fernández-Pradas, J. M.; Berthet, F. X.; Colina, M.; Elvira, J.; Morenza, J. L.

    Protein-based biosensors are highly efficient tools for protein detection and identification. The production of these devices requires the manipulation of tiny amounts of protein solutions in conditions preserving their biological properties. In this work, laser induced forward transfer (LIFT) was used for spotting an array of a purified bacterial antigen in order to check the viability of this technique for the production of protein microarrays. A pulsed Nd:YAG laser beam (355 nm wavelength, 10 ns pulse duration) was used to transfer droplets of a solution containing the Treponema pallidum 17 kDa protein antigen on a glass slide. Optical microscopy showed that a regular array of micrometric droplets could be precisely and uniformly spotted onto a solid substrate. Subsequently, it was proved that LIFT deposition of a T. pallidum 17 kDa antigen onto nylon-coated glass slides preserves its antigenic reactivity and diagnostic properties. These results support that LIFT is suitable for the production of protein microarrays and pave the way for future diagnostics applications.

  15. Segmentation of prostate cancer tissue microarray images

    NASA Astrophysics Data System (ADS)

    Cline, Harvey E.; Can, Ali; Padfield, Dirk

    2006-02-01

    Prostate cancer is diagnosed by histopathology interpretation of hematoxylin and eosin (H and E)-stained tissue sections. Gland and nuclei distributions vary with the disease grade. The morphological features vary with the advance of cancer where the epithelial regions grow into the stroma. An efficient pathology slide image analysis method involved using a tissue microarray with known disease stages. Digital 24-bit RGB images were acquired for each tissue element on the slide with both 10X and 40X objectives. Initial segmentation at low magnification was accomplished using prior spectral characteristics from a training tissue set composed of four tissue clusters; namely, glands, epithelia, stroma and nuclei. The segmentation method was automated by using the training RGB values as an initial guess and iterating the averaging process 10 times to find the four cluster centers. Labels were assigned to the nearest cluster center in red-blue spectral feature space. An automatic threshold algorithm separated the glands from the tissue. A visual pseudo color representation of 60 segmented tissue microarray image was generated where white, pink, red, blue colors represent glands, epithelia, stroma and nuclei, respectively. The higher magnification images provided refined nuclei morphology. The nuclei were detected with a RGB color space principle component analysis that resulted in a grey scale image. The shape metrics such as compactness, elongation, minimum and maximum diameters were calculated based on the eigenvalues of the best-fitting ellipses to the nuclei.

  16. Enzyme microarrays assembled by acoustic dispensing technology.

    PubMed

    Wong, E Y; Diamond, S L

    2008-10-01

    Miniaturizing bioassays to the nanoliter scale for high-throughput screening reduces the consumption of reagents that are expensive or difficult to handle. Through the use of acoustic dispensing technology, nanodroplets containing 10 microM ATP (3 microCi/microL (32)P) and reaction buffer in 10% glycerol were positionally dispensed to the surface of glass slides to form 40-nL compartments (100 droplets/slide) for Pim1 (proviral integration site 1) kinase reactions. The reactions were activated by dispensing 4 nL of various levels of a pyridocarbazolo-cyclopentadienyl ruthenium complex Pim1 inhibitor, followed by dispensing 4 nL of a Pim1 kinase and peptide substrate solution to achieve final concentrations of 150 nM enzyme and 10 microM substrate. The microarray was incubated at 30 degrees C (97% R(h)) for 1.5 h. The spots were then blotted to phosphocellulose membranes to capture phosphorylated substrate. With phosphor imaging to quantify the washed membranes, the assay showed that, for doses of inhibitor from 0.75 to 3 microM, Pim1 was increasingly inhibited. Signal-to-background ratios were as high as 165, and average coefficients of variation for the assay were approximately 20%. Coefficients of variation for dispensing typical working buffers were under 5%. Thus, microarrays assembled by acoustic dispensing are promising as cost-effective tools that can be used in protein assay development. PMID:18616925

  17. Label-free detection repeatability of protein microarrays by oblique-incidence reflectivity difference method

    NASA Astrophysics Data System (ADS)

    Dai, Jun; Li, Lin; Wang, JingYi; He, LiPing; Lu, HuiBin; Ruan, KangCheng; Jin, KuiJuan; Yang, GuoZhen

    2012-12-01

    We examine the repeatabilities of oblique-incidence reflectivity difference (OIRD) method for label-free detecting biological molecular interaction using protein microarrays. The experimental results show that the repeatabilities are the same in a given microarray or microarray-microarray and are consistent, indicating that OIRD is a promising label-free detection technique for biological microarrays.

  18. Detecting variants with Metabolic Design, a new software tool to design probes for explorative functional DNA microarray development

    PubMed Central

    2010-01-01

    Background Microorganisms display vast diversity, and each one has its own set of genes, cell components and metabolic reactions. To assess their huge unexploited metabolic potential in different ecosystems, we need high throughput tools, such as functional microarrays, that allow the simultaneous analysis of thousands of genes. However, most classical functional microarrays use specific probes that monitor only known sequences, and so fail to cover the full microbial gene diversity present in complex environments. We have thus developed an algorithm, implemented in the user-friendly program Metabolic Design, to design efficient explorative probes. Results First we have validated our approach by studying eight enzymes involved in the degradation of polycyclic aromatic hydrocarbons from the model strain Sphingomonas paucimobilis sp. EPA505 using a designed microarray of 8,048 probes. As expected, microarray assays identified the targeted set of genes induced during biodegradation kinetics experiments with various pollutants. We have then confirmed the identity of these new genes by sequencing, and corroborated the quantitative discrimination of our microarray by quantitative real-time PCR. Finally, we have assessed metabolic capacities of microbial communities in soil contaminated with aromatic hydrocarbons. Results show that our probe design (sensitivity and explorative quality) can be used to study a complex environment efficiently. Conclusions We successfully use our microarray to detect gene expression encoding enzymes involved in polycyclic aromatic hydrocarbon degradation for the model strain. In addition, DNA microarray experiments performed on soil polluted by organic pollutants without prior sequence assumptions demonstrate high specificity and sensitivity for gene detection. Metabolic Design is thus a powerful, efficient tool that can be used to design explorative probes and monitor metabolic pathways in complex environments, and it may also be used to

  19. Production of tissue microarrays, immunohistochemistry staining and digitalization within the human protein atlas.

    PubMed

    Kampf, Caroline; Olsson, Ingmarie; Ryberg, Urban; Sjöstedt, Evelina; Pontén, Fredrik

    2012-01-01

    The tissue microarray (TMA) technology provides the means for high-throughput analysis of multiple tissues and cells. The technique is used within the Human Protein Atlas project for global analysis of protein expression patterns in normal human tissues, cancer and cell lines. Here we present the assembly of 1 mm cores, retrieved from microscopically selected representative tissues, into a single recipient TMA block. The number and size of cores in a TMA block can be varied from approximately forty 2 mm cores to hundreds of 0.6 mm cores. The advantage of using TMA technology is that large amount of data can rapidly be obtained using a single immunostaining protocol to avoid experimental variability. Importantly, only limited amount of scarce tissue is needed, which allows for the analysis of large patient cohorts (1 2). Approximately 250 consecutive sections (4 μm thick) can be cut from a TMA block and used for immunohistochemical staining to determine specific protein expression patterns for 250 different antibodies. In the Human Protein Atlas project, antibodies are generated towards all human proteins and used to acquire corresponding protein profiles in both normal human tissues from 144 individuals and cancer tissues from 216 different patients, representing the 20 most common forms of human cancer. Immunohistochemically stained TMA sections on glass slides are scanned to create high-resolution images from which pathologists can interpret and annotate the outcome of immunohistochemistry. Images together with corresponding pathology-based annotation data are made publically available for the research community through the Human Protein Atlas portal (www.proteinatlas.org) (Figure 1) (3 4). The Human Protein Atlas provides a map showing the distribution and relative abundance of proteins in the human body. The current version contains over 11 million images with protein expression data for 12.238 unique proteins, corresponding to more than 61% of all proteins

  20. ZODET: Software for the Identification, Analysis and Visualisation of Outlier Genes in Microarray Expression Data

    PubMed Central

    Roden, Daniel L.; Sewell, Gavin W.; Lobley, Anna; Levine, Adam P.; Smith, Andrew M.; Segal, Anthony W.

    2014-01-01

    Summary Complex human diseases can show significant heterogeneity between patients with the same phenotypic disorder. An outlier detection strategy was developed to identify variants at the level of gene transcription that are of potential biological and phenotypic importance. Here we describe a graphical software package (z-score outlier detection (ZODET)) that enables identification and visualisation of gross abnormalities in gene expression (outliers) in individuals, using whole genome microarray data. Mean and standard deviation of expression in a healthy control cohort is used to detect both over and under-expressed probes in individual test subjects. We compared the potential of ZODET to detect outlier genes in gene expression datasets with a previously described statistical method, gene tissue index (GTI), using a simulated expression dataset and a publicly available monocyte-derived macrophage microarray dataset. Taken together, these results support ZODET as a novel approach to identify outlier genes of potential pathogenic relevance in complex human diseases. The algorithm is implemented using R packages and Java. Availability The software is freely available from http://www.ucl.ac.uk/medicine/molecular-medicine/publications/microarray-outlier-analysis. PMID:24416128

  1. 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.

  2. Variation of RNA Quality and Quantity Are Major Sources of Batch Effects in Microarray Expression Data

    PubMed Central

    Fasold, Mario; Binder, Hans

    2014-01-01

    The great utility of microarrays for genome-scale expression analysis is challenged by the widespread presence of batch effects, which bias expression measurements in particular within large data sets. These unwanted technical artifacts can obscure biological variation and thus significantly reduce the reliability of the analysis results. It is largely unknown which are the predominant technical sources leading to batch effects. We here quantitatively assess the prevalence and impact of several known technical effects on microarray expression results. Particularly, we focus on important factors such as RNA degradation, RNA quantity, and sequence biases including multiple guanine effects. We find that the common variation of RNA quality and RNA quantity can not only yield low-quality expression results, but that both factors also correlate with batch effects and biological characteristics of the samples.

  3. Array2BIO: A Comprehensive Suite of Utilities for the Analysis of Microarray Data

    SciTech Connect

    Loots, G G; Chain, P G; Mabery, S; Rasley, A; Garcia, E; Ovcharenko, I

    2006-02-13

    We have developed an integrative and automated toolkit for the analysis of Affymetrix microarray data, named Array2BIO. It identifies groups of coexpressed genes using two complementary approaches--comparative analysis of signal versus control microarrays and clustering analysis of gene expression across different conditions. The identified genes are assigned to functional categories based on the Gene Ontology classification, and a detection of corresponding KEGG protein interaction pathways. Array2BIO reliably handles low-expressor genes and provides a set of statistical methods to quantify the odds of observations, including the Benjamini-Hochberg and Bonferroni multiple testing corrections. Automated interface with the ECR Browser provides evolutionary conservation analysis of identified gene loci while the interconnection with Creme allows high-throughput analysis of human promoter regions and prediction of gene regulatory elements that underlie the observed expression patterns. Array2BIO is publicly available at http://array2bio.dcode.org.

  4. Microbial Diagnostic Microarrays for the Detection and Typing of Food- and Water-Borne (Bacterial) Pathogens

    PubMed Central

    Kostić, Tanja; Sessitsch, Angela

    2011-01-01

    Reliable and sensitive pathogen detection in clinical and environmental (including food and water) samples is of greatest importance for public health. Standard microbiological methods have several limitations and improved alternatives are needed. Most important requirements for reliable analysis include: (i) specificity; (ii) sensitivity; (iii) multiplexing potential; (iv) robustness; (v) speed; (vi) automation potential; and (vii) low cost. Microarray technology can, through its very nature, fulfill many of these requirements directly and the remaining challenges have been tackled. In this review, we attempt to compare performance characteristics of the microbial diagnostic microarrays developed for the detection and typing of food and water pathogens, and discuss limitations, points still to be addressed and issues specific for the analysis of food, water and environmental samples.

  5. Experimental Approaches to Microarray Analysis of Tumor Samples

    ERIC Educational Resources Information Center

    Furge, Laura Lowe; Winter, Michael B.; Meyers, Jacob I.; Furge, Kyle A.

    2008-01-01

    Comprehensive measurement of gene expression using high-density nucleic acid arrays (i.e. microarrays) has become an important tool for investigating the molecular differences in clinical and research samples. Consequently, inclusion of discussion in biochemistry, molecular biology, or other appropriate courses of microarray technologies has…

  6. Removal of hybridization and scanning noise from microarrays.

    PubMed

    Gopalappa, Chaitra; Das, Tapas K; Enkemann, Steven; Eschrich, Steven

    2009-09-01

    Microarray technology for measuring gene expression values has created significant opportunities for advances in disease diagnosis and individualized treatment planning. However, the random noise introduced by the sample preparation, hybridization, and scanning stages of microarray processing creates significant inaccuracies in the gene expression levels, and hence presents a major barrier in realizing the anticipated advances. Literature presents several methodologies for noise reduction, which can be broadly categorized as: 1) model based approaches for estimation and removal of hybridization noise; 2) approaches using commonly available image denoising tools; and 3) approaches involving the need for control sample(s). In this paper, we present a novel methodology for identifying and removing hybridization and scanning noise from microarray images, using a dual-tree-complex-wavelet-transform-based multiresolution analysis coupled with bivariate shrinkage thresholding. The key features of our methodology include consideration of inherent features and type of noise specific to microarray images, and the ability to work with a single microarray without needing a control. Our methodology is first benchmarked on a fabricated dataset that mimics a real microarray probe dataset. Thereafter, our methodology is tested on datasets obtained from a number of Affymetrix GeneChip human genome HG-U133 Plus 2.0 arrays, processed on HCT-116 cell line at the Microarray Core Facility of Moffitt Cancer Center and Research Institute. The results indicate an appreciable improvement in the quality of the microarray data. PMID:20051337

  7. Applications of microarray technology in breast cancer research

    PubMed Central

    Cooper, Colin S

    2001-01-01

    Microarrays provide a versatile platform for utilizing information from the Human Genome Project to benefit human health. This article reviews the ways in which microarray technology may be used in breast cancer research. Its diverse applications include monitoring chromosome gains and losses, tumour classification, drug discovery and development, DNA resequencing, mutation detection and investigating the mechanism of tumour development. PMID:11305951

  8. Demonstrating a Multi-drug Resistant Mycobacterium tuberculosis Amplification Microarray

    PubMed Central

    Linger, Yvonne; Kukhtin, Alexander; Golova, Julia; Perov, Alexander; Qu, Peter; Knickerbocker, Christopher; Cooney, Christopher G.; Chandler, Darrell P.

    2014-01-01

    Simplifying microarray workflow is a necessary first step for creating MDR-TB microarray-based diagnostics that can be routinely used in lower-resource environments. An amplification microarray combines asymmetric PCR amplification, target size selection, target labeling, and microarray hybridization within a single solution and into a single microfluidic chamber. A batch processing method is demonstrated with a 9-plex asymmetric master mix and low-density gel element microarray for genotyping multi-drug resistant Mycobacterium tuberculosis (MDR-TB). The protocol described here can be completed in 6 hr and provide correct genotyping with at least 1,000 cell equivalents of genomic DNA. Incorporating on-chip wash steps is feasible, which will result in an entirely closed amplicon method and system. The extent of multiplexing with an amplification microarray is ultimately constrained by the number of primer pairs that can be combined into a single master mix and still achieve desired sensitivity and specificity performance metrics, rather than the number of probes that are immobilized on the array. Likewise, the total analysis time can be shortened or lengthened depending on the specific intended use, research question, and desired limits of detection. Nevertheless, the general approach significantly streamlines microarray workflow for the end user by reducing the number of manually intensive and time-consuming processing steps, and provides a simplified biochemical and microfluidic path for translating microarray-based diagnostics into routine clinical practice. PMID:24796567

  9. Application of Microarray Technology to Investigate Salmonella and Antimicrobial Resistance

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Microarrays have been developed for the study of various aspects of Salmonella, which is a model system for investigating pathogenesis. Microarrays were used to analyze the gene expression of Salmonella in various environments that mimic the host environment and these studies have helped to elucidat...

  10. ARACNe-based inference, using curated microarray data, of Arabidopsis thaliana root transcriptional regulatory networks

    PubMed Central

    2014-01-01

    Background Uncovering the complex transcriptional regulatory networks (TRNs) that underlie plant and animal development remains a challenge. However, a vast amount of data from public microarray experiments is available, which can be subject to inference algorithms in order to recover reliable TRN architectures. Results In this study we present a simple bioinformatics methodology that uses public, carefully curated microarray data and the mutual information algorithm ARACNe in order to obtain a database of transcriptional interactions. We used data from Arabidopsis thaliana root samples to show that the transcriptional regulatory networks derived from this database successfully recover previously identified root transcriptional modules and to propose new transcription factors for the SHORT ROOT/SCARECROW and PLETHORA pathways. We further show that these networks are a powerful tool to integrate and analyze high-throughput expression data, as exemplified by our analysis of a SHORT ROOT induction time-course microarray dataset, and are a reliable source for the prediction of novel root gene functions. In particular, we used our database to predict novel genes involved in root secondary cell-wall synthesis and identified the MADS-box TF XAL1/AGL12 as an unexpected participant in this process. Conclusions This study demonstrates that network inference using carefully curated microarray data yields reliable TRN architectures. In contrast to previous efforts to obtain root TRNs, that have focused on particular functional modules or tissues, our root transcriptional interactions provide an overview of the transcriptional pathways present in Arabidopsis thaliana roots and will likely yield a plethora of novel hypotheses to be tested experimentally. PMID:24739361

  11. APPLICATION OF CDNA MICROARRAY TECHNOLOGY TO IN VITRO TOXICOLOGY AND THE SELECTION OF GENES FOR A REAL TIME RT-PCR-BASED SCREEN FOR OXIDATIVE STRESS IN HEP-G2 CELLS

    EPA Science Inventory

    Large-scale analysis of gene expression using cDNA microarrays promises the
    rapid detection of the mode of toxicity for drugs and other chemicals. cDNA
    microarrays were used to examine chemically-induced alterations of gene
    expression in HepG2 cells exposed to oxidative ...

  12. Development and validation of a flax (Linum usitatissimum L.) gene expression oligo microarray

    PubMed Central

    2010-01-01

    flax varieties. Conclusion All results suggest that our high-density flax oligo-microarray platform can be used as a very sensitive tool for analyzing gene expression in a large variety of tissues as well as in different cultivars. Moreover, this highly reliable platform can also be used for the quantification of mRNA transcriptional profiling in different flax tissues. PMID:20964859

  13. Microarray multiplex assay for the simultaneous detection and discrimination of hepatitis B, hepatitis C, and human immunodeficiency type-1 viruses in human blood samples

    SciTech Connect

    Hsia, Chu Chieh . E-mail: chuchieh.hsia@fda.hhs.gov; Chizhikov, Vladimir E.; Yang, Amy X.; Selvapandiyan, Angamuthu; Hewlett, Indira; Duncan, Robert; Puri, Raj K.; Nakhasi, Hira L.; Kaplan, Gerardo G.

    2007-05-18

    Hepatitis B virus (HBV), hepatitis C virus (HCV), and human immunodeficiency virus type-1 (HIV-1) are transfusion-transmitted human pathogens that have a major impact on blood safety and public health worldwide. We developed a microarray multiplex assay for the simultaneous detection and discrimination of these three viruses. The microarray consists of 16 oligonucleotide probes, immobilized on a silylated glass slide. Amplicons from multiplex PCR were labeled with Cy-5 and hybridized to the microarray. The assay detected 1 International Unit (IU), 10 IU, 20 IU of HBV, HCV, and HIV-1, respectively, in a single multiplex reaction. The assay also detected and discriminated the presence of two or three of these viruses in a single sample. Our data represent a proof-of-concept for the possible use of highly sensitive multiplex microarray assay to screen and confirm the presence of these viruses in blood donors and patients.

  14. A Comparative Study of Normalization Methods Used in Statistical Analysis of Oligonucleotide Microarray Data

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Normalization methods used in the statistical analysis of oligonucleotide microarray data were evaluated. The oligonucleotide microarray is considered an efficient analytical tool for analyzing thousands of genes simultaneously in a single experiment. However, systematic variation in microarray, ori...

  15. Genomic-Wide Analysis with Microarrays in Human Oncology

    PubMed Central

    Inaoka, Kenichi; Inokawa, Yoshikuni; Nomoto, Shuji

    2015-01-01

    DNA microarray technologies have advanced rapidly and had a profound impact on examining gene expression on a genomic scale in research. This review discusses the history and development of microarray and DNA chip devices, and specific microarrays are described along with their methods and applications. In particular, microarrays have detected many novel cancer-related genes by comparing cancer tissues and non-cancerous tissues in oncological research. Recently, new methods have been in development, such as the double-combination array and triple-combination array, which allow more effective analysis of gene expression and epigenetic changes. Analysis of gene expression alterations in precancerous regions compared with normal regions and array analysis in drug-resistance cancer tissues are also successfully performed. Compared with next-generation sequencing, a similar method of genome analysis, several important differences distinguish these techniques and their applications. Development of novel microarray technologies is expected to contribute to further cancer research.

  16. An ultralow background substrate for protein microarray technology.

    PubMed

    Feng, Hui; Zhang, Qingyang; Ma, Hongwei; Zheng, Bo

    2015-08-21

    We herein report an ultralow background substrate for protein microarrays. Conventional protein microarray substrates often suffer from non-specific protein adsorption and inhomogeneous spot morphology. Consequently, surface treatment and a suitable printing solution are required to improve the microarray performance. In the current work, we improved the situation by developing a new microarray substrate based on a fluorinated ethylene propylene (FEP) membrane. A polydopamine microspot array was fabricated on the FEP membrane, with proteins conjugated to the FEP surface through polydopamine. Uniform microspots were obtained on FEP without the application of a special printing solution. The modified FEP membrane demonstrated ultralow background signal and was applied in protein and peptide microarray analysis. PMID:26134063

  17. Chapter 9 - Methylation Analysis by Microarray

    PubMed Central

    Deatherage, Daniel E.; Potter, Dustin; Yan, Pearlly S.; Huang, Tim H.-M.; Lin, Shili

    2010-01-01

    Differential Methylation Hybridization (DMH) is a high-throughput DNA methylation screening tool that utilizes methylation-sensitive restriction enzymes to profile methylated fragments by hybridizing them to a CpG island microarray. This array contains probes spanning all the 27,800 islands annotated in the UCSC Genome Browser. Herein we describe a DMH protocol with clearly identified quality control points. In this manner, samples that are unlikely to provide good read-outs for differential methylation profiles between the test and the control samples will be identified and repeated with appropriate modifications. The step-by-step laboratory DMH protocol is described. In addition, we provide descriptions regarding DMH data analysis, including image quantification, background correction, and statistical procedures for both exploratory analysis and more formal inferences. Issues regarding quality control are addressed as well. PMID:19488875

  18. Uses of Dendrimers for DNA Microarrays

    PubMed Central

    Caminade, Anne-Marie; Padié, Clément; Laurent, Régis; Maraval, Alexandrine; Majoral, Jean-Pierre

    2006-01-01

    Biosensors such as DNA microarrays and microchips are gaining an increasing importance in medicinal, forensic, and environmental analyses. Such devices are based on the detection of supramolecular interactions called hybridizations that occur between complementary oligonucleotides, one linked to a solid surface (the probe), and the other one to be analyzed (the target). This paper focuses on the improvements that hyperbranched and perfectly defined nanomolecules called dendrimers can provide to this methodology. Two main uses of dendrimers for such purpose have been described up to now; either the dendrimer is used as linker between the solid surface and the probe oligonucleotide, or the dendrimer is used as a multilabeled entity linked to the target oligonucleotide. In the first case the dendrimer generally induces a higher loading of probes and an easier hybridization, due to moving away the solid phase. In the second case the high number of localized labels (generally fluorescent) induces an increased sensitivity, allowing the detection of small quantities of biological entities.

  19. Meta-analysis of incomplete microarray studies.

    PubMed

    Zollinger, Alix; Davison, Anthony C; Goldstein, Darlene R

    2015-10-01

    Meta-analysis of microarray studies to produce an overall gene list is relatively straightforward when complete data are available. When some studies lack information-providing only a ranked list of genes, for example-it is common to reduce all studies to ranked lists prior to combining them. Since this entails a loss of information, we consider a hierarchical Bayes approach to meta-analysis using different types of information from different studies: the full data matrix, summary statistics, or ranks. The model uses an informative prior for the parameter of interest to aid the detection of differentially expressed genes. Simulations show that the new approach can give substantial power gains compared with classical meta-analysis and list aggregation methods. A meta-analysis of 11 published studies with different data types identifies genes known to be involved in ovarian cancer and shows significant enrichment. PMID:25987649

  20. DNA microarrays on a mesospaced surface

    NASA Astrophysics Data System (ADS)

    Hong, Bong Jin; Park, Joon Won

    2004-12-01

    A dendron having nine carboxylic acid groups at the end of the branches and a protected amine at the apex was allowed to form a molecular layer on the aminosilylated surface through multipoint ionic attraction. It was found that a compact and smooth monolayer was obtained at appropriate condition. The film quality was maintained successfully after deprotecting CBZ group with trimethylsilyl iodide. The surface density of the primary amine after the deprotection was measured with fluorometry, and 0.1-0.2 amine group per 1 nm2 was observed. This implies that the spacing between the amine functional groups is 24-34 Å in hexagonal close packing (hcp) model. In addition, DNA microarrays were fabricated successfully on the dendron-modified surface.

  1. Digital microarray analysis for digital artifact genomics

    NASA Astrophysics Data System (ADS)

    Jaenisch, Holger; Handley, James; Williams, Deborah

    2013-06-01

    We implement a Spatial Voting (SV) based analogy of microarray analysis for digital gene marker identification in malware code sections. We examine a famous set of malware formally analyzed by Mandiant and code named Advanced Persistent Threat (APT1). APT1 is a Chinese organization formed with specific intent to infiltrate and exploit US resources. Manidant provided a detailed behavior and sting analysis report for the 288 malware samples available. We performed an independent analysis using a new alternative to the traditional dynamic analysis and static analysis we call Spatial Analysis (SA). We perform unsupervised SA on the APT1 originating malware code sections and report our findings. We also show the results of SA performed on some members of the families associated by Manidant. We conclude that SV based SA is a practical fast alternative to dynamics analysis and static analysis.

  2. Giant Magnetoresistive Sensors for DNA Microarray

    PubMed Central

    Xu, Liang; Yu, Heng; Han, Shu-Jen; Osterfeld, Sebastian; White, Robert L.; Pourmand, Nader; Wang, Shan X.

    2009-01-01

    Giant magnetoresistive (GMR) sensors are developed for a DNA microarray. Compared with the conventional fluorescent sensors, GMR sensors are cheaper, more sensitive, can generate fully electronic signals, and can be easily integrated with electronics and microfluidics. The GMR sensor used in this work has a bottom spin valve structure with an MR ratio of 12%. The single-strand target DNA detected has a length of 20 bases. Assays with DNA concentrations down to 10 pM were performed, with a dynamic range of 3 logs. A double modulation technique was used in signal detection to reduce the 1/f noise in the sensor while circumventing electromagnetic interference. The logarithmic relationship between the magnetic signal and the target DNA concentration can be described by the Temkin isotherm. Furthermore, GMR sensors integrated with microfluidics has great potential of improving the sensitivity to 1 pM or below, and the total assay time can be reduced to less than 1 hour. PMID:20824116

  3. Functional assessment of time course microarray data

    PubMed Central

    Nueda, María José; Sebastián, Patricia; Tarazona, Sonia; García-García, Francisco; Dopazo, Joaquín; Ferrer, Alberto; Conesa, Ana

    2009-01-01

    Motivation Time-course microarray experiments study the progress of gene expression along time across one or several experimental conditions. Most developed analysis methods focus on the clustering or the differential expression analysis of genes and do not integrate functional information. The assessment of the functional aspects of time-course transcriptomics data requires the use of approaches that exploit the activation dynamics of the functional categories to where genes are annotated. Methods We present three novel methodologies for the functional assessment of time-course microarray data. i) maSigFun derives from the maSigPro method, a regression-based strategy to model time-dependent expression patterns and identify genes with differences across series. maSigFun fits a regression model for groups of genes labeled by a functional class and selects those categories which have a significant model. ii) PCA-maSigFun fits a PCA model of each functional class-defined expression matrix to extract orthogonal patterns of expression change, which are then assessed for their fit to a time-dependent regression model. iii) ASCA-functional uses the ASCA model to rank genes according to their correlation to principal time expression patterns and assess functional enrichment on a GSA fashion. We used simulated and experimental datasets to study these novel approaches. Results were compared to alternative methodologies. Results Synthetic and experimental data showed that the different methods are able to capture different aspects of the relationship between genes, functions and co-expression that are biologically meaningful. The methods should not be considered as competitive but they provide different insights into the molecular and functional dynamic events taking place within the biological system under study. PMID:19534758

  4. Lipid Microarray Biosensor for Biotoxin Detection.

    SciTech Connect

    Singh, Anup K.; Throckmorton, Daniel J.; Moran-Mirabal, Jose C.; Edel, Joshua B.; Meyer, Grant D.; Craighead, Harold G.

    2006-05-01

    We present the use of micron-sized lipid domains, patterned onto planar substrates and within microfluidic channels, to assay the binding of bacterial toxins via total internal reflection fluorescence microscopy (TIRFM). The lipid domains were patterned using a polymer lift-off technique and consisted of ganglioside-populated DSPC:cholesterol supported lipid bilayers (SLBs). Lipid patterns were formed on the substrates by vesicle fusion followed by polymer lift-off, which revealed micron-sized SLBs containing either ganglioside GT1b or GM1. The ganglioside-populated SLB arrays were then exposed to either Cholera toxin subunit B (CTB) or Tetanus toxin fragment C (TTC). Binding was assayed on planar substrates by TIRFM down to 1 nM concentration for CTB and 100 nM for TTC. Apparent binding constants extracted from three different models applied to the binding curves suggest that binding of a protein to a lipid-based receptor is strongly affected by the lipid composition of the SLB and by the substrate on which the bilayer is formed. Patterning of SLBs inside microfluidic channels also allowed the preparation of lipid domains with different compositions on a single device. Arrays within microfluidic channels were used to achieve segregation and selective binding from a binary mixture of the toxin fragments in one device. The binding and segregation within the microfluidic channels was assayed with epifluorescence as proof of concept. We propose that the method used for patterning the lipid microarrays on planar substrates and within microfluidic channels can be easily adapted to proteins or nucleic acids and can be used for biosensor applications and cell stimulation assays under different flow conditions. KEYWORDS. Microarray, ganglioside, polymer lift-off, cholera toxin, tetanus toxin, TIRFM, binding constant.4

  5. Image microarrays (IMA): Digital pathology's missing tool

    PubMed Central

    Hipp, Jason; Cheng, Jerome; Pantanowitz, Liron; Hewitt, Stephen; Yagi, Yukako; Monaco, James; Madabhushi, Anant; Rodriguez-canales, Jaime; Hanson, Jeffrey; Roy-Chowdhuri, Sinchita; Filie, Armando C.; Feldman, Michael D.; Tomaszewski, John E.; Shih, Natalie NC.; Brodsky, Victor; Giaccone, Giuseppe; Emmert-Buck, Michael R.; Balis, Ulysses J.

    2011-01-01

    Introduction: The increasing availability of whole slide imaging (WSI) data sets (digital slides) from glass slides offers new opportunities for the development of computer-aided diagnostic (CAD) algorithms. With the all-digital pathology workflow that these data sets will enable in the near future, literally millions of digital slides will be generated and stored. Consequently, the field in general and pathologists, specifically, will need tools to help extract actionable information from this new and vast collective repository. Methods: To address this limitation, we designed and implemented a tool (dCORE) to enable the systematic capture of image tiles with constrained size and resolution that contain desired histopathologic features. Results: In this communication, we describe a user-friendly tool that will enable pathologists to mine digital slides archives to create image microarrays (IMAs). IMAs are to digital slides as tissue microarrays (TMAs) are to cell blocks. Thus, a single digital slide could be transformed into an array of hundreds to thousands of high quality digital images, with each containing key diagnostic morphologies and appropriate controls. Current manual digital image cut-and-paste methods that allow for the creation of a grid of images (such as an IMA) of matching resolutions are tedious. Conclusion: The ability to create IMAs representing hundreds to thousands of vetted morphologic features has numerous applications in education, proficiency testing, consensus case review, and research. Lastly, in a manner analogous to the way conventional TMA technology has significantly accelerated in situ studies of tissue specimens use of IMAs has similar potential to significantly accelerate CAD algorithm development. PMID:22200030

  6. Q-GDEMAR: a general method for the identification of differentially expressed genes in microarrays with unbalanced groups.

    PubMed

    Guebel, Daniel V; Perera-Alberto, Montserrat; Torres, Néstor V

    2016-01-01

    Microarray analysis is a powerful tool to simultaneously determine the pattern of transcription of large amounts of genes. For data post-processing distinct computational methods are currently used that, however, lead to different results regarding the genes expressed differentially. Herein, a new methodology for microarray data analysis named Q-GDEMAR is presented. It combines the quantile characterization of the entire distribution together with the Gaussian deconvolution of the central region of the microarray data distribution. Three discriminant variable variants are proposed that allow us to summarize data and compare groups even when their size is strongly unbalanced. In addition, a simple procedure to compute the false discovery rate (FDR) is also presented. The performance of the method is compared with that observed when using LIMMA (Linear Models Microarray) software as reference. In 58 out of 68 cases, Q-GDEMAR showed a higher sensitivity than LIMMA to detect differentially expressed genes (p = 1 × 10(-10)). The proposed method does not produce biased information, detecting genes with high sensitivity equally well at both tails of the distribution (p = 0.7428). Moreover, all detected genes were associated with very low levels of FDR (median value = 0.67%, interquartile range = 0.87%). Q-GDEMAR can be used as a general method for microarray analysis, but is particularly indicated when the conditions to be compared are unbalanced. The superior performance of Q-GEDEMAR is the consequence of its higher discriminative power and, the fact that it yields a univocal correspondence between the p-values and the values of the discriminating variable. Q-GDEMAR was tested only using Affymetrix microarrays. However, given that it operates after the step of data standardization, it can be used with the same quality features on any of the available mono- or dual-channel microarray platforms. PMID:26563436

  7. Benchmarking a memetic algorithm for ordering microarray data.

    PubMed

    Moscato, P; Mendes, A; Berretta, R

    2007-03-01

    This work introduces a new algorithm for "gene ordering". Given a matrix of gene expression data values, the task is to find a permutation of the gene names list such that genes with similar expression patterns should be relatively close in the permutation. The algorithm is based on a combined approach that integrates a constructive heuristic with evolutionary and Tabu Search techniques in a single methodology. To evaluate the benefits of this method, we compared our results with the current outputs provided by several widely used algorithms in functional genomics. We also compared the results with our own hierarchical clustering method when used in isolation. We show that the use of images, corrupted with known levels of noise, helps to illustrate some aspects of the performance of the algorithms and provide a complementary benchmark for the analysis. The use of these images, with known high-quality solutions, facilitates in some cases the assessment of the methods and helps the software development, validation and reproducibility of results. We also propose two quantitative measures of performance for gene ordering. Using these measures, we make a comparison with probably the most used algorithm (due to Eisen and collaborators, PNAS 1998) using a microarray dataset available on the public domain (the complete yeast cell cycle dataset). PMID:16870322

  8. Do Drug Treatment Facilities Increase Clients’ Exposure to Potential Neighborhood-Level Triggers for Relapse? A Small-Area Assessment of a Large, Public Treatment System

    PubMed Central

    2006-01-01

    Research on drug treatment facility locations has focused narrowly on the issue of geographic proximity to clients. We argue that neighborhood conditions should also enter into the facility location decision and illustrate a formal assessment of neighborhood conditions at facilities in a large, metropolitan area, taking into account conditions clients already face at home. We discuss choice and construction of small-area measures relevant to the drug treatment context, including drug activity, disadvantage, and violence as well as statistical comparisons of clients’ home and treatment locations with respect to these measures. Analysis of 22,707 clients discharged from 494 community-based outpatient and residential treatment facilities that received public funds during 1998–2000 in Los Angeles County revealed no significant mean differences between home and treatment neighborhoods. However, up to 20% of clients are exposed to markedly higher levels of disadvantage, violence, or drug activity where they attend treatment than where they live, suggesting that it is not uncommon for treatment locations to increase clients’ exposure to potential environmental triggers for relapse. Whereas on average both home and treatment locations exhibit higher levels of these measures than the household locations of the general population, substantial variability in public treatment clients’ home neighborhoods calls into question the notion that they hail exclusively from poor, high drug activity areas. Shortcomings of measures available for neighborhood assessment of treatment locations and implications of the findings for other areas of treatment research are also discussed. PMID:16736365

  9. Cost-Effective Large-Scale Occupancy–Abundance Monitoring of Invasive Brushtail Possums (Trichosurus Vulpecula) on New Zealand’s Public Conservation Land

    PubMed Central

    Gormley, Andrew M.; Forsyth, David M.; Wright, Elaine F.; Lyall, John; Elliott, Mike; Martini, Mark; Kappers, Benno; Perry, Mike; McKay, Meredith

    2015-01-01

    There is interest in large-scale and unbiased monitoring of biodiversity status and trend, but there are few published examples of such monitoring being implemented. The New Zealand Department of Conservation is implementing a monitoring program that involves sampling selected biota at the vertices of an 8-km grid superimposed over the 8.6 million hectares of public conservation land that it manages. The introduced brushtail possum (Trichosurus Vulpecula) is a major threat to some biota and is one taxon that they wish to monitor and report on. A pilot study revealed that the traditional method of monitoring possums using leg-hold traps set for two nights, termed the Trap Catch Index, was a constraint on the cost and logistical feasibility of the monitoring program. A phased implementation of the monitoring program was therefore conducted to collect data for evaluating the trade-off between possum occupancy–abundance estimates and the costs of sampling for one night rather than two nights. Reducing trapping effort from two nights to one night along four trap-lines reduced the estimated costs of monitoring by 5.8% due to savings in labour, food and allowances; it had a negligible effect on estimated national possum occupancy but resulted in slightly higher and less precise estimates of relative possum abundance. Monitoring possums for one night rather than two nights would provide an annual saving of NZ$72,400, with 271 fewer field days required for sampling. Possums occupied 60% (95% credible interval; 53–68) of sampling locations on New Zealand’s public conservation land, with a mean relative abundance (Trap Catch Index) of 2.7% (2.0–3.5). Possum occupancy and abundance were higher in forest than in non-forest habitats. Our case study illustrates the need to evaluate relationships between sampling design, cost, and occupancy–abundance estimates when designing and implementing large-scale occupancy–abundance monitoring programs. PMID:26029890

  10. Cost-Effective Large-Scale Occupancy-Abundance Monitoring of Invasive Brushtail Possums (Trichosurus Vulpecula) on New Zealand's Public Conservation Land.

    PubMed

    Gormley, Andrew M; Forsyth, David M; Wright, Elaine F; Lyall, John; Elliott, Mike; Martini, Mark; Kappers, Benno; Perry, Mike; McKay, Meredith

    2015-01-01

    There is interest in large-scale and unbiased monitoring of biodiversity status and trend, but there are few published examples of such monitoring being implemented. The New Zealand Department of Conservation is implementing a monitoring program that involves sampling selected biota at the vertices of an 8-km grid superimposed over the 8.6 million hectares of public conservation land that it manages. The introduced brushtail possum (Trichosurus Vulpecula) is a major threat to some biota and is one taxon that they wish to monitor and report on. A pilot study revealed that the traditional method of monitoring possums using leg-hold traps set for two nights, termed the Trap Catch Index, was a constraint on the cost and logistical feasibility of the monitoring program. A phased implementation of the monitoring program was therefore conducted to collect data for evaluating the trade-off between possum occupancy-abundance estimates and the costs of sampling for one night rather than two nights. Reducing trapping effort from two nights to one night along four trap-lines reduced the estimated costs of monitoring by 5.8% due to savings in labour, food and allowances; it had a negligible effect on estimated national possum occupancy but resulted in slightly higher and less precise estimates of relative possum abundance. Monitoring possums for one night rather than two nights would provide an annual saving of NZ$72,400, with 271 fewer field days required for sampling. Possums occupied 60% (95% credible interval; 53-68) of sampling locations on New Zealand's public conservation land, with a mean relative abundance (Trap Catch Index) of 2.7% (2.0-3.5). Possum occupancy and abundance were higher in forest than in non-forest habitats. Our case study illustrates the need to evaluate relationships between sampling design, cost, and occupancy-abundance estimates when designing and implementing large-scale occupancy-abundance monitoring programs. PMID:26029890

  11. Novel Microarrays for Simultaneous Serodiagnosis of Multiple Antiviral Antibodies

    PubMed Central

    Sivakumar, Ponnurengam Malliappan; Moritsugu, Nozomi; Obuse, Sei; Isoshima, Takashi; Tashiro, Hideo; Ito, Yoshihiro

    2013-01-01

    We developed an automated diagnostic system for the detection of virus-specific immunoglobulin Gs (IgGs) that was based on a microarray platform. We compared efficacies of our automated system with conventional enzyme immunoassays (EIAs). Viruses were immobilized to microarrays using a radical cross-linking reaction that was induced by photo-irradiation. A new photoreactive polymer containing perfluorophenyl azide (PFPA) and poly(ethylene glycol) methacrylate was prepared and coated on plates. Inactivated measles, rubella, mumps, Varicella-Zoster and recombinant Epstein-Barr viruse antigen were added to coated plates, and irradiated with ultraviolet light to facilitate immobilization. Virus-specific IgGs in healthy human sera were assayed using these prepared microarrays and the results obtained compared with those from conventional EIAs. We observed high correlation (0.79–0.96) in the results between the automated microarray technique and EIAs. The microarray-based assay was more rapid, involved less reagents and sample, and was easier to conduct compared with conventional EIA techniques. The automated microarray system was further improved by introducing reagent storage reservoirs inside the chamber, thereby conserving the use of expensive reagents and antibodies. We considered the microarray format to be suitable for rapid and multiple serological diagnoses of viral diseases that could be developed further for clinical applications. PMID:24367491

  12. Novel microarrays for simultaneous serodiagnosis of multiple antiviral antibodies.

    PubMed

    Sivakumar, Ponnurengam Malliappan; Moritsugu, Nozomi; Obuse, Sei; Isoshima, Takashi; Tashiro, Hideo; Ito, Yoshihiro

    2013-01-01

    We developed an automated diagnostic system for the detection of virus-specific immunoglobulin Gs (IgGs) that was based on a microarray platform. We compared efficacies of our automated system with conventional enzyme immunoassays (EIAs). Viruses were immobilized to microarrays using a radical cross-linking reaction that was induced by photo-irradiation. A new photoreactive polymer containing perfluorophenyl azide (PFPA) and poly(ethylene glycol) methacrylate was prepared and coated on plates. Inactivated measles, rubella, mumps, Varicella-Zoster and recombinant Epstein-Barr viruse antigen were added to coated plates, and irradiated with ultraviolet light to facilitate immobilization. Virus-specific IgGs in healthy human sera were assayed using these prepared microarrays and the results obtained compared with those from conventional EIAs. We observed high correlation (0.79-0.96) in the results between the automated microarray technique and EIAs. The microarray-based assay was more rapid, involved less reagents and sample, and was easier to conduct compared with conventional EIA techniques. The automated microarray system was further improved by introducing reagent storage reservoirs inside the chamber, thereby conserving the use of expensive reagents and antibodies. We considered the microarray format to be suitable for rapid and multiple serological diagnoses of viral diseases that could be developed further for clinical applications. PMID:24367491

  13. Time-series microarray data simulation modeled with a case-control label.

    PubMed

    Liu, Y J; Zhang, J Y

    2016-01-01

    With advances in molecular biology, microarray data have become an important resource in the exploration of complex human diseases. Although gene chip technology continues to grow, there are still many barriers to overcome, such as high costs, small sample sizes, complex procedures, poor repeatability, and the dependence on data analysis methods. To avoid these problems, simulation data have a vital role in the study of complex diseases. A simulation method of microarray data is introduced in this study to model the occurrence and development of general diseases. Using classic statistics and control theory, five risk models are proposed. One or more models can be introduced into the baseline simulation dataset with a case-control label. In addition, time-series gene expression data can be generated to model the dynamic evolutionary process of a disease. The prevalence of each model is estimated and disease-associated genes are tested by significance analysis of microarrays. The source code, written in MATLAB, is freely and publicly available at http://sourceforge.net/projects/genesimulation/files/. PMID:27323009

  14. Penalized mixtures of factor analyzers with application to clustering high-dimensional microarray data

    PubMed Central

    Xie, Benhuai; Pan, Wei; Shen, Xiaotong

    2010-01-01

    Motivation: Model-based clustering has been widely used, e.g. in microarray data analysis. Since for high-dimensional data variable selection is necessary, several penalized model-based clustering methods have been proposed tørealize simultaneous variable selection and clustering. However, the existing methods all assume that the variables are independent with the use of diagonal covariance matrices. Results: To model non-independence of variables (e.g. correlated gene expressions) while alleviating the problem with the large number of unknown parameters associated with a general non-diagonal covariance matrix, we generalize the mixture of factor analyzers to that with penalization, which, among others, can effectively realize variable selection. We use simulated data and real microarray data to illustrate the utility and advantages of the proposed method over several existing ones. Contact: weip@biostat.umn.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:20031967

  15. Developing an Efficient and General Strategy for Immobilization of Small Molecules onto Microarrays Using Isocyanate Chemistry

    PubMed Central

    Zhu, Chenggang; Zhu, Xiangdong; Landry, James P.; Cui, Zhaomeng; Li, Quanfu; Dang, Yongjun; Mi, Lan; Zheng, Fengyun; Fei, Yiyan

    2016-01-01

    Small-molecule microarray (SMM) is an effective platform for identifying lead compounds from large collections of small molecules in drug discovery, and efficient immobilization of molecular compounds is a pre-requisite for the success of such a platform. On an isocyanate functionalized surface, we studied the dependence of immobilization efficiency on chemical residues on molecular compounds, terminal residues on isocyanate functionalized surface, lengths of spacer molecules, and post-printing treatment conditions, and we identified a set of optimized conditions that enable us to immobilize small molecules with significantly improved efficiencies, particularly for those molecules with carboxylic acid residues that are known to have low isocyanate reactivity. We fabricated microarrays of 3375 bioactive compounds on isocyanate functionalized glass slides under these optimized conditions and confirmed that immobilization percentage is over 73%. PMID:26999137

  16. Combining nebulization-mediated transfection and polymer microarrays for the rapid determination of optimal transfection substrates.

    PubMed

    Unciti-Broceta, Asier; Díaz-Mochón, Juan J; Mizomoto, Hitoshi; Bradley, Mark

    2008-01-01

    In this manuscript, we report how transfection efficiencies vary as a function of the substrate upon which cells adhere using a polymer microarray platform to allow rapid analysis of a large number of substrates. During these studies, traditional transfection protocols were nonsatisfactory, and thus we developed an approach in which an ultrasonic nebulizer was used to dispense lipoplexes onto cell-based microarrays in the absence of liquid. Under these conditions, droplets were directly deposited onto the cells thereby enhancing transfection. This approach was successfully applied to the transfection of various cell lines immobilized on a library of polyacrylates and permitted the identification of highly efficient transfection/polymer combinations, while showing that specific polymer-cell interactions may promote the efficacy of chemical transfection. PMID:18247582

  17. Fluorescent Protein Nanowire-Mediated Protein Microarrays for Multiplexed and Highly Sensitive Pathogen Detection.

    PubMed

    Men, Dong; Zhou, Juan; Li, Wei; Leng, Yan; Chen, Xinwen; Tao, Shengce; Zhang, Xian-En

    2016-07-13

    Protein microarrays are powerful tools for high-throughput and simultaneous detection of different target molecules in complex biological samples. However, the sensitivity of conventional fluorescence-labeling protein detection methods is limited by the availability of signal molecules for binding to the target molecule. Here, we built a multifunctional fluorescent protein nanowire (FNw) by harnessing self-assembly of yeast amyloid protein. The FNw integrated a large number of fluorescent molecules, thereby enhancing the fluorescent signal output in target detection. The FNw was then combined with protein microarray technology to detect proteins derived from two pathogens, including influenza virus (hemagglutinin 1, HA1) and human immunodeficiency virus (p24 and gp120). The resulting detection sensitivity achieved a 100-fold improvement over a commercially available detection reagent. PMID:27315221

  18. Parallel human genome analysis: Microarray-based expression monitoring of 1000 genes

    SciTech Connect

    Schena, M.; Heller, R.; Chai, A.; Davis, R.W.

    1996-10-01

    Microarrays containing 1046 human cDNAs of unknown sequence were printed on glass with high-speed robotics. These 1.0-cm{sup 2} DNA {open_quotes}chips{close_quotes} were used to quantitatively monitor differential expression of the cognate human genes using a highly sensitive two-color hybridization assay. Array elements that displayed differential expression patterns under given experimental conditions were characterized by sequencing. The identification of known and novel heat shock and phorbol ester-regulated genes in human T cells demonstrates the sensitivity of the assay. Parallel gene analysis with microarrays provides a rapid and efficient method for large-scale human gene discovery. 33 refs., 3 figs., 2 tabs.

  19. The Peptide Microarray-Based Resonance Light Scattering Assay for Sensitively Detecting Intracellular Kinase Activity.

    PubMed

    Li, Tao; Liu, Xia; Liu, Dianjun; Wang, Zhenxin

    2016-01-01

    The peptide microarray technology is a robust, reliable, and efficient technique for large-scale determination of enzyme activities, and high-throughput profiling of substrate/inhibitor specificities of enzymes. Here, the activities of cyclic adenosine monophosphate (cAMP)-dependent protein kinase A (PKA) in different cell lysates have been detected by a peptide microarray-based resonance light scattering (RLS) assay with gold nanoparticle (GNP) probes. Highly sensitive detection of PKA activity in 0.1 μg total cell proteins of SHG-44 (human glioma cell) cell lysate (corresponding to 200 cells) is achieved by a selected peptide substrate. The experimental results also demonstrate that the RLS assay can be employed to evaluate the chemical regulation of intracellular kinase activity. PMID:26490469

  20. Developing an Efficient and General Strategy for Immobilization of Small Molecules onto Microarrays Using Isocyanate Chemistry.

    PubMed

    Zhu, Chenggang; Zhu, Xiangdong; Landry, James P; Cui, Zhaomeng; Li, Quanfu; Dang, Yongjun; Mi, Lan; Zheng, Fengyun; Fei, Yiyan

    2016-01-01

    Small-molecule microarray (SMM) is an effective platform for identifying lead compounds from large collections of small molecules in drug discovery, and efficient immobilization of molecular compounds is a pre-requisite for the success of such a platform. On an isocyanate functionalized surface, we studied the dependence of immobilization efficiency on chemical residues on molecular compounds, terminal residues on isocyanate functionalized surface, lengths of spacer molecules, and post-printing treatment conditions, and we identified a set of optimized conditions that enable us to immobilize small molecules with significantly improved efficiencies, particularly for those molecules with carboxylic acid residues that are known to have low isocyanate reactivity. We fabricated microarrays of 3375 bioactive compounds on isocyanate functionalized glass slides under these optimized conditions and confirmed that immobilization percentage is over 73%. PMID:26999137

  1. Protein Microarrays with Novel Microfluidic Methods: Current Advances

    PubMed Central

    Dixit, Chandra K.; Aguirre, Gerson R.

    2014-01-01

    Microfluidic-based micromosaic technology has allowed the pattering of recognition elements in restricted micrometer scale areas with high precision. This controlled patterning enabled the development of highly multiplexed arrays multiple analyte detection. This arraying technology was first introduced in the beginning of 2001 and holds tremendous potential to revolutionize microarray development and analyte detection. Later, several microfluidic methods were developed for microarray application. In this review we discuss these novel methods and approaches which leverage the property of microfluidic technologies to significantly improve various physical aspects of microarray technology, such as enhanced imprinting homogeneity, stability of the immobilized biomolecules, decreasing assay times, and reduction of the costs and of the bulky instrumentation.

  2. A Perspective on DNA Microarrays in Pathology Research and Practice

    PubMed Central

    Pollack, Jonathan R.

    2007-01-01

    DNA microarray technology matured in the mid-1990s, and the past decade has witnessed a tremendous growth in its application. DNA microarrays have provided powerful tools for pathology researchers seeking to describe, classify, and understand human disease. There has also been great expectation that the technology would advance the practice of pathology. This review highlights some of the key contributions of DNA microarrays to experimental pathology, focusing in the area of cancer research. Also discussed are some of the current challenges in translating utility to clinical practice. PMID:17600117

  3. Imaging combined autoimmune and infectious disease microarrays

    NASA Astrophysics Data System (ADS)

    Ewart, Tom; Raha, Sandeep; Kus, Dorothy; Tarnopolsky, Mark

    2006-09-01

    Bacterial and viral pathogens are implicated in many severe autoimmune diseases, acting through such mechanisms as molecular mimicry, and superantigen activation of T-cells. For example, Helicobacter pylori, well known cause of stomach ulcers and cancers, is also identified in ischaemic heart disease (mimicry of heat shock protein 65), autoimmune pancreatitis, systemic sclerosis, autoimmune thyroiditis (HLA DRB1*0301 allele susceptibility), and Crohn's disease. Successful antibiotic eradication of H.pylori often accompanies their remission. Yet current diagnostic devices, and test-limiting cost containment, impede recognition of the linkage, delaying both diagnosis and therapeutic intervention until the chronic debilitating stage. We designed a 15 minute low cost 39 antigen microarray assay, combining autoimmune, viral and bacterial antigens1. This enables point-of-care serodiagnosis and cost-effective narrowly targeted concurrent antibiotic and monoclonal anti-T-cell and anti-cytokine immunotherapy. Arrays of 26 pathogen and 13 autoimmune antigens with IgG and IgM dilution series were printed in triplicate on epoxysilane covalent binding slides with Teflon well masks. Sera diluted 1:20 were incubated 10 minutes, washed off, anti-IgG-Cy3 (green) and anti-IgM-Dy647 (red) were incubated for 5 minutes, washed off and the slide was read in an ArrayWoRx(e) scanning CCD imager (Applied Precision, Issaquah, WA). As a preliminary model for the combined infectious disease-autoimmune diagnostic microarray we surveyed 98 unidentified, outdated sera that were discarded after Hepatitis B antibody testing. In these, significant IgG or IgM autoantibody levels were found: dsDNA 5, ssDNA 11, Ro 2, RNP 7, SSB 4, gliadin 2, thyroglobulin 13 cases. Since control sera showed no autoantibodies, the high frequency of anti-DNA and anti-thyroglobulin antibodies found in infected sera lend increased support for linkage of infection to subsequent autoimmune disease. Expansion of the antigen

  4. New technologies for fabricating biological microarrays

    NASA Astrophysics Data System (ADS)

    Larson, Bradley James

    This dissertation contains the description of two technologies that we have developed to reduce the cost and improve the quality of spotted biological microarrays. The first is a device, called a fluid microplotter, that uses ultrasonics to deposit spots with diameters of less than 5 microns. It consists of a dispenser, composed of a micropipette fastened to a piece of PZT piezoelectric, attached to a precision positioning system. A gentle pumping of fluid to the surface occurs when the micropipette is driven at specific frequencies. Spots or continuous lines can be deposited in this manner. The small fluid features conserve expensive and limited-quantity biological reagents. We characterize the performance of the microplotter in depositing fluid and examine the theoretical underpinnings of its operation. We present an analytical expression for the diameter of a deposited spot as a function of droplet volume and wettability of a surface and compare it with experimental results. We also examine the resonant properties of the piezoelectric element used to drive the dispenser and relate that to the frequencies at which pumping occurs. Finally, we propose a mechanism to explain the pumping behavior within the microplotter dispenser. The second technology we present is a process that uses a cold plasma and a subsequent in vacuo vapor-phase reaction to terminate a variety of oxide surfaces with epoxide chemical groups. These epoxide groups can react with amine-containing biomolecules to form strong covalent linkages between the biomolecules and the treated surface. The use of a plasma activation step followed by an in vacuo vapor-phase reaction allows for the precise control of surface functional groups, rather than the mixture of functionalities normally produced. This process modifies a range of different oxide surfaces, is fast, consumes a minimal amount of reagents, and produces attachment densities for bound biomolecules that are comparable to or better than

  5. A practical tool for public health surveillance: Semi-automated coding of short injury narratives from large administrative databases using Naïve Bayes algorithms.

    PubMed

    Marucci-Wellman, Helen R; Lehto, Mark R; Corns, Helen L

    2015-11-01

    Public health surveillance programs in the U.S. are undergoing landmark changes with the availability of electronic health records and advancements in information technology. Injury narratives gathered from hospital records, workers compensation claims or national surveys can be very useful for identifying antecedents to injury or emerging risks. However, classifying narratives manually can become prohibitive for large datasets. The purpose of this study was to develop a human-machine system that could be relatively easily tailored to routinely and accurately classify injury narratives from large administrative databases such as workers compensation. We used a semi-automated approach based on two Naïve Bayesian algorithms to classify 15,000 workers compensation narratives into two-digit Bureau of Labor Statistics (BLS) event (leading to injury) codes. Narratives were filtered out for manual review if the algorithms disagreed or made weak predictions. This approach resulted in an overall accuracy of 87%, with consistently high positive predictive values across all two-digit BLS event categories including the very small categories (e.g., exposure to noise, needle sticks). The Naïve Bayes algorithms were able to identify and accurately machine code most narratives leaving only 32% (4853) for manual review. This strategy substantially reduces the need for resources compared with manual review alone. PMID:26412196

  6. Classification and Clustering on Microarray Data for Gene Functional Prediction Using R.

    PubMed

    López-Kleine, Liliana; Kleine, Liliana López; Montaño, Rosa; Torres-Avilés, Francisco

    2016-01-01

    Gene expression data (microarrays and RNA-sequencing data) as well as other kinds of genomic data can be extracted from publicly available genomic data. Here, we explain how to apply multivariate cluster and classification methods on gene expression data. These methods have become very popular and are implemented in freely available software in order to predict the participation of gene products in a specific functional category of interest. Taking into account the availability of data and of these methods, every biological study should apply them in order to obtain knowledge on the organism studied and functional category of interest. A special emphasis is made on the nonlinear kernel classification methods. PMID:25762300

  7. Studying Modification of Aminoglycoside Antibiotics by Resistance-Causing Enzymes via Microarray

    PubMed Central

    Disney, Matthew D.

    2013-01-01

    Widespread bacterial resistance to antibiotics is a significant public health concern. To remain a step ahead of evolving bacteria, new methods to study resistance to antibacterials and to uncover novel antibiotics that evade resistance are urgently needed. Herein, microarray-based methods that have been developed to study aminoglycoside modification by resistance-causing enzymes are reviewed. These arrays can also be used to study the binding of aminoglycoside antibiotics to a mimic of their therapeutic target, the rRNA aminoacyl site (A-site), and how modification by resistance-causing enzymes affects their abilities to bind RNA. PMID:22057534

  8. Studying modification of aminoglycoside antibiotics by resistance-causing enzymes via microarray.

    PubMed

    Disney, Matthew D

    2012-01-01

    Widespread bacterial resistance to antibiotics is a significant public health concern. To remain a step ahead of evolving bacteria, new methods to study resistance to antibacterials and to uncover novel antibiotics that evade resistance are urgently needed. Herein, microarray-based methods that have been developed to study aminoglycoside modification by resistance-causing enzymes are reviewed. These arrays can also be used to study the binding of aminoglycoside antibiotics to a mimic of their therapeutic target, the rRNA aminoacyl site (A-site), and how modification by resistance-causing enzymes affects their abilities to bind RNA. PMID:22057534

  9. Development and Optimization of a Thrombin Sandwich Aptamer Microarray

    PubMed Central

    Meneghello, Anna; Sosic, Alice; Antognoli, Agnese; Cretaio, Erica; Gatto, Barbara

    2012-01-01

    A sandwich microarray employing two distinct aptamers for human thrombin has been optimized for the detection of subnanomolar concentrations of the protein. The aptamer microarray demonstrates high specificity for thrombin, proving that a two-site binding assay with the TBA1 aptamer as capture layer and the TBA2 aptamer as detection layer can ensure great specificity at times and conditions compatible with standard routine analysis of biological samples. Aptamer microarray sensitivity was evaluated directly by fluorescent analysis employing Cy5-labeled TBA2 and indirectly by the use of TBA2-biotin followed by detection with fluorescent streptavidin. Sub-nanomolar LODs were reached in all cases and in the presence of serum, demonstrating that the optimized aptamer microarray can identify thrombin by a low-cost, sensitive and specific method.

  10. Cell-Based Microarrays for In Vitro Toxicology

    NASA Astrophysics Data System (ADS)

    Wegener, Joachim

    2015-07-01

    DNA/RNA and protein microarrays have proven their outstanding bioanalytical performance throughout the past decades, given the unprecedented level of parallelization by which molecular recognition assays can be performed and analyzed. Cell microarrays (CMAs) make use of similar construction principles. They are applied to profile a given cell population with respect to the expression of specific molecular markers and also to measure functional cell responses to drugs and chemicals. This review focuses on the use of cell-based microarrays for assessing the cytotoxicity of drugs, toxins, or chemicals in general. It also summarizes CMA construction principles with respect to the cell types that are used for such microarrays, the readout parameters to assess toxicity, and the various formats that have been established and applied. The review ends with a critical comparison of CMAs and well-established microtiter plate (MTP) approaches.

  11. Cell-Based Microarrays for In Vitro Toxicology.

    PubMed

    Wegener, Joachim

    2015-01-01

    DNA/RNA and protein microarrays have proven their outstanding bioanalytical performance throughout the past decades, given the unprecedented level of parallelization by which molecular recognition assays can be performed and analyzed. Cell microarrays (CMAs) make use of similar construction principles. They are applied to profile a given cell population with respect to the expression of specific molecular markers and also to measure functional cell responses to drugs and chemicals. This review focuses on the use of cell-based microarrays for assessing the cytotoxicity of drugs, toxins, or chemicals in general. It also summarizes CMA construction principles with respect to the cell types that are used for such microarrays, the readout parameters to assess toxicity, and the various formats that have been established and applied. The review ends with a critical comparison of CMAs and well-established microtiter plate (MTP) approaches. PMID:26077916

  12. Applications in high-content functional protein microarrays.

    PubMed

    Moore, Cedric D; Ajala, Olutobi Z; Zhu, Heng

    2016-02-01

    Protein microarray technology provides a versatile platform for characterization of hundreds to thousands of proteins in a parallel and high-throughput manner. Over the last decade, applications of functional protein microarrays in particular have flourished in studying protein function at a systems level and have led to the construction of networks and pathways describing these functions. Relevant areas of research include the detection of various binding properties of proteins, the study of enzyme-substrate relationships, the analysis of host-microbe interactions, and profiling antibody specificity. In addition, discovery of novel biomarkers in autoimmune diseases and cancers is emerging as a major clinical application of functional protein microarrays. In this review, we will summarize the recent advances of functional protein microarrays in both basic and clinical applications. PMID:26599287

  13. Improving Microarray Sample Size Using Bootstrap Data Combination

    PubMed Central

    Phan, John H.; Moffitt, Richard A.; Barrett, Andrea B.; Wang, May D.

    2016-01-01

    Microarray technology has enabled us to simultaneously measure the expression of thousands of genes. Using this high-throughput technology, we can examine subtle genetic changes between biological samples and build predictive models for clinical applications. Although microarrays have dramatically increased the rate of data collection, sample size is still a major issue when selecting features. Previous methods show that combining multiple microarray datasets improves feature selection using simple methods such as fold change. We propose a wrapper-based gene selection technique that combines bootstrap estimated classification errors for individual genes across multiple datasets and reduces the contribution of datasets with high variance. We use the bootstrap because it is an unbiased estimator of classification error that is also effective for small sample data. Coupled with data combination across multiple datasets, we show that our meta-analytic approach improves the biological relevance of gene selection using prostate and renal cancer microarray data. PMID:19164001

  14. Particle-Based Microarrays of Oligonucleotides and Oligopeptides

    PubMed Central

    Nesterov-Mueller, Alexander; Maerkle, Frieder; Hahn, Lothar; Foertsch, Tobias; Schillo, Sebastian; Bykovskaya, Valentina; Sedlmayr, Martyna; Weber, Laura K.; Ridder, Barbara; Soehindrijo, Miriam; Muenster, Bastian; Striffler, Jakob; Bischoff, F. Ralf; Breitling, Frank; Loeffler, Felix F.

    2014-01-01

    In this review, we describe different methods of microarray fabrication based on the use of micro-particles/-beads and point out future tendencies in the development of particle-based arrays. First, we consider oligonucleotide bead arrays, where each bead is a carrier of one specific sequence of oligonucleotides. This bead-based array approach, appearing in the late 1990s, enabled high-throughput oligonucleotide analysis and had a large impact on genome research. Furthermore, we consider particle-based peptide array fabrication using combinatorial chemistry. In this approach, particles can directly participate in both the synthesis and the transfer of synthesized combinatorial molecules to a substrate. Subsequently, we describe in more detail the synthesis of peptide arrays with amino acid polymer particles, which imbed the amino acids inside their polymer matrix. By heating these particles, the polymer matrix is transformed into a highly viscous gel, and thereby, imbedded monomers are allowed to participate in the coupling reaction. Finally, we focus on combinatorial laser fusing of particles for the synthesis of high-density peptide arrays. This method combines the advantages of particles and combinatorial lithographic approaches.

  15. Application of Phenotype Microarray technology to soil microbiology

    NASA Astrophysics Data System (ADS)

    Mocali, Stefano

    2016-04-01

    It is well established that soil microorganisms are extremely diverse and only a small fraction has been successfully cultured in the laboratory. Furthermore, addressing the functionality of genomes is one of the most important and challenging tasks of today's biology. In particular the ability to link genotypes to corresponding phenotypes is of interest in the reconstruction and biotechnological manipulation of metabolic pathways. High-throughput culture in micro wells provides a method for rapid screening of a wide variety of growth conditions and commercially available plates contain a large number of substrates, nutrient sources, and inhibitors, which can provide an assessment of the phenotype of an organism. Thus, over the last years, Phenotype Microarray (PM) technology has been used to address many specific issues related to the metabolic functionality of microorganisms. However, computational tools that could directly link PM data with the gene(s) of interest followed by the extraction of information on gene-phenotype correlation are still missing. Here potential applications of phenotype arrays to soil microorganisms, use of the plates in stress response studies and for assessment of phenotype of environmental communities are described. Considerations and challenges in data interpretation and visualization, including data normalization, statistics, and curve fitting are also discussed. In particular, here we present DuctApe, a suite that allows the analysis of both genomic sequences and PM data, to find metabolic differences among PM experiments and to correlate them with KEGG pathways and gene presence/absence patterns.

  16. The VIMOS Public Extragalactic Redshift Survey (VIPERS). An unprecedented view of galaxies and large-scale structure at 0.5 < z < 1.2

    NASA Astrophysics Data System (ADS)

    Guzzo, L.; Scodeggio, M.; Garilli, B.; Granett, B. R.; Fritz, A.; Abbas, U.; Adami, C.; Arnouts, S.; Bel, J.; Bolzonella, M.; Bottini, D.; Branchini, E.; Cappi, A.; Coupon, J.; Cucciati, O.; Davidzon, I.; De Lucia, G.; de la Torre, S.; Franzetti, P.; Fumana, M.; Hudelot, P.; Ilbert, O.; Iovino, A.; Krywult, J.; Le Brun, V.; Le Fèvre, O.; Maccagni, D.; Małek, K.; Marulli, F.; McCracken, H. J.; Paioro, L.; Peacock, J. A.; Polletta, M.; Pollo, A.; Schlagenhaufer, H.; Tasca, L. A. M.; Tojeiro, R.; Vergani, D.; Zamorani, G.; Zanichelli, A.; Burden, A.; Di Porto, C.; Marchetti, A.; Marinoni, C.; Mellier, Y.; Moscardini, L.; Nichol, R. C.; Percival, W. J.; Phleps, S.; Wolk, M.

    2014-06-01

    We describe the construction and general features of VIPERS, the VIMOS Public Extragalactic Redshift Survey. This ESO Large Programme is using the Very Large Telescope with the aim of building a spectroscopic sample of ~ 100 000 galaxies with iAB< 22.5 and 0.5 large-scale structure and galaxy evolution, thanks to a unique combination of volume (~ 5 × 107h-3 Mpc3) and sampling rate (~ 40%), comparable to state-of-the-art surveys of the local Universe, together with extensive multi-band optical and near-infrared photometry. Here we present the survey design, the selection of the source catalogue and the development of the spectroscopic observations. We discuss in detail the overall selection function that results from the combination of the different constituents of the project. This includes the masks arising from the parent photometric sample and the spectroscopic instrumental footprint, together with the weights needed to account for the sampling and the success rates of the observations. Using the catalogue of 53 608 galaxy redshifts composing the forthcoming VIPERS Public Data Release 1 (PDR-1), we provide a first assessment of the quality of the spectroscopic data. The stellar contamination is found to be only 3.2%, endorsing the quality of the star-galaxy separation process and fully confirming the original estimates based on the VVDS data, which also indicate a galaxy incompleteness from this process of only 1.4%. Using a set of 1215 repeated observations, we estimate an rms redshift error σz/ (1 + z) = 4.7 × 10-4 and calibrate the internal spectral quality grading. Benefiting from the combination of size and detailed sampling of this dataset, we conclude by presenting a map showing in unprecedented detail the large-scale distribution of galaxies between 5 and 8 billion years ago. Based on observations

  17. Multiplex Serum Cytokine Immunoassay Using Nanoplasmonic Biosensor Microarrays

    PubMed Central

    Chen, Pengyu; Chung, Meng Ting; McHugh, Walker; Nidetz, Robert; Li, Yuwei; Fu, Jianping; Cornell, Timothy T.; Shanley, Thomas P.; Kurabayashi, Katsuo

    2015-01-01

    Precise monitoring of the rapidly changing immune status during the course of a disease requires multiplex analysis of cytokines from frequently sampled human blood. However, the current lack of rapid, multiplex, and low volume assays makes immune monitoring for clinical decision-making (e.g., critically ill patients) impractical. Without such assays, immune monitoring is even virtually impossible for infants and neonates with infectious diseases and/or immune mediated disorders as access to their blood in large quantities is prohibited. Localized surface plasmon resonance (LSPR)-based microfluidic optical biosensing is a promising approach to fill this technical gap as it could potentially permit real-time refractometric detection of biomolecular binding on a metallic nanoparticle surface and sensor miniaturization, both leading to rapid and sample-sparing analyte analysis. Despite this promise, practical implementation of such a microfluidic assay for cytokine biomarker detection in serum samples has not been established primarily due to the limited sensitivity of LSPR biosensing. Here, we developed a high-throughput, label-free, multiarrayed LSPR optical biosensor device with 480 nanoplasmonic sensing spots in microfluidic channel arrays and demonstrated parallel multiplex immunoassays of six cytokines in a complex serum matrix on a single device chip while overcoming technical limitations. The device was fabricated using easy-to-implement, one-step microfluidic patterning and antibody conjugation of gold nanorods (AuNRs). When scanning the scattering light intensity across the microarrays of AuNR ensembles with dark-field imaging optics, our LSPR biosensing technique allowed for high-sensitivity quantitative cytokine measurements at concentrations down to 5–20 pg/mL from a 1 µL serum sample. Using the nanoplasmonic biosensor microarray device, we demonstrated the ability to monitor the inflammatory responses of infants following cardiopulmonary bypass (CPB

  18. Serologic response in eight alpacas vaccinated by extralabel use of a large animal rabies vaccine during a public health response to a rabid alpaca in South Carolina.

    PubMed

    Wallace, Ryan M; Niezgoda, Michael; Waggoner, Emily A; Blanton, Jesse Dean; Radcliffe, Rachel A

    2016-09-15

    CASE DESCRIPTION A female alpaca, kept at pasture with 12 other female alpacas, 2 crias, and 5 goats, was evaluated because of clinical signs of aggression. CLINICAL FINDINGS The clinical signs of aggression progressed to include biting at other animals as well as disorientation. Three days later, the alpaca was euthanized because of suspicion of rabies virus infection. TREATMENT AND OUTCOME No physical injuries were found at necropsy. Brain tissue specimens were confirmed positive for rabies on the basis of direct fluorescent antibody test results. Molecular typing identified the rabies virus variant as one that is enzootic in raccoons. The farm was placed under quarantine, restricting movement of animals on and off the property for 6 months. To prevent further rabies cases, 14 alpacas (12 adults and 2 crias) were vaccinated by extralabel use of a large animal rabies vaccine. Of the 14 vaccinated alpacas, 8 had paired serum samples obtained immediately before and 21 days after vaccination; all 8 alpacas had adequate serum antirabies antibody production in response to rabies vaccination. As a result of an adequate serologic response, the quarantine was reduced to 3 months. In the year after the index rabies case, no other animals on the farm developed rabies. CLINICAL RELEVANCE Extralabel use of rabies vaccines in camelids was used in the face of a public health investigation. This report provides an example of handling of a rabies case for future public health investigations, which will undoubtedly need to develop ad-hoc rabies vaccination recommendations on the basis of the unique characteristics of the event. PMID:27585106

  19. Questionnaire survey about use of an online appointment booking system in one large tertiary public hospital outpatient service center in China

    PubMed Central

    2014-01-01

    Background As a part of nationwide healthcare reforms, the Chinese government launched web-based appointment systems (WAS) to provide a solution to problems around outpatient appointments and services. These have been in place in all Chinese public tertiary hospitals since 2009. Methods Questionnaires were collected from both patients and doctors in one large tertiary public hospital in Shanghai, China.Data were analyzed to measure their satisfaction and views about the WAS. Results The 1000 outpatients randomly selected for the survey were least satisfied about the waiting time to see a doctor. Even though the WAS provided a much more convenient booking method, only 17% of patients used it. Of the 197 doctors surveyed, over 90% thought it was necessary to provide alternative forms of appointment booking systems for outpatients. However, about 80% of those doctors who were not associated professors would like to provide an ‘on-the-spot’ appointment option, which would lead to longer waits for patients. Conclusions Patients were least satisfied about the waiting times. To effectively reduce appointment-waiting times is therefore an urgent issue. Despite the benefits of using the WAS, most patients still registered via the usual method of queuing, suggesting that hospitals and health service providers should promote and encourage the use of the WAS. Furthermore, Chinese health providers need to help doctors to take others’ opinions or feedback into consideration when treating patients to minimize the gap between patients’ and doctors’ opinions. These findings may provide useful information for both practitioners and regulators, and improve recognition of this efficient and useful booking system, which may have far-reaching and positive implications for China’s ongoing reforms. PMID:24912568

  20. Emerging Use of Gene Expression Microarrays in Plant Physiology

    DOE PAGESBeta

    Wullschleger, Stan D.; Difazio, Stephen P.

    2003-01-01

    Microarrays have become an important technology for the global analysis of gene expression in humans, animals, plants, and microbes. Implemented in the context of a well-designed experiment, cDNA and oligonucleotide arrays can provide highthroughput, simultaneous analysis of transcript abundance for hundreds, if not thousands, of genes. However, despite widespread acceptance, the use of microarrays as a tool to better understand processes of interest to the plant physiologist is still being explored. To help illustrate current uses of microarrays in the plant sciences, several case studies that we believe demonstrate the emerging application of gene expression arrays in plant physiology weremore » selected from among the many posters and presentations at the 2003 Plant and Animal Genome XI Conference. Based on this survey, microarrays are being used to assess gene expression in plants exposed to the experimental manipulation of air temperature, soil water content and aluminium concentration in the root zone. Analysis often includes characterizing transcript profiles for multiple post-treatment sampling periods and categorizing genes with common patterns of response using hierarchical clustering techniques. In addition, microarrays are also providing insights into developmental changes in gene expression associated with fibre and root elongation in cotton and maize, respectively. Technical and analytical limitations of microarrays are discussed and projects attempting to advance areas of microarray design and data analysis are highlighted. Finally, although much work remains, we conclude that microarrays are a valuable tool for the plant physiologist interested in the characterization and identification of individual genes and gene families with potential application in the fields of agriculture, horticulture and forestry.« less

  1. Profiling In Situ Microbial Community Structure with an Amplification Microarray

    PubMed Central

    Knickerbocker, Christopher; Bryant, Lexi; Golova, Julia; Wiles, Cory; Williams, Kenneth H.; Peacock, Aaron D.; Long, Philip E.

    2013-01-01

    The objectives of this study were to unify amplification, labeling, and microarray hybridization chemistries within a single, closed microfluidic chamber (an amplification microarray) and verify technology performance on a series of groundwater samples from an in situ field experiment designed to compare U(VI) mobility under conditions of various alkalinities (as HCO3−) during stimulated microbial activity accompanying acetate amendment. Analytical limits of detection were between 2 and 200 cell equivalents of purified DNA. Amplification microarray signatures were well correlated with 16S rRNA-targeted quantitative PCR results and hybridization microarray signatures. The succession of the microbial community was evident with and consistent between the two microarray platforms. Amplification microarray analysis of acetate-treated groundwater showed elevated levels of iron-reducing bacteria (Flexibacter, Geobacter, Rhodoferax, and Shewanella) relative to the average background profile, as expected. Identical molecular signatures were evident in the transect treated with acetate plus NaHCO3, but at much lower signal intensities and with a much more rapid decline (to nondetection). Azoarcus, Thaurea, and Methylobacterium were responsive in the acetate-only transect but not in the presence of bicarbonate. Observed differences in microbial community composition or response to bicarbonate amendment likely had an effect on measured rates of U reduction, with higher rates probable in the part of the field experiment that was amended with bicarbonate. The simplification in microarray-based work flow is a significant technological advance toward entirely closed-amplicon microarray-based tests and is generally extensible to any number of environmental monitoring applications. PMID:23160129

  2. Where statistics and molecular microarray experiments biology meet.

    PubMed

    Kelmansky, Diana M

    2013-01-01

    This review chapter presents a statistical point of view to microarray experiments with the purpose of understanding the apparent contradictions that often appear in relation to their results. We give a brief introduction of molecular biology for nonspecialists. We describe microarray experiments from their construction and the biological principles the experiments rely on, to data acquisition and analysis. The role of epidemiological approaches and sample size considerations are also discussed. PMID:23385529

  3. A highly oriented hybrid microarray modified electrode fabricated by a template-free method for ultrasensitive electrochemical DNA recognition

    NASA Astrophysics Data System (ADS)

    Shi, Lei; Chu, Zhenyu; Dong, Xueliang; Jin, Wanqin; Dempsey, Eithne

    2013-10-01

    Highly oriented growth of a hybrid microarray was realized by a facile template-free method on gold substrates for the first time. The proposed formation mechanism involves an interfacial structure-directing force arising from self-assembled monolayers (SAMs) between gold substrates and hybrid crystals. Different SAMs and variable surface coverage of the assembled molecules play a critical role in the interfacial directing forces and influence the morphologies of hybrid films. A highly oriented hybrid microarray was formed on the highly aligned and vertical SAMs of 1,4-benzenedithiol molecules with rigid backbones, which afforded an intense structure-directing power for the oriented growth of hybrid crystals. Additionally, the density of the microarray could be adjusted by controlling the surface coverage of assembled molecules. Based on the hybrid microarray modified electrode with a large specific area (ca. 10 times its geometrical area), a label-free electrochemical DNA biosensor was constructed for the detection of an oligonucleotide fragment of the avian flu virus H5N1. The DNA biosensor displayed a significantly low detection limit of 5 pM (S/N = 3), a wide linear response from 10 pM to 10 nM, as well as excellent selectivity, good regeneration and high stability. We expect that the proposed template-free method can provide a new reference for the fabrication of a highly oriented hybrid array and the as-prepared microarray modified electrode will be a promising paradigm in constructing highly sensitive and selective biosensors.Highly oriented growth of a hybrid microarray was realized by a facile template-free method on gold substrates for the first time. The proposed formation mechanism involves an interfacial structure-directing force arising from self-assembled monolayers (SAMs) between gold substrates and hybrid crystals. Different SAMs and variable surface coverage of the assembled molecules play a critical role in the interfacial directing forces and

  4. Development of a porcine (Sus scofa) embryo-specific microarray: array annotation and validation

    PubMed Central

    2012-01-01

    Background The domestic pig is an important livestock species and there is strong interest in the factors that affect the development of viable embryos and offspring in this species. A limited understanding of the molecular mechanisms involved in early embryonic development has inhibited our ability to fully elucidate these factors. Next generation deep sequencing and microarray technologies are powerful tools for delineation of molecular pathways involved in the developing embryo. Results Here we present the development of a porcine-embryo-specific microarray platform created from a large expressed sequence tag (EST) analysis generated by Roche/454 next-generation sequencing of cDNAs constructed from critical stages of in vivo or in vitro porcine preimplantation embryos. Two cDNA libraries constructed from in vitro and in vivo produced preimplantation porcine embryos were normalized and sequenced using 454 Titanium pyrosequencing technology. Over one million high-quality EST sequences were obtained and used to develop the EMbryogene Porcine Version 1 (EMPV1) microarray composed of 43,795 probes. Based on an initial probe sequence annotation, the EMPV1 features 17,409 protein-coding, 473 pseudogenes, 46 retrotransposed, 2,359 non-coding RNA, 4,121 splice variants in 2,862 genes and a total of 12,324 Novel Transcript Regions (NTR). After re-annotation, the total unique genes increased from 11,961 to 16,281 and 1.9% of them belonged to a large olfactory receptor (OR) gene family. Quality control on the EMPV1 was performed and revealed an even distribution of ten clusters of spiked-in control spots and array to array (dye-swap) correlation was 0.97. Conclusions Using next-generation deep sequencing we have produced a large EST dataset to allow for the selection of probe sequences for the development of the EMPV1 microarray platform. The quality of this embryo-specific array was confirmed with a high-level of reproducibility using current Agilent microarray technology

  5. Evaluating concentration estimation errors in ELISA microarray experiments

    SciTech Connect

    Daly, Don S.; White, Amanda M.; Varnum, Susan M.; Anderson, Kevin K.; Zangar, Richard C.

    2005-01-26

    Enzyme-linked immunosorbent assay (ELISA) is a standard immunoassay to predict a protein concentration in a sample. Deploying ELISA in a microarray format permits simultaneous prediction of the concentrations of numerous proteins in a small sample. These predictions, however, are uncertain due to processing error and biological variability. Evaluating prediction error is critical to interpreting biological significance and improving the ELISA microarray process. Evaluating prediction error must be automated to realize a reliable high-throughput ELISA microarray system. Methods: In this paper, we present a statistical method based on propagation of error to evaluate prediction errors in the ELISA microarray process. Although propagation of error is central to this method, it is effective only when comparable data are available. Therefore, we briefly discuss the roles of experimental design, data screening, normalization and statistical diagnostics when evaluating ELISA microarray prediction errors. We use an ELISA microarray investigation of breast cancer biomarkers to illustrate the evaluation of prediction errors. The illustration begins with a description of the design and resulting data, followed by a brief discussion of data screening and normalization. In our illustration, we fit a standard curve to the screened and normalized data, review the modeling diagnostics, and apply propagation of error.

  6. Assessing Bacterial Interactions Using Carbohydrate-Based Microarrays

    PubMed Central

    Flannery, Andrea; Gerlach, Jared Q.; Joshi, Lokesh; Kilcoyne, Michelle

    2015-01-01

    Carbohydrates play a crucial role in host-microorganism interactions and many host glycoconjugates are receptors or co-receptors for microbial binding. Host glycosylation varies with species and location in the body, and this contributes to species specificity and tropism of commensal and pathogenic bacteria. Additionally, bacterial glycosylation is often the first bacterial molecular species encountered and responded to by the host system. Accordingly, characterising and identifying the exact structures involved in these critical interactions is an important priority in deciphering microbial pathogenesis. Carbohydrate-based microarray platforms have been an underused tool for screening bacterial interactions with specific carbohydrate structures, but they are growing in popularity in recent years. In this review, we discuss carbohydrate-based microarrays that have been profiled with whole bacteria, recombinantly expressed adhesins or serum antibodies. Three main types of carbohydrate-based microarray platform are considered; (i) conventional carbohydrate or glycan microarrays; (ii) whole mucin microarrays; and (iii) microarrays constructed from bacterial polysaccharides or their components. Determining the nature of the interactions between bacteria and host can help clarify the molecular mechanisms of carbohydrate-mediated interactions in microbial pathogenesis, infectious disease and host immune response and may lead to new strategies to boost therapeutic treatments. PMID:27600247

  7. Basic Concepts of Microarrays and Potential Applications in Clinical Microbiology

    PubMed Central

    Miller, Melissa B.; Tang, Yi-Wei

    2009-01-01

    Summary: The introduction of in vitro nucleic acid amplification techniques, led by real-time PCR, into the clinical microbiology laboratory has transformed the laboratory detection of viruses and select bacterial pathogens. However, the progression of the molecular diagnostic revolution currently relies on the ability to efficiently and accurately offer multiplex detection and characterization for a variety of infectious disease pathogens. Microarray analysis has the capability to offer robust multiplex detection but has just started to enter the diagnostic microbiology laboratory. Multiple microarray platforms exist, including printed double-stranded DNA and oligonucleotide arrays, in situ-synthesized arrays, high-density bead arrays, electronic microarrays, and suspension bead arrays. One aim of this paper is to review microarray technology, highlighting technical differences between them and each platform's advantages and disadvantages. Although the use of microarrays to generate gene expression data has become routine, applications pertinent to clinical microbiology continue to rapidly expand. This review highlights uses of microarray technology that impact diagnostic microbiology, including the detection and identification of pathogens, determination of antimicrobial resistance, epidemiological strain typing, and analysis of microbial infections using host genomic expression and polymorphism profiles. PMID:19822891

  8. Design and analysis of mismatch probes for long oligonucleotide microarrays

    SciTech Connect

    Deng, Ye; He, Zhili; Van Nostrand, Joy D.; Zhou, Jizhong

    2008-08-15

    Nonspecific hybridization is currently a major concern with microarray technology. One of most effective approaches to estimating nonspecific hybridizations in oligonucleotide microarrays is the utilization of mismatch probes; however, this approach has not been used for longer oligonucleotide probes. Here, an oligonucleotide microarray was constructed to evaluate and optimize parameters for 50-mer mismatch probe design. A perfect match (PM) and 28 mismatch (MM) probes were designed for each of ten target genes selected from three microorganisms. The microarrays were hybridized with synthesized complementary oligonucleotide targets at different temperatures (e.g., 42, 45 and 50 C). In general, the probes with evenly distributed mismatches were more distinguishable than those with randomly distributed mismatches. MM probes with 3, 4 and 5 mismatched nucleotides were differentiated for 50-mer oligonucleotide probes hybridized at 50, 45 and 42 C, respectively. Based on the experimental data generated from this study, a modified positional dependent nearest neighbor (MPDNN) model was constructed to adjust the thermodynamic parameters of matched and mismatched dimer nucleotides in the microarray environment. The MM probes with four flexible positional mismatches were designed using the newly established MPDNN model and the experimental results demonstrated that the redesigned MM probes could yield more consistent hybridizations. Conclusions: This study provides guidance on the design of MM probes for long oligonucleotides (e.g., 50 mers). The novel MPDNN model has improved the consistency for long MM probes, and this modeling method can potentially be used for the prediction of oligonucleotide microarray hybridizations.

  9. Shrinkage regression-based methods for microarray missing value imputation

    PubMed Central

    2013-01-01

    Background Missing values commonly occur in the microarray data, which usually contain more than 5% missing values with up to 90% of genes affected. Inaccurate missing value estimation results in reducing the power of downstream microarray data analyses. Many types of methods have been developed to estimate missing values. Among them, the regression-based methods are very popular and have been shown to perform better than the other types of methods in many testing microarray datasets. Results To further improve the performances of the regression-based methods, we propose shrinkage regression-based methods. Our methods take the advantage of the correlation structure in the microarray data and select similar genes for the target gene by Pearson correlation coefficients. Besides, our methods incorporate the least squares principle, utilize a shrinkage estimation approach to adjust the coefficients of the regression model, and then use the new coefficients to estimate missing values. Simulation results show that the proposed methods provide more accurate missing value estimation in six testing microarray datasets than the existing regression-based methods do. Conclusions Imputation of missing values is a very important aspect of microarray data analyses because most of the downstream analyses require a complete dataset. Therefore, exploring accurate and efficient methods for estimating missing values has become an essential issue. Since our proposed shrinkage regression-based methods can provide accurate missing value estimation, they are competitive alternatives to the existing regression-based methods. PMID:24565159

  10. A comparative analysis of DNA barcode microarray feature size

    PubMed Central

    Ammar, Ron; Smith, Andrew M; Heisler, Lawrence E; Giaever, Guri; Nislow, Corey

    2009-01-01

    Background Microarrays are an invaluable tool in many modern genomic studies. It is generally perceived that decreasing the size of microarray features leads to arrays with higher resolution (due to greater feature density), but this increase in resolution can compromise sensitivity. Results We demonstrate that barcode microarrays with smaller features are equally capable of detecting variation in DNA barcode intensity when compared to larger feature sizes within a specific microarray platform. The barcodes used in this study are the well-characterized set derived from the Yeast KnockOut (YKO) collection used for screens of pooled yeast (Saccharomyces cerevisiae) deletion mutants. We treated these pools with the glycosylation inhibitor tunicamycin as a test compound. Three generations of barcode microarrays at 30, 8 and 5 μm features sizes independently identified the primary target of tunicamycin to be ALG7. Conclusion We show that the data obtained with 5 μm feature size is of comparable quality to the 30 μm size and propose that further shrinking of features could yield barcode microarrays with equal or greater resolving power and, more importantly, higher density. PMID:19825181

  11. Novel 3-Dimensional Dendrimer Platform for Glycolipid Microarray

    PubMed Central

    Zhang, Jian; Zhou, Xichun

    2011-01-01

    Glycolipids are important biological molecules that modulate cellular recognitions and pathogen adhesions. In this paper, we report a sensitive glycolipid microarray for non-covalently immobilizing glycolipids on a microarray substrate and we perform a set of immunoassays to explore glycolipid-protein interactions. This substrate utilizes a three-dimensional hydrazide-functionalized dendrimer monolayer attached onto a microscopic glass surface, which possesses the characteristics to adsorb glycoliplids non-covalently and facilitates multivalent attributes on the substrate surface. In the proof-of-concept experiments, gangliosides such as GM1, FucGM1, GM3, GD1b, GT1b, and GQ1b, and a lipoarabinomannan were tested on the substrate and interrogated with toxins and antibodies. The resulting glycolipid microarrays exhibited hypersensitivity and specificity for detection of glycolipid-protein interactions. In particular, a robust and specific binding of a pentameric cholera toxin B subunit to the GM1 glycolipid spotted on the array has demonstrated its superiority in sensitivity and specificity. In addition, this glycolipid microarray substrate was used to detect lipoarabinomannan in buffer within a limit-of-detection of 125 ng/mL. Furthermore, Mycobacterium tuberculosis (Mtb) Lipoarabinomannan was tested in human urine specimens on this platform, which can effectively identify urine samples either infected or not infected with Mtb. The results of this work suggest the possibility of using this glycolipid microarray platform to fabricate glycoconjugate microarrays, which includes free glycans and glycolipids and potential application in detection of pathogen and toxin. PMID:21820887

  12. Surface Enzyme Chemistries for Ultrasensitive Microarray Biosensing with SPR Imaging.

    PubMed

    Fasoli, Jennifer B; Corn, Robert M

    2015-09-01

    The sensitivity and selectivity of surface plasmon resonance imaging (SPRI) biosensing with nucleic acid microarrays can be greatly enhanced by exploiting various nucleic acid ligases, nucleases, and polymerases that manipulate the surface-bound DNA and RNA. We describe here various examples from each of these different classes of surface enzyme chemistries that have been incorporated into novel detection strategies that either drastically enhance the sensitivity of or create uniquely selective methods for the SPRI biosensing of proteins and nucleic acids. A dual-element generator-detector microarray approach that couples a bioaffinity adsorption event on one microarray element to nanoparticle-enhanced SPRI measurements of nucleic acid hybridization adsorption on a different microarray element is used to quantitatively detect DNA, RNA, and proteins at femtomolar concentrations. Additionally, this dual-element format can be combined with the transcription and translation of RNA from surface-bound double-stranded DNA (dsDNA) templates for the on-chip multiplexed biosynthesis of aptamer and protein microarrays in a microfluidic format; these microarrays can be immediately used for real-time SPRI bioaffinity sensing measurements. PMID:25641598

  13. DNA Microarray Characterization of Pathogens Associated with Sexually Transmitted Diseases

    PubMed Central

    Cao, Boyang; Wang, Suwei; Tian, Zhenyang; Hu, Pinliang; Feng, Lu; Wang, Lei

    2015-01-01

    This study established a multiplex PCR-based microarray to detect simultaneously a diverse panel of 17 sexually transmitted diseases (STDs)-associated pathogens including Neisseria gonorrhoeae, Chlamydia trachomatis, Mycoplasma genitalium, Mycoplasma hominis, Ureaplasma, Herpes simplex virus (HSV) types 1 and 2, and Human papillomavirus (HPV) types 6, 11, 16, 18, 31, 33, 35, 39, 54 and 58. The target genes are 16S rRNA gene for N. gonorrhoeae, M. genitalium, M. hominism, and Ureaplasma, the major outer membrane protein gene (ompA) for C. trachomatis, the glycoprotein B gene (gB) for HSV; and the L1 gene for HPV. A total of 34 probes were selected for the microarray including 31 specific probes, one as positive control, one as negative control, and one as positional control probe for printing reference. The microarray is specific as the commensal and pathogenic microbes (and closely related organisms) in the genitourinary tract did not cross-react with the microarray probes. The microarray is 10 times more sensitive than that of the multiplex PCR. Among the 158 suspected HPV specimens examined, the microarray showed that 49 samples contained HPV, 21 samples contained Ureaplasma, 15 contained M. hominis, four contained C. trachomatis, and one contained N. gonorrhoeae. This work reports the development of the first high through-put detection system that identifies common pathogens associated with STDs from clinical samples, and paves the way for establishing a time-saving, accurate and high-throughput diagnostic tool for STDs. PMID:26208181

  14. Surface Enzyme Chemistries for Ultrasensitive Microarray Biosensing with SPR Imaging

    PubMed Central

    2015-01-01

    The sensitivity and selectivity of surface plasmon resonance imaging (SPRI) biosensing with nucleic acid microarrays can be greatly enhanced by exploiting various nucleic acid ligases, nucleases, and polymerases that manipulate the surface-bound DNA and RNA. We describe here various examples from each of these different classes of surface enzyme chemistries that have been incorporated into novel detection strategies that either drastically enhance the sensitivity of or create uniquely selective methods for the SPRI biosensing of proteins and nucleic acids. A dual-element generator–detector microarray approach that couples a bioaffinity adsorption event on one microarray element to nanoparticle-enhanced SPRI measurements of nucleic acid hybridization adsorption on a different microarray element is used to quantitatively detect DNA, RNA, and proteins at femtomolar concentrations. Additionally, this dual-element format can be combined with the transcription and translation of RNA from surface-bound double-stranded DNA (dsDNA) templates for the on-chip multiplexed biosynthesis of aptamer and protein microarrays in a microfluidic format; these microarrays can be immediately used for real-time SPRI bioaffinity sensing measurements. PMID:25641598

  15. Microintaglio Printing of In situ Synthesized Proteins Enables Rapid Printing of High-Density Protein Microarrays Directly from DNA Microarrays

    NASA Astrophysics Data System (ADS)

    Biyani, Manish; Moriyasu, Junpei; Tanaka, Yoko; Sato, Shusuke; Ueno, Shingo; Ichiki, Takanori

    2013-08-01

    A simple and versatile approach to the simultaneous on-chip synthesis and printing of proteins has been studied for high-density protein microarray applications. The method used is based on the principle of intaglio printing using microengraved plates. Unlike conventional approaches that require multistep reactions for synthesizing proteins off the chip followed by printing using a robotic spotter, our approach demonstrates the following: (i) parallel and spotter-free printing of high-density protein microarrays directly from a type of DNA microarray and (ii) microcompartmentalization of cell-free coupled transcription/translation reaction and direct transferring of picoliter protein solution per spot to pattern microarrays of 25-100 µm features.

  16. MICB Allele Genotyping on Microarrays by Improving the Specificity of Extension Primers

    PubMed Central

    Baek, In-Cheol; Jang, Jung-Pil; Choi, Eun-Jeong; Kim, Tai-Gyu

    2015-01-01

    Major histocompatibility complex (MHC) class I chain-related gene B (MICB) encodes a ligand for activating NKG2D that expressed in natural killer cells, γδ T cells, and αβ CD8+ T cells, which is associated with autoimmune diseases, cancer, and infectious diseases. Here, we have established a system for genotyping MICB alleles using allele-specific primer extension (ASPE) on microarrays. Thirty-six high quality, allele-specific extension primers were evaluated using strict and reliable cut-off values using mean fluorescence intensity (MFI), whereby an MFI >30,000 represented a positive signal and an MFI <10,000 represented a negative signal. Eight allele-specific extension primers were found to be false positives, five of which were improved by adjusting their length, and three of which were optimized by refractory modification. The MICB alleles (*002:01, *003, *005:02/*010, *005:03, *008, *009N, *018, and *024) present in the quality control panel could be exactly defined by 22 allele-specific extension primers. MICB genotypes that were identified by ASPE on microarrays were in full concordance with those identified by PCR-sequence-based typing. In conclusion, we have developed a method for genotyping MICB alleles using ASPE on microarrays; which can be applicable for large-scale single nucleotide polymorphism typing studies of population and disease associations. PMID:26569110

  17. Sequencing by Cyclic Ligation and Cleavage (CycLiC) directly on a microarray captured template

    PubMed Central

    Mir, Kalim U.; Qi, Hong; Salata, Oleg; Scozzafava, Giuseppe

    2009-01-01

    Next generation sequencing methods that can be applied to both the resequencing of whole genomes and to the selective resequencing of specific parts of genomes are needed. We describe (i) a massively scalable biochemistry, Cyclical Ligation and Cleavage (CycLiC) for contiguous base sequencing and (ii) apply it directly to a template captured on a microarray. CycLiC uses four color-coded DNA/RNA chimeric oligonucleotide libraries (OL) to extend a primer, a base at a time, along a template. The cycles comprise the steps: (i) ligation of OLs, (ii) identification of extended base by label detection, and (iii) cleavage to remove label/terminator and undetermined bases. For proof-of-principle, we show that the method conforms to design and that we can read contiguous bases of sequence correctly from a template captured by hybridization from solution to a microarray probe. The method is amenable to massive scale-up, miniaturization and automation. Implementation on a microarray format offers the potential for both selection and sequencing of a large number of genomic regions on a single platform. Because the method uses commonly available reagents it can be developed further by a community of users. PMID:19015154

  18. Optimal design of genetic studies of gene expression with two-color microarrays in outbred crosses.

    PubMed

    Lam, Alex C; Fu, Jingyuan; Jansen, Ritsert C; Haley, Chris S; de Koning, Dirk-Jan

    2008-11-01

    Combining global gene-expression profiling and genetic analysis of natural allelic variation (genetical genomics) has great potential in dissecting the genetic pathways underlying complex phenotypes. Efficient use of microarrays is paramount in experimental design as the cost of conducting this type of study is high. For those organisms where recombinant inbred lines are available for mapping, the "distant pair design" maximizes the number of informative contrasts over all marker loci. Here, we describe an extension of this design, named the "optimal pair design," for use with F2 crosses between outbred lines. The performance of this design is investigated by simulation and compared to several other two-color microarray designs. We show that, for a given number of microarrays, the optimal pair design outperforms all other designs considered for detection of expression quantitative trait loci (eQTL) with additive effects by linkage analysis. We also discuss the suitability of this design for outbred crosses in organisms with large genomes and for detection of dominance. PMID:18791249

  19. Construction of a robust microarray from a non-model species (largemouth bass) using pyrosequencing technology

    PubMed Central

    Garcia-Reyero, Natàlia; Griffitt, Robert J.; Liu, Li; Kroll, Kevin J.; Farmerie, William G.; Barber, David S.; Denslow, Nancy D.

    2009-01-01

    A novel custom microarray for largemouth bass (Micropterus salmoides) was designed with sequences obtained from a normalized cDNA library using the 454 Life Sciences GS-20 pyrosequencer. This approach yielded in excess of 58 million bases of high-quality sequence. The sequence information was combined with 2,616 reads obtained by traditional suppressive subtractive hybridizations to derive a total of 31,391 unique sequences. Annotation and coding sequences were predicted for these transcripts where possible. 16,350 annotated transcripts were selected as target sequences for the design of the custom largemouth bass oligonucleotide microarray. The microarray was validated by examining the transcriptomic response in male largemouth bass exposed to 17β-œstradiol. Transcriptomic responses were assessed in liver and gonad, and indicated gene expression profiles typical of exposure to œstradiol. The results demonstrate the potential to rapidly create the tools necessary to assess large scale transcriptional responses in non-model species, paving the way for expanded impact of toxicogenomics in ecotoxicology. PMID:19936325

  20. Nucleosome positioning from tiling microarray data

    PubMed Central

    Yassour, Moran; Kaplan, Tommy; Jaimovich, Ariel; Friedman, Nir

    2008-01-01

    Motivation: The packaging of DNA around nucleosomes in eukaryotic cells plays a crucial role in regulation of gene expression, and other DNA-related processes. To better understand the regulatory role of nucleosomes, it is important to pinpoint their position in a high (5–10 bp) resolution. Toward this end, several recent works used dense tiling arrays to map nucleosomes in a high-throughput manner. These data were then parsed and hand-curated, and the positions of nucleosomes were assessed. Results: In this manuscript, we present a fully automated algorithm to analyze such data and predict the exact location of nucleosomes. We introduce a method, based on a probabilistic graphical model, to increase the resolution of our predictions even beyond that of the microarray used. We show how to build such a model and how to compile it into a simple Hidden Markov Model, allowing for a fast and accurate inference of nucleosome positions. We applied our model to nucleosomal data from mid-log yeast cells reported by Yuan et al. and compared our predictions to those of the original paper; to a more recent method that uses five times denser tiling arrays as explained by Lee et al.; and to a curated set of literature-based nucleosome positions. Our results suggest that by applying our algorithm to the same data used by Yuan et al. our fully automated model traced 13% more nucleosomes, and increased the overall accuracy by about 20%. We believe that such an improvement opens the way for a better understanding of the regulatory mechanisms controlling gene expression, and how they are encoded in the DNA. Contact: nir@cs.huji.ac.il PMID:18586706

  1. Analysis of porcine MHC using microarrays.

    PubMed

    Gao, Yu; Wahlberg, Per; Marthey, Sylvain; Esquerré, Diane; Jaffrézic, Florence; Lecardonnel, Jérome; Hugot, Karine; Rogel-Gaillard, Claire

    2012-07-15

    The major histocompatibility complex (MHC) in Mammals is one of the most gene dense regions of the genome and contains the polymorphic histocompatibility gene families known to be involved in pathogen response and control of auto-immunity. The MHC is a complex genetic system that provides an interesting model system to study genome expression regulation and genetic diversity at the megabase scale. The pig MHC or SLA (Swine Leucocyte Antigen) complex spans 2.4 megabases and 151 loci have been annotated. We will review key results from previous RNA expression studies using microarrays containing probes specific to annotated loci within SLA and in addition present novel data obtained using high-density tiling arrays encompassing the whole SLA complex. We have focused on transcriptome modifications of porcine peripheral blood mononuclear cells stimulated with a mixture of phorbol myristate acetate and ionomycin known to activate B and T cell proliferation. Our results show that numerous loci mapping to the SLA complex are affected by the treatment. A general decreased level of expression for class I and II genes and an up-regulation of genes involved in peptide processing and transport were observed. Tiling array-based experiments contributed to refined gene annotations as presented for one SLA class I gene referred to as SLA-11. In conclusion, high-density tiling arrays can serve as an excellent tool to draw comprehensive transcription maps, and improve genome annotations for the SLA complex. We are currently studying their relevance to characterize SLA genetic diversity in combination with high throughput next generation sequencing. PMID:21561666

  2. Assessing outcomes of large-scale public health interventions in the absence of baseline data using a mixture of Cox and binomial regressions

    PubMed Central

    2014-01-01

    Background Large-scale public health interventions with rapid scale-up are increasingly being implemented worldwide. Such implementation allows for a large target population to be reached in a short period of time. But when the time comes to investigate the effectiveness of these interventions, the rapid scale-up creates several methodological challenges, such as the lack of baseline data and the absence of control groups. One example of such an intervention is Avahan, the India HIV/AIDS initiative of the Bill & Melinda Gates Foundation. One question of interest is the effect of Avahan on condom use by female sex workers with their clients. By retrospectively reconstructing condom use and sex work history from survey data, it is possible to estimate how condom use rates evolve over time. However formal inference about how this rate changes at a given point in calendar time remains challenging. Methods We propose a new statistical procedure based on a mixture of binomial regression and Cox regression. We compare this new method to an existing approach based on generalized estimating equations through simulations and application to Indian data. Results Both methods are unbiased, but the proposed method is more powerful than the existing method, especially when initial condom use is high. When applied to the Indian data, the new method mostly agrees with the existing method, but seems to have corrected some implausible results of the latter in a few districts. We also show how the new method can be used to analyze the data of all districts combined. Conclusions The use of both methods can be recommended for exploratory data analysis. However for formal statistical inference, the new method has better power. PMID:24397563

  3. A Simple Method for Optimization of Reference Gene Identification and Normalization in DNA Microarray Analysis

    PubMed Central

    Casares, Federico M.

    2016-01-01

    Background Comparative DNA microarray analyses typically yield very large gene expression data sets that reflect complex patterns of change. Despite the wealth of information that is obtained, the identification of stable reference genes is required for normalization of disease- or drug-induced changes across tested groups. This is a prerequisite in quantitative real-time reverse transcription-PCR (qRT-PCR) and relative RT-PCR but rare in gene microarray analysis. The goal of the present study was to outline a simple method for identification of reliable reference genes derived from DNA microarray data sets by comparative statistical analysis of software-generated and manually calculated candidate genes. Material/Methods DNA microarray data sets derived from whole-blood samples obtained from 14 Zucker diabetic fatty (ZDF) rats (7 lean and 7 diabetic obese) were used for the method development. This involved the use of software-generated filtering parameters to accomplish the desired signal-to-noise ratios, 75th percentile signal manual normalizations, and the selection of reference genes as endogenous controls for target gene expression normalization. Results The combination of software-generated and manual normalization methods yielded a group of 5 stably expressed, suitable endogenous control genes which can be used in further target gene expression determinations in whole blood of ZDF rats. Conclusions This method can be used to correct for potentially false results and aid in the selection of suitable endogenous control genes. It is especially useful when aimed to aid the software in cases of borderline results, where the expression and/or the fold change values are just beyond the pre-established set of acceptable parameters. PMID:27122237

  4. Influence of microarrays experiments missing values on the stability of gene groups by hierarchical clustering

    PubMed Central

    de Brevern, Alexandre G; Hazout, Serge; Malpertuy, Alain

    2004-01-01

    Background Microarray technologies produced large amount of data. The hierarchical clustering is commonly used to identify clusters of co-expressed genes. However, microarray datasets often contain missing values (MVs) representing a major drawback for the use of the clustering methods. Usually the MVs are not treated, or replaced by zero or estimated by the k-Nearest Neighbor (kNN) approach. The topic of the paper is to study the stability of gene clusters, defined by various hierarchical clustering algorithms, of microarrays experiments including or not MVs. Results In this study, we show that the MVs have important effects on the stability of the gene clusters. Moreover, the magnitude of the gene misallocations is depending on the aggregation algorithm. The most appropriate aggregation methods (e.g. complete-linkage and Ward) are highly sensitive to MVs, and surprisingly, for a very tiny proportion of MVs (e.g. 1%). In most of the case, the MVs must be replaced by expected values. The MVs replacement by the kNN approach clearly improves the identification of co-expressed gene clusters. Nevertheless, we observe that kNN approach is less suitable for the extreme values of gene expression. Conclusion The presence of MVs (even at a low rate) is a major factor of gene cluster instability. In addition, the impact depends on the hierarchical clustering algorithm used. Some methods should be used carefully. Nevertheless, the kNN approach constitutes one efficient method for restoring the missing expression gene values, with a low error level. Our study highlights the need of statistical treatments in microarray data to avoid misinterpretation. PMID:15324460

  5. A novel biclustering algorithm of binary microarray data: BiBinCons and BiBinAlter.

    PubMed

    Saber, Haifa Ben; Elloumi, Mourad

    2015-01-01

    The biclustering of microarray data has been the subject of a large research. No one of the existing biclustering algorithms is perfect. The construction of biologically significant groups of biclusters for large microarray data is still a problem that requires a continuous work. Biological validation of biclusters of microarray data is one of the most important open issues. So far, there are no general guidelines in the literature on how to validate biologically extracted biclusters. In this paper, we develop two biclustering algorithms of binary microarray data, adopting the Iterative Row and Column Clustering Combination (IRCCC) approach, called BiBinCons and BiBinAlter. However, the BiBinAlter algorithm is an improvement of BiBinCons. On the other hand, BiBinAlter differs from BiBinCons by the use of the EvalStab and IndHomog evaluation functions in addition to the CroBin one (Bioinformatics 20:1993-2003, 2004). BiBinAlter can extracts biclusters of good quality with better p-values. PMID:26628919

  6. Microarray-based long oligonucleotides probe designed for Brucella Spp. detection and identification of antibiotic susceptibility pattern

    PubMed Central

    Khazaei, Zahra; Najafi, Ali; Piranfar, Vahhab; Mirnejad, Reza

    2016-01-01

    Brucella spp. is a common zoonotic infection referred to as Brucellosis, and it is a serious public health problem around the world. There are currently six classical species (pathogenic species in both animals and humans) within the genus Brucella. The ability and practicality facilitated by a microarray experiment help us to recognize Brucella spp. and its antibiotic resistant gene. Rapid phenotypic determination of antibiotic resistance is not possible by disk diffusion methods. Thus, evaluating antibiotics pattern and Brucella detection appear necessary technique by molecular methods in brucellosis. So, the aim of this study was to design a microarray long oligonucleotides probe and primer for the complete diagnosis of Brucella spp. and obtaining genetic profiles for antibiotic resistance in bacteria at the same time. In this study, we designed 16 antibiotic-resistant gene solid-phase primers with similar melting temperatures of 60 °C and 16 long oligonucleotide probes. These primers and probes can identify tetracycline-, chloramphenicol-, and aminoglycoside-resistant genes, respectively. The design of microarray probes is a versatile process that be done in a wide range of selections. Since the long oligo microarray probes are the best choices for specific diagnosis and definite treatment, this group of probes was designed in the present survey. PMID:27280008

  7. Microarray-based long oligonucleotides probe designed for Brucella Spp. detection and identification of antibiotic susceptibility pattern.

    PubMed

    Khazaei, Zahra; Najafi, Ali; Piranfar, Vahhab; Mirnejad, Reza

    2016-04-01

    Brucella spp. is a common zoonotic infection referred to as Brucellosis, and it is a serious public health problem around the world. There are currently six classical species (pathogenic species in both animals and humans) within the genus Brucella. The ability and practicality facilitated by a microarray experiment help us to recognize Brucella spp. and its antibiotic resistant gene. Rapid phenotypic determination of antibiotic resistance is not possible by disk diffusion methods. Thus, evaluating antibiotics pattern and Brucella detection appear necessary technique by molecular methods in brucellosis. So, the aim of this study was to design a microarray long oligonucleotides probe and primer for the complete diagnosis of Brucella spp. and obtaining genetic profiles for antibiotic resistance in bacteria at the same time. In this study, we designed 16 antibiotic-resistant gene solid-phase primers with similar melting temperatures of 60 °C and 16 long oligonucleotide probes. These primers and probes can identify tetracycline-, chloramphenicol-, and aminoglycoside-resistant genes, respectively. The design of microarray probes is a versatile process that be done in a wide range of selections. Since the long oligo microarray probes are the best choices for specific diagnosis and definite treatment, this group of probes was designed in the present survey. PMID:27280008

  8. Construction and validation of a Bovine Innate Immune Microarray

    PubMed Central

    Donaldson, Laurelea; Vuocolo, Tony; Gray, Christian; Strandberg, Ylva; Reverter, Antonio; McWilliam, Sean; Wang, YongHong; Byrne, Keren; Tellam, Ross

    2005-01-01

    Background Microarray transcript profiling has the potential to illuminate the molecular processes that are involved in the responses of cattle to disease challenges. This knowledge may allow the development of strategies that exploit these genes to enhance resistance to disease in an individual or animal population. Results The Bovine Innate Immune Microarray developed in this study consists of 1480 characterised genes identified by literature searches, 31 positive and negative control elements and 5376 cDNAs derived from subtracted and normalised libraries. The cDNA libraries were produced from 'challenged' bovine epithelial and leukocyte cells. The microarray was found to have a limit of detection of 1 pg/μg of total RNA and a mean slide-to-slide correlation co-efficient of 0.88. The profiles of differentially expressed genes from Concanavalin A (ConA) stimulated bovine peripheral blood lymphocytes were determined. Three distinct profiles highlighted 19 genes that were rapidly up-regulated within 30 minutes and returned to basal levels by 24 h; 76 genes that were up-regulated between 2–8 hours and sustained high levels of expression until 24 h and 10 genes that were down-regulated. Quantitative real-time RT-PCR on selected genes was used to confirm the results from the microarray analysis. The results indicate that there is a dynamic process involving gene activation and regulatory mechanisms re-establishing homeostasis in the ConA activated lymphocytes. The Bovine Innate Immune Microarray was also used to determine the cross-species hybridisation capabilities of an ovine PBL sample. Conclusion The Bovine Innate Immune Microarray has been developed which contains a set of well-characterised genes and anonymous cDNAs from a number of different bovine cell types. The microarray can be used to determine the gene expression profiles underlying innate immune responses in cattle and sheep. PMID:16176586

  9. Protein microarray: sensitive and effective immunodetection for drug residues

    PubMed Central

    2010-01-01

    Background Veterinary drugs such as clenbuterol (CL) and sulfamethazine (SM2) are low molecular weight (<1000 Da) compounds, or haptens, that are difficult to develop immunoassays due to their low immunogenicity. In this study, we conjugated the drugs to ovalbumin to increase their immunogenicity for antiserum production in rabbits and developed a protein microarray immunoassay for detection of clenbuterol and sulfamethazine. The sensitivity of this approach was then compared to traditional ELISA technique. Results The artificial antigens were spotted on microarray slides. Standard concentrations of the compounds were added to compete with the spotted antigens for binding to the antisera to determine the IC50. Our microarray assay showed the IC50 were 39.6 ng/ml for CL and 48.8 ng/ml for SM2, while the traditional competitive indirect-ELISA (ci-ELISA) showed the IC50 were 190.7 ng/ml for CL and 156.7 ng/ml for SM2. We further validated the two methods with CL fortified chicken muscle tissues, and the protein microarray assay showed 90% recovery while the ci-ELISA had 76% recovery rate. When tested with CL-fed chicken muscle tissues, the protein microarray assay had higher sensitivity (0.9 ng/g) than the ci-ELISA (0.1 ng/g) for detection of CL residues. Conclusions The protein microarrays showed 4.5 and 3.5 times lower IC50 than the ci-ELISA detection for CL and SM2, respectively, suggesting that immunodetection of small molecules with protein microarray is a better approach than the traditional ELISA technique. PMID:20158905

  10. Which Members of the Microbial Communities Are Active? Microarrays

    NASA Astrophysics Data System (ADS)

    Morris, Brandon E. L.

    Here, we introduce the concept of microarrays, discuss the advantages of several different types of arrays and present a case study that illustrates a targeted-profiling approach to bioremediation of a hydrocarbon-contaminated site in an Arctic environment. The majority of microorganisms in the terrestrial subsurface, particularly those involved in 'heavy oil' formation, reservoir souring or biofouling remain largely uncharacterised (Handelsman, 2004). There is evidence though that these processes are biologically catalysed, including stable isotopic composition of hydrocarbons in oil formations (Pallasser, 2000; Sun et al., 2005), the absence of biodegraded oil from reservoirs warmer than 80°C (Head et al., 2003) or negligible biofouling in the absence of biofilms (Dobretsov et al., 2009; Lewandowski and Beyenal, 2008), and all clearly suggest an important role for microorganisms in the deep biosphere in general and oilfield systems in particular. While the presence of sulphate-reducing bacteria in oilfields was first observed in the early twentieth century (Bastin, 1926), it was only through careful experiments with isolates from oil systems or contaminated environments that unequivocal evidence for hydrocarbon biodegradation under anaerobic conditions was provided (for a review, see Widdel et al., 2006). Work with pure cultures and microbial enrichments also led to the elucidation of the biochemistry of anaerobic aliphatic and aromatic hydrocarbon degradation and the identification of central metabolites and genes involved in the process, e.g. (Callaghan et al., 2008; Griebler et al., 2003; Kropp et al., 2000). This information could then be extrapolated to the environment to monitor degradation processes and determine if in situ microbial populations possessed the potential for contaminant bioremediation, e.g. Parisi et al. (2009). While other methods have also been developed to monitor natural attenuation of hydrocarbons (Meckenstock et al., 2004), we are

  11. Challenges in microarray class discovery: a comprehensive examination of normalization, gene selection and clustering

    PubMed Central

    2010-01-01

    Background Cluster analysis, and in particular hierarchical clustering, is widely used to extract information from gene expression data. The aim is to discover new classes, or sub-classes, of either individuals or genes. Performing a cluster analysis commonly involve decisions on how to; handle missing values, standardize the data and select genes. In addition, pre-processing, involving various types of filtration and normalization procedures, can have an effect on the ability to discover biologically relevant classes. Here we consider cluster analysis in a broad sense and perform a comprehensive evaluation that covers several aspects of cluster analyses, including normalization. Result We evaluated 2780 cluster analysis methods on seven publicly available 2-channel microarray data sets with common reference designs. Each cluster analysis method differed in data normalization (5 normalizations were considered), missing value imputation (2), standardization of data (2), gene selection (19) or clustering method (11). The cluster analyses are evaluated using known classes, such as cancer types, and the adjusted Rand index. The performances of the different analyses vary between the data sets and it is difficult to give general recommendations. However, normalization, gene selection and clustering method are all variables that have a significant impact on the performance. In particular, gene selection is important and it is generally necessary to include a relatively large number of genes in order to get good performance. Selecting genes with high standard deviation or using principal component analysis are shown to be the preferred gene selection methods. Hierarchical clustering using Ward's method, k-means clustering and Mclust are the clustering methods considered in this paper that achieves the highest adjusted Rand. Normalization can have a significant positive impact on the ability to cluster individuals, and there are indications that background correction is

  12. Detection of influent virulence and resistance genes in microarray data through quasi likelihood modeling.

    PubMed

    Romeo, José S; Torres-Avilés, Francisco; López-Kleine, Liliana

    2013-02-01

    Publicly available genomic data are a great source of biological knowledge that can be extracted when appropriate data analysis is used. Predicting the biological function of genes is of interest to understand molecular mechanisms of virulence and resistance in pathogens and hosts and is important for drug discovery and disease control. This is commonly done by searching for similar gene expression behavior. Here, we used publicly available Streptococcus pyogenes microarray data obtained during primate infection to identify genes that have a potential influence on virulence and Phytophtora infestance inoculated tomato microarray data to identify genes potentially implicated in resistance processes. This approach goes beyond co-expression analysis. We employed a quasi-likelihood model separated by primate gender/inoculation condition to model median gene expression of known virulence/resistance factors. Based on this model, an influence analysis considering time course measurement was performed to detect genes with atypical expression. This procedure allowed for the detection of genes potentially implicated in the infection process. Finally, we discuss the biological meaning of these results, showing that influence analysis is an efficient and useful alternative for functional gene prediction. PMID:23296985

  13. Evaluating concentration estimation errors in ELISA microarray experiments

    PubMed Central

    Daly, Don Simone; White, Amanda M; Varnum, Susan M; Anderson, Kevin K; Zangar, Richard C

    2005-01-01

    Background Enzyme-linked immunosorbent assay (ELISA) is a standard immunoassay to estimate a protein's concentration in a sample. Deploying ELISA in a microarray format permits simultaneous estimation of the concentrations of numerous proteins in a small sample. These estimates, however, are uncertain due to processing error and biological variability. Evaluating estimation error is critical to interpreting biological significance and improving the ELISA microarray process. Estimation error evaluation must be automated to realize a reliable high-throughput ELISA microarray system. In this paper, we present a statistical method based on propagation of error to evaluate concentration estimation errors in the ELISA microarray process. Although propagation of error is central to this method and the focus of this paper, it is most effective only when comparable data are available. Therefore, we briefly discuss the roles of experimental design, data screening, normalization, and statistical diagnostics when evaluating ELISA microarray concentration estimation errors. Results We use an ELISA microarray investigation of breast cancer biomarkers to illustrate the evaluation of concentration estimation errors. The illustration begins with a description of the design and resulting data, followed by a brief discussion of data screening and normalization. In our illustration, we fit a standard curve to the screened and normalized data, review the modeling diagnostics, and apply propagation of error. We summarize the results with a simple, three-panel diagnostic visualization featuring a scatterplot of the standard data with logistic standard curve and 95% confidence intervals, an annotated histogram of sample measurements, and a plot of the 95% concentration coefficient of variation, or relative error, as a function of concentration. Conclusions This statistical method should be of value in the rapid evaluation and quality control of high-throughput ELISA microarray analyses

  14. Multi-objective dynamic population shuffled frog-leaping biclustering of microarray data

    PubMed Central

    2012-01-01

    Background Multi-objective optimization (MOO) involves optimization problems with multiple objectives. Generally, theose objectives is used to estimate very different aspects of the solutions, and these aspects are often in conflict with each other. MOO first gets a Pareto set, and then looks for both commonality and systematic variations across the set. For the large-scale data sets, heuristic search algorithms such as EA combined with MOO techniques are ideal. Newly DNA microarray technology may study the transcriptional response of a complete genome to different experimental conditions and yield a lot of large-scale datasets. Biclustering technique can simultaneously cluster rows and columns of a dataset, and hlep to extract more accurate information from those datasets. Biclustering need optimize several conflicting objectives, and can be solved with MOO methods. As a heuristics-based optimization approach, the particle swarm optimization (PSO) simulate the movements of a bird flock finding food. The shuffled frog-leaping algorithm (SFL) is a population-based cooperative search metaphor combining the benefits of the local search of PSO and the global shuffled of information of the complex evolution technique. SFL is used to solve the optimization problems of the large-scale datasets. Results This paper integrates dynamic population strategy and shuffled frog-leaping algorithm into biclustering of microarray data, and proposes a novel multi-objective dynamic population shuffled frog-leaping biclustering (MODPSFLB) algorithm to mine maximum bicluesters from microarray data. Experimental results show that the proposed MODPSFLB algorithm can effectively find significant biological structures in terms of related biological processes, components and molecular functions. Conclusions The proposed MODPSFLB algorithm has good diversity and fast convergence of Pareto solutions and will become a powerful systematic functional analysis in genome research. PMID:22759615

  15. Can Zipf's law be adapted to normalize microarrays?

    PubMed Central

    Lu, Tim; Costello, Christine M; Croucher, Peter JP; Häsler, Robert; Deuschl, Günther; Schreiber, Stefan

    2005-01-01

    Background Normalization is the process of removing non-biological sources of variation between array experiments. Recent investigations of data in gene expression databases for varying organisms and tissues have shown that the majority of expressed genes exhibit a power-law distribution with an exponent close to -1 (i.e. obey Zipf's law). Based on the observation that our single channel and two channel microarray data sets also followed a power-law distribution, we were motivated to develop a normalization method based on this law, and examine how it compares with existing published techniques. A computationally simple and intuitively appealing technique based on this observation is presented. Results Using pairwise comparisons using MA plots (log ratio vs. log intensity), we compared this novel method to previously published normalization techniques, namely global normalization to the mean, the quantile method, and a variation on the loess normalization method designed specifically for boutique microarrays. Results indicated that, for single channel microarrays, the quantile method was superior with regard to eliminating intensity-dependent effects (banana curves), but Zipf's law normalization does minimize this effect by rotating the data distribution such that the maximal number of data points lie on the zero of the log ratio axis. For two channel boutique microarrays, the Zipf's law normalizations performed as well as, or better than existing techniques. Conclusion Zipf's law normalization is a useful tool where the Quantile method cannot be applied, as is the case with microarrays containing functionally specific gene sets (boutique arrays). PMID:15727680

  16. Electronic microarray assays for avian influenza and Newcastle disease virus.

    PubMed

    Lung, Oliver; Beeston, Anne; Ohene-Adjei, Samuel; Pasick, John; Hodko, Dalibor; Hughes, Kimberley Burton; Furukawa-Stoffer, Tara; Fisher, Mathew; Deregt, Dirk

    2012-11-01

    Microarrays are suitable for multiplexed detection and typing of pathogens. Avian influenza virus (AIV) is currently classified into 16 H (hemagglutinin) and 9 N (neuraminidase) subtypes, whereas Newcastle disease virus (NDV) strains differ in virulence and are broadly classified into high and low pathogenicity types. In this study, three assays for detection and typing of poultry viruses were developed on an automated microarray platform: a multiplex assay for simultaneous detection of AIV and detection and pathotyping of NDV, and two separate assays for differentiating all AIV H and N subtypes. The AIV-NDV multiplex assay detected all strains in a 63 virus panel, and accurately typed all high pathogenicity NDV strains tested. A limit of detection of 10(1)-10(3) TCID(50)/mL and 200-400 EID(50)/mL was obtained for NDV and AIV, respectively. The AIV typing assays accurately typed all 41 AIV strains and a limit of detection of 4-200 EID(50)/mL was obtained. Assay validation showed that the microarray assays were generally comparable to real-time RT-PCR. However, the AIV typing microarray assays detected more positive clinical samples than the AIV matrix real-time RT-PCR, and also provided information regarding the subtype. The AIV-NDV multiplex and AIV H typing microarray assays detected mixed infections and could be useful for detection and typing of AIV and NDV. PMID:22796283

  17. A protein multiplex microarray substrate with high sensitivity and specificity

    PubMed Central

    Fici, Dolores A.; McCormick, William; Brown, David W.; Herrmann, John E.; Kumar, Vikram; Awdeh, Zuheir L.

    2010-01-01

    The problems that have been associated with protein multiplex microarray immunoassay substrates and existing technology platforms include: binding, sensitivity, a low signal to noise ratio, target immobilization and the optimal simultaneous detection of diverse protein targets. Current commercial substrates for planar multiplex microarrays rely on protein attachment chemistries that range from covalent attachment to affinity ligand capture, to simple adsorption. In this pilot study, experimental performance parameters for direct monoclonal mouse IgG detection were compared for available two and three dimensional slide surface coatings with a new colloidal nitrocellulose substrate. New technology multiplex microarrays were also developed and evaluated for the detection of pathogen specific antibodies in human serum and the direct detection of enteric viral antigens. Data supports the nitrocellulose colloid as an effective reagent with the capacity to immobilize sufficient diverse protein target quantities for increased specificory signal without compromising authentic protein structure. The nitrocellulose colloid reagent is compatible with the array spotters and scanners routinely used for microarray preparation and processing. More importantly, as an alternate to fluorescence, colorimetric chemistries may be used for specific and sensitive protein target detection. The advantages of the nitrocellulose colloid platform indicate that this technology may be a valuable tool for the further development and expansion of multiplex microarray immunoassays in both the clinical and research laborat environment. PMID:20974147

  18. Production of biomolecule microarrays through laser induced forward transfer

    NASA Astrophysics Data System (ADS)

    Fernandez-Pradas, Juan Marcos; Serra, Pere; Colina, Monica; Morenza, Jose-Luis

    2004-10-01

    Biomolecule microarrays are a kind of biosensors that consist in patterns of different biological molecules immobilized on a solid substrate and capable to bind specifically to their complementary targets. In particular, DNA and protein microarrays have been revealed to be very efficient devices for genen and protein identification, what has converted them in powerful tools for many applications, like clinical diagnose, drug discovery analysis, genomics and proteomics. The production of these devices requires the manipulation of tiny amounts of a liquid solution containing biomolecules without damaging them. In this work laser induced forward transfer (LIFT) has been used for spotting a biomolecule in order to check the viability of this technique for the production of microarrays. A pulsed Nd:YAG laser beam (355 nm wavelength) has been used to transfer droplets of a biomolecule containing solution onto a solid slide. Optical microscopy of the transferred material has been carried out to investigate the morphological characteristics of the droplets obtained under different irradiation conditions. Afterwards, a DNA microarray has been spotted. The viability of the transference has been tested by checking the biological activity of the biomolecule in front of its specific complementary target. This has revealed that, indeed, the LIFT technique is adequate for the production of DNA microarrays.

  19. Inkjet printing for the production of protein microarrays.

    PubMed

    McWilliam, Iain; Chong Kwan, Marisa; Hall, Duncan

    2011-01-01

    A significant proportion of protein microarray researchers would like the arrays they develop to become widely used research, screening, validation or diagnostic devices. For this to be achievable the arrays must be compatible with high-throughput techniques that allow manufacturing scale production. In order to simplify the transition from laboratory bench to market, Arrayjet have developed a range of inkjet microarray printers, which, at one end of the scale, are suitable for R&D and, at the other end, are capable of true high-throughput array output. To maintain scalability, all Arrayjet microarray printers utilise identical core technology comprising a JetSpyder™ liquid handling adaptor, which enables automated loading of an industry standard inkjet printhead compatible with non-contact on-the-fly printing. This chapter contains a detailed explanation of Arrayjet technology followed by a historical look at the development of inkjet technologies for protein microarray production. The method described subsequently is a simple example of an antibody array printed onto nitrocellulose-coated slides with specific detection with fluorescently labelled IgG. The method is linked to a notes section with advice on best practice and sources of useful information for protein microarray production using inkjet technology. PMID:21901611

  20. Self-Assembled Cell Microarray (SAMcell) for High-Throughput RNAi Screening.

    PubMed

    Zhang, Hanshuo; Li, Juan

    2016-01-01

    RNAi has now become a valuable research tool for cell-based high-throughput screening. However, traditional RNAi high-throughput methods are based on multi-well plates, relying on expensive instruments and complicated operations. In this chapter, we describe a method termed self-assembled cell microarray (SAMcell), which integrates micro-fabrication, reverse transfection, and RNAi technologies and allows for cell behavior investigations to be performed directly on the cell chip. This method has been successfully employed to perform large-scale functional screening assays to identify gene modulators of cell migration, cell proliferation, and cellular apoptosis. PMID:27581287

  1. Krylov subspace algorithms for computing GeneRank for the analysis of microarray data mining.

    PubMed

    Wu, Gang; Zhang, Ying; Wei, Yimin

    2010-04-01

    GeneRank is a new engine technology for the analysis of microarray experiments. It combines gene expression information with a network structure derived from gene notations or expression profile correlations. Using matrix decomposition techniques, we first give a matrix analysis of the GeneRank model. We reformulate the GeneRank vector as a linear combination of three parts in the general case when the matrix in question is non-diagonalizable. We then propose two Krylov subspace methods for computing GeneRank. Numerical experiments show that, when the GeneRank problem is very large, the new algorithms are appropriate choices. PMID:20426695

  2. Generation of Aorta Transcript Atlases of Wild-Type and Apolipoprotein E-null Mice by Laser Capture Microdissection-Based mRNA Expression Microarrays.

    PubMed

    Yin, Changjun; Mohanta, Sarajo; Ma, Zhe; Weber, Christian; Hu, Desheng; Weih, Falk; Habenicht, Andreas

    2015-01-01

    Atherosclerosis is a transmural chronic inflammatory disease of medium and large arteries. Though it is well recognized that immune responses contribute to atherosclerosis, it remains unclear whether these responses are carried out in secondary lymphoid organs such as the spleen and lymph nodes and/or within the arterial wall. Arteries are composed of three major layers, i.e., the laminae intima, media, and adventitia. However, each of these layers may play different roles in arterial wall biology and atherogenesis. We identified well-structured artery tertiary lymphoid organs (ATLOs) in the abdominal aorta adventitia but not in the intima of aged apolipoprotein E-null (ApoE(-/-)) mice. These observations suggested that disease-associated immune responses are highly territorialized within the arterial wall and that the adventitia may play distinct and hitherto unrecognized roles. Here, we set out to apply laser capture microdissection (LCM) to dissect plaque, media, adventitia, and adjacent aorta-draining lymph nodes (LN) in aged ApoE(-/-) mice in attempts to establish the territoriality of atherosclerosis immune responses. Using whole-genome mRNA expression microarrays of arterial wall tissues, we constructed robust transcript atlases of wild-type and ApoE(-/-) mouse aortas. Data were deposited in the National Center for Biotechnology Information's gene expression omnibus (GEO) and are accessible to the public through the Internet. These transcript atlases are anticipated to prove valuable to address a wide scope of issues ranging from atherosclerosis immunity and inflammation to the role of single genes in regulating arterial wall remodeling. This chapter presents protocols for LCM of mouse aorta and microarray expression analysis from LCM-isolated aorta laminae. PMID:26445797

  3. Rapid and simultaneous detection of ricin, staphylococcal enterotoxin B and saxitoxin by chemiluminescence-based microarray immunoassay.

    PubMed

    Szkola, A; Linares, E M; Worbs, S; Dorner, B G; Dietrich, R; Märtlbauer, E; Niessner, R; Seidel, M

    2014-11-21

    Simultaneous detection of small and large molecules on microarray immunoassays is a challenge that limits some applications in multiplex analysis. This is the case for biosecurity, where fast, cheap and reliable simultaneous detection of proteotoxins and small toxins is needed. Two highly relevant proteotoxins, ricin (60 kDa) and bacterial toxin staphylococcal enterotoxin B (SEB, 30 kDa) and the small phycotoxin saxitoxin (STX, 0.3 kDa) are potential biological warfare agents and require an analytical tool for simultaneous detection. Proteotoxins are successfully detected by sandwich immunoassays, whereas competitive immunoassays are more suitable for small toxins (<1 kDa). Based on this need, this work provides a novel and efficient solution based on anti-idiotypic antibodies for small molecules to combine both assay principles on one microarray. The biotoxin measurements are performed on a flow-through chemiluminescence microarray platform MCR3 in 18 minutes. The chemiluminescence signal was amplified by using a poly-horseradish peroxidase complex (polyHRP), resulting in low detection limits: 2.9 ± 3.1 μg L(-1) for ricin, 0.1 ± 0.1 μg L(-1) for SEB and 2.3 ± 1.7 μg L(-1) for STX. The developed multiplex system for the three biotoxins is completely novel, relevant in the context of biosecurity and establishes the basis for research on anti-idiotypic antibodies for microarray immunoassays. PMID:25237676

  4. Quantification of the Epitope Diversity of HIV-1-Specific Binding Antibodies by Peptide Microarrays for Global HIV-1 Vaccine Development

    PubMed Central

    Stephenson, Kathryn E.; Neubauer, George H.; Reimer, Ulf; Pawlowski, Nikolaus; Knaute, Tobias; Zerweck, Johannes; Korber, Bette T.; Barouch, Dan H.

    2014-01-01

    An effective vaccine against human immunodeficiency virus type 1 (HIV-1) will have to provide protection against a vast array of different HIV-1 strains. Current methods to measure HIV-1-specific binding antibodies following immunization typically focus on determining the magnitude of antibody responses, but the epitope diversity of antibody responses has remained largely unexplored. Here we describe the development of a global HIV-1 peptide microarray that contains 6,564 peptides from across the HIV-1 proteome and covers the majority of HIV-1 sequences in the Los Alamos National Laboratory global HIV-1 sequence database. Using this microarray, we quantified the magnitude, breadth, and depth of IgG binding to linear HIV-1 sequences in HIV-1-infected humans and HIV-1-vaccinated humans, rhesus monkeys and guinea pigs. The microarray measured potentially important differences in antibody epitope diversity, particularly regarding the depth of epitope variants recognized at each binding site. Our data suggest that the global HIV-1 peptide microarray may be a useful tool for both preclinical and clinical HIV-1 research. PMID:25445329

  5. Identification of non-random sequence properties in groups of signature peptides obtained in random sequence peptide microarray experiments.

    PubMed

    Kuznetsov, Igor B

    2016-05-01

    Immunosignaturing is an emerging experimental technique that uses random sequence peptide microarrays to detect antibodies produced by the immune system in response to a particular disease. Two important questions regarding immunosignaturing are "Do microarray peptides that exhibit a strong affinity to a given type of antibodies share common sequence properties?" and "If so, what are those properties?" In this work, three statistical tests designed to detect non-random patterns in the amino acid makeup of a group of microarray peptides are presented. One test detects patterns of significantly biased amino acid usage, whereas the other two detect patterns of significant bias in the biochemical properties. These tests do not require a large number of peptides per group. The tests were applied to analyze 19 groups of peptides identified in immunosignaturing experiments as being specific for antibodies produced in response to various types of cancer and other diseases. The positional distribution of the biochemical properties of the amino acids in these 19 peptide groups was also studied. Remarkably, despite the random nature of the sequence libraries used to design the microarrays, a unique group-specific non-random pattern was identified in the majority of the peptide groups studied. © 2016 Wiley Periodicals, Inc. Biopolymers (Pept Sci) 106: 318-329, 2016. PMID:27037995

  6. Graph based study of allergen cross-reactivity of plant lipid transfer proteins (LTPs) using microarray in a multicenter study.

    PubMed

    Palacín, Arantxa; Gómez-Casado, Cristina; Rivas, Luis A; Aguirre, Jacobo; Tordesillas, Leticia; Bartra, Joan; Blanco, Carlos; Carrillo, Teresa; Cuesta-Herranz, Javier; de Frutos, Consolación; Alvarez-Eire, Genoveva García; Fernández, Francisco J; Gamboa, Pedro; Muñoz, Rosa; Sánchez-Monge, Rosa; Sirvent, Sofía; Torres, María J; Varela-Losada, Susana; Rodríguez, Rosalía; Parro, Victor; Blanca, Miguel; Salcedo, Gabriel; Díaz-Perales, Araceli

    2012-01-01

    The study of cross-reactivity in allergy is key to both understanding. the allergic response of many patients and providing them with a rational treatment In the present study, protein microarrays and a co-sensitization graph approach were used in conjunction with an allergen microarray immunoassay. This enabled us to include a wide number of proteins and a large number of patients, and to study sensitization profiles among members of the LTP family. Fourteen LTPs from the most frequent plant food-induced allergies in the geographical area studied were printed into a microarray specifically designed for this research. 212 patients with fruit allergy and 117 food-tolerant pollen allergic subjects were recruited from seven regions of Spain with different pollen profiles, and their sera were tested with allergen microarray. This approach has proven itself to be a good tool to study cross-reactivity between members of LTP family, and could become a useful strategy to analyze other families of allergens. PMID:23272072

  7. Quantification of the epitope diversity of HIV-1-specific binding antibodies by peptide microarrays for global HIV-1 vaccine development

    SciTech Connect

    Stephenson, Kathryn E.; Neubauer, George H.; Reimer, Ulf; Pawlowski, Nikolaus; Knaute, Tobias; Zerweck, Johannes; Korber, Bette T.; Barouch, Dan H.

    2014-11-14

    An effective vaccine against human immunodeficiency virus type 1 (HIV-1) will have to provide protection against a vast array of different HIV-1 strains. Current methods to measure HIV-1-specific binding antibodies following immunization typically focus on determining the magnitude of antibody responses, but the epitope diversity of antibody responses has remained largely unexplored. Here we describe the development of a global HIV-1 peptide microarray that contains 6564 peptides from across the HIV-1 proteome and covers the majority of HIV-1 sequences in the Los Alamos National Laboratory global HIV-1 sequence database. Using this microarray, we quantified the magnitude, breadth, and depth of IgG binding to linear HIV-1 sequences in HIV-1-infected humans and HIV-1-vaccinated humans, rhesus monkeys and guinea pigs. The microarray measured potentially important differences in antibody epitope diversity, particularly regarding the depth of epitope variants recognized at each binding site. Our data suggest that the global HIV-1 peptide microarray may be a useful tool for both preclinical and clinical HIV-1 research.

  8. Quantification of the epitope diversity of HIV-1-specific binding antibodies by peptide microarrays for global HIV-1 vaccine development

    DOE PAGESBeta

    Stephenson, Kathryn E.; Neubauer, George H.; Reimer, Ulf; Pawlowski, Nikolaus; Knaute, Tobias; Zerweck, Johannes; Korber, Bette T.; Barouch, Dan H.

    2014-11-14

    An effective vaccine against human immunodeficiency virus type 1 (HIV-1) will have to provide protection against a vast array of different HIV-1 strains. Current methods to measure HIV-1-specific binding antibodies following immunization typically focus on determining the magnitude of antibody responses, but the epitope diversity of antibody responses has remained largely unexplored. Here we describe the development of a global HIV-1 peptide microarray that contains 6564 peptides from across the HIV-1 proteome and covers the majority of HIV-1 sequences in the Los Alamos National Laboratory global HIV-1 sequence database. Using this microarray, we quantified the magnitude, breadth, and depth ofmore » IgG binding to linear HIV-1 sequences in HIV-1-infected humans and HIV-1-vaccinated humans, rhesus monkeys and guinea pigs. The microarray measured potentially important differences in antibody epitope diversity, particularly regarding the depth of epitope variants recognized at each binding site. Our data suggest that the global HIV-1 peptide microarray may be a useful tool for both preclinical and clinical HIV-1 research.« less

  9. Factorial microarray analysis of zebra mussel (Dreissena polymorpha: Dreissenidae, Bivalvia) adhesion

    PubMed Central

    2010-01-01

    Background The zebra mussel (Dreissena polymorpha) has been well known for its expertise in attaching to substances under the water. Studies in past decades on this underwater adhesion focused on the adhesive protein isolated from the byssogenesis apparatus of the zebra mussel. However, the mechanism of the initiation, maintenance, and determination of the attachment process remains largely unknown. Results In this study, we used a zebra mussel cDNA microarray previously developed in our lab and a factorial analysis to identify the genes that were involved in response to the changes of four factors: temperature (Factor A), current velocity (Factor B), dissolved oxygen (Factor C), and byssogenesis status (Factor D). Twenty probes in the microarray were found to be modified by one of the factors. The transcription products of four selected genes, DPFP-BG20_A01, EGP-BG97/192_B06, EGP-BG13_G05, and NH-BG17_C09 were unique to the zebra mussel foot based on the results of quantitative reverse transcription PCR (qRT-PCR). The expression profiles of these four genes under the attachment and non-attachment were also confirmed by qRT-PCR and the result is accordant to that from microarray assay. The in situ hybridization with the RNA probes of two identified genes DPFP-BG20_A01 and EGP-BG97/192_B06 indicated that both of them were expressed by a type of exocrine gland cell located in the middle part of the zebra mussel foot. Conclusions The results of this study suggested that the changes of D. polymorpha byssogenesis status and the environmental factors can dramatically affect the expression profiles of the genes unique to the foot. It turns out that the factorial design and analysis of the microarray experiment is a reliable method to identify the influence of multiple factors on the expression profiles of the probesets in the microarray; therein it provides a powerful tool to reveal the mechanism of zebra mussel underwater attachment. PMID:20509938

  10. Microarray-Based Sketches of the HERV Transcriptome Landscape

    PubMed Central

    Pérot, Philippe; Mugnier, Nathalie; Montgiraud, Cécile; Gimenez, Juliette; Jaillard, Magali; Bonnaud, Bertrand; Mallet, François

    2012-01-01

    Human endogenous retroviruses (HERVs) are spread throughout the genome and their long terminal repeats (LTRs) constitute a wide collection of putative regulatory sequences. Phylogenetic similarities and the profusion of integration sites, two inherent characteristics of transposable elements, make it difficult to study individual locus expression in a large-scale approach, and historically apart from some placental and testis-regulated elements, it was generally accepted that HERVs are silent due to epigenetic control. Herein, we have introduced a generic method aiming to optimally characterize individual loci associated with 25-mer probes by minimizing cross-hybridization risks. We therefore set up a microarray dedicated to a collection of 5,573 HERVs that can reasonably be assigned to a unique genomic position. We obtained a first view of the HERV transcriptome by using a composite panel of 40 normal and 39 tumor samples. The experiment showed that almost one third of the HERV repertoire is indeed transcribed. The HERV transcriptome follows tropism rules, is sensitive to the state of differentiation and, unexpectedly, seems not to correlate with the age of the HERV families. The probeset definition within the U3 and U5 regions was used to assign a function to some LTRs (i.e. promoter or polyA) and revealed that (i) autonomous active LTRs are broadly subjected to operational determinism (ii) the cellular gene density is substantially higher in the surrounding environment of active LTRs compared to silent LTRs and (iii) the configuration of neighboring cellular genes differs between active and silent LTRs, showing an approximately 8 kb zone upstream of promoter LTRs characterized by a drastic reduction in sense cellular genes. These gathered observations are discussed in terms of virus/host adaptive strategies, and together with the methods and tools developed for this purpose, this work paves the way for further HERV transcriptome projects. PMID:22761958

  11. DNA Microarray-Based Typing of Streptococcus agalactiae Isolates

    PubMed Central

    Nitschke, Heike; Slickers, Peter; Müller, Elke; Ehricht, Ralf

    2014-01-01

    Streptococcus agalactiae frequently colonizes the urogenital tract, and it is a major cause of bacterial septicemia, meningitis, and pneumonia in newborns. For typing purposes, a microarray targeting group B streptococcus (GBS) virulence-associated markers and resistance genes was designed and validated with reference strains, as well as clinical and veterinary isolates. Selected isolates were also subjected to multilocus sequence typing. It was observed that putative typing markers, such as alleles of the alpha-like protein or capsule types, vary independently of each other, and they also vary independently from the affiliation to their multilocus sequence typing (MLST)-defined sequence types. Thus, it is not possible to assign isolates to sequence types based on the identification of a single distinct marker, such as a capsule type or alp allele. This suggests the occurrence of frequent genomic recombination. For array-based typing, a set of 11 markers (bac, alp, pil1 locus, pepS8, fbsB, capsule locus, hylB, abiG-I/-II plus Q8DZ34, pil2 locus, nss plus srr plus rogB2, and rgfC/A/D/B) was defined that provides a framework for splitting the tested 448 S. agalactiae isolates into 76 strains that clustered mainly according to MLST-defined clonal complexes. There was evidence for region- and host-specific differences in the population structure of S. agalactiae, as well as an overrepresentation of strains related to sequence type 17 among the invasive isolates. The arrays and typing scheme described here proved to be a convenient tool for genotyping large numbers of clinical/veterinary isolates and thus might help obtain insight into the epidemiology of S. agalactiae. PMID:25165085

  12. CLUM: a cluster program for analyzing microarray data.

    PubMed

    Irigoien, I; Fernandez, E; Vives, S; Arenas, C

    2008-08-01

    Microarray technology is increasingly being applied in biological and medical research to address a wide range of problems. Cluster analysis has proven to be a very useful tool for investigating the structure of microarray data. This paper presents a program for clustering microarray data, which is based on the so call path-distance. The algorithm gives in each step a partition in two clusters and no prior assumptions on the structure of clusters are required. It assigns each object (gene or sample) to only one cluster and gives the global optimum for the function that quantifies the adequacy of a given partition of the sample into k clusters. The program was tested on experimental data sets, showing the robustness of the algorithm. PMID:18825964

  13. Comparative analysis of genomic signal processing for microarray data clustering.

    PubMed

    Istepanian, Robert S H; Sungoor, Ala; Nebel, Jean-Christophe

    2011-12-01

    Genomic signal processing is a new area of research that combines advanced digital signal processing methodologies for enhanced genetic data analysis. It has many promising applications in bioinformatics and next generation of healthcare systems, in particular, in the field of microarray data clustering. In this paper we present a comparative performance analysis of enhanced digital spectral analysis methods for robust clustering of gene expression across multiple microarray data samples. Three digital signal processing methods: linear predictive coding, wavelet decomposition, and fractal dimension are studied to provide a comparative evaluation of the clustering performance of these methods on several microarray datasets. The results of this study show that the fractal approach provides the best clustering accuracy compared to other digital signal processing and well known statistical methods. PMID:22157075

  14. [Research progress of probe design software of oligonucleotide microarrays].

    PubMed

    Chen, Xi; Wu, Zaoquan; Liu, Zhengchun

    2014-02-01

    DNA microarray has become an essential medical genetic diagnostic tool for its high-throughput, miniaturization and automation. The design and selection of oligonucleotide probes are critical for preparing gene chips with high quality. Several sets of probe design software have been developed and are available to perform this work now. Every set of the software aims to different target sequences and shows different advantages and limitations. In this article, the research and development of these sets of software are reviewed in line with three main criteria, including specificity, sensitivity and melting temperature (Tm). In addition, based on the experimental results from literatures, these sets of software are classified according to their applications. This review will be helpful for users to choose an appropriate probe-design software. It will also reduce the costs of microarrays, improve the application efficiency of microarrays, and promote both the research and development (R&D) and commercialization of high-performance probe design software. PMID:24804514

  15. Fluorous-based Peptide Microarrays for Protease Screening

    PubMed Central

    Collet, Beatrice Y. M.; Nagashima, Tadamichi; Yu, Marvin S.; Pohl, Nicola L. B.

    2009-01-01

    As ever more protease sequences are uncovered through genome sequencing projects, efficient parallel methods to discover the potential substrates of these proteases becomes crucial. Herein we describe the first use of fluorous-based microarrays to probe peptide sequences and begin to define the scope and limitations of fluorous microarray technologies for the screening of proteases. Comparison of a series of serine proteases showed that their ability to cleave peptide substrates in solution was maintained upon immobilization of these substrates onto fluorous-coated glass slides. The fluorous surface did not serve to significantly inactivate the enzymes. However, addition of hydrophilic components to the peptide sequences could induce lower rates of substrate cleavage with enzymes such as chymotrypsin with affinities to hydrophobic moieties. This work represents the first step to creating robust protease screening platforms using noncovalent microarray interface that can easily incorporate a range of compounds on the same slide. PMID:20161483

  16. A Protein Microarray ELISA for Screening Biological Fluids

    SciTech Connect

    Varnum, Susan M.; Woodbury, Ronald L.; Zangar, Richard C.

    2004-02-01

    Protein microarrays permit the simultaneous measurement of many proteins in a small sample volume and therefore provide an attractive approach for the quantitative measurement of proteins in biological fluids, including serum. This chapter describes a microarray ELISA assay. Capture antibodies are immobilized onto a glass surface, the covalently attached antibodies bind a specific antigen from a sample overlaying the array. A second, biotinylated antibody that recognizes the same antigen as the first antibody but at a different epitope is then used for detection. Detection is based upon an enzymatic signal enhancement method known as tyramide signal amplification (TSA). By coupling a microarray-ELISA format with the signal amplification of tyramide deposition, the assay sensitivity is as low as sub-pg/ml.

  17. Emergent FDA biodefense issues for microarray technology: process analytical technology.

    PubMed

    Weinberg, Sandy

    2004-11-01

    A successful biodefense strategy relies upon any combination of four approaches. A nation can protect its troops and citizenry first by advanced mass vaccination, second, by responsive ring vaccination, and third, by post-exposure therapeutic treatment (including vaccine therapies). Finally, protection can be achieved by rapid detection followed by exposure limitation (suites and air filters) or immediate treatment (e.g., antibiotics, rapid vaccines and iodine pills). All of these strategies rely upon or are enhanced by microarray technologies. Microarrays can be used to screen, engineer and test vaccines. They are also used to construct early detection tools. While effective biodefense utilizes a variety of tactical tools, microarray technology is a valuable arrow in that quiver. PMID:15525220

  18. Salt concentration effects on equilibrium melting curves from DNA microarrays.

    PubMed

    Fuchs, J; Fiche, J-B; Buhot, A; Calemczuk, R; Livache, T

    2010-09-22

    DNA microarrays find applications in an increasing number of domains where more quantitative results are required. DNA being a charged polymer, the repulsive interactions between the surface of the microarray and the targets in solution are increasing upon hybridization. Such electrostatic penalty is generally reduced by increasing the salt concentration. In this article, we present equilibrium-melting curves obtained from dedicated physicochemical experiments on DNA microarrays in order to get a better understanding of the electrostatic penalty incurred during the hybridization reaction at the surface. Various salt concentrations have been considered and deviations from the commonly used Langmuir adsorption model are experimentally quantified for the first time in agreement with theoretical predictions. PMID:20858434

  19. An easy operating pathogen microarray (EOPM) platform for rapid screening of vertebrate pathogens

    PubMed Central

    2013-01-01

    Background Infectious diseases emerge frequently in China, partly because of its large and highly mobile population. Therefore, a rapid and cost-effective pathogen screening method with broad coverage is required for prevention and control of infectious diseases. The availability of a large number of microbial genome sequences generated by conventional Sanger sequencing and next generation sequencing has enabled the development of a high-throughput high-density microarray platform for rapid large-scale screening of vertebrate pathogens. Methods An easy operating pathogen microarray (EOPM) was designed to detect almost all known pathogens and related species based on their genomic sequences. For effective identification of pathogens from EOPM data, a statistical enrichment algorithm has been proposed, and further implemented in a user-friendly web-based interface. Results Using multiple probes designed to specifically detect a microbial genus or species, EOPM can correctly identify known pathogens at the species or genus level in blinded testing. Despite a lower sensitivity than PCR, EOPM is sufficiently sensitive to detect the predominant pathogens causing clinical symptoms. During application in two recent clinical infectious disease outbreaks in China, EOPM successfully identified the responsible pathogens. Conclusions EOPM is an effective surveillance platform for infectious diseases, and can play an important role in infectious disease control. PMID:24053492

  20. Nanodroplet chemical microarrays and label-free assays.

    PubMed

    Gosalia, Dhaval; Diamond, Scott L

    2010-01-01

    The microarraying of chemicals or biomolecules on a glass surface allows for dense storage and miniaturized screening experiments and can be deployed in chemical-biology research or drug discovery. Microarraying allows the production of scores of replicate slides. Small molecule libraries are typically stored as 10 mM DMSO stock solutions, whereas libraries of biomolecules are typically stored in high percentages of glycerol. Thus, a method is required to print such libraries on microarrays, and then assay them against biological targets. By printing either small molecule libraries or biomolecule libraries in an aqueous solvent containing glycerol, each adherent nanodroplet remains fixed at a position on the microarray by surface tension without the use of wells, without evaporating, and without the need for chemically linking the compound to the surface. Importantly, glycerol is a high boiling point solvent that is fully miscible with DMSO and water and has the additional property of stabilizing various enzymes. The nanoliter volume of the droplet forms the reaction compartment once additional reagents are metered onto the microarray, either by aerosol spray deposition or by addressable acoustic dispensing. Incubation of the nanodroplet microarray in a high humidity environment controls the final water content of the reaction. This platform has been validated for fluorescent HTS assays of protease and kinases as well as for fluorogenic substrate profiling of proteases. Label-free HTS is also possible by running nanoliter HTS reactions on a MALDI target for mass spectrometry (MS) analysis without the need for desalting of the samples. A method is described for running nanoliter-scale multicomponent homogeneous reactions followed by label-free MALDI MS spectrometry analysis of the reactions. PMID:20857358

  1. Chromosomal Microarrays for the Prenatal Detection of Microdeletions and Microduplications.

    PubMed

    Wou, Karen; Levy, Brynn; Wapner, Ronald J

    2016-06-01

    Chromosomal microarray analysis has replaced conventional G-banded karyotype in prenatal diagnosis as the first-tier test for the cytogenetic detection of copy number imbalances in fetuses with/without major structural abnormalities. This article reviews the basic technology of microarray; the value and clinical significance of the detection of microdeletions, microduplications, and other copy number variants; as well as the importance of genetic counseling for prenatal diagnosis. It also discusses the current status of noninvasive screening for some of these microdeletion and microduplication syndromes. PMID:27235911

  2. Unravelling Microbial Communities with DNA-Microarrays: Challengesand Future Directions.

    SciTech Connect

    Wagner, Michael; Smidt, Hauke; Loy, Alexander; Zhou, Jizhong

    2007-03-08

    High-throughput technologies are urgently needed formonitoring the formidable biodiversity and functional capabilities ofmicroorganisms in the environment. Ten years ago, DNA microarrays,miniaturized platforms for highly parallel hybridization reactions, foundtheir way into environmental microbiology and raised great expectationsamong researchers in the field. In this article, we briefly summarize thestate-of-the-art of microarray approaches in microbial ecology researchand discuss in more detail crucial problems and promising solutions.Finally, we outline scenarios for an innovative combination ofmicroarrays with other molecular tools for structure-function analysis ofcomplex microbial communities.

  3. Label and Label-Free Detection Techniques for Protein Microarrays

    PubMed Central

    Syahir, Amir; Usui, Kenji; Tomizaki, Kin-ya; Kajikawa, Kotaro; Mihara, Hisakazu

    2015-01-01

    Protein microarray technology has gone through numerous innovative developments in recent decades. In this review, we focus on the development of protein detection methods embedded in the technology. Early microarrays utilized useful chromophores and versatile biochemical techniques dominated by high-throughput illumination. Recently, the realization of label-free techniques has been greatly advanced by the combination of knowledge in material sciences, computational design and nanofabrication. These rapidly advancing techniques aim to provide data without the intervention of label molecules. Here, we present a brief overview of this remarkable innovation from the perspectives of label and label-free techniques in transducing nano-biological events.

  4. DNA microarrays: design principles for maximizing ergodic, chaotic mixing.

    PubMed

    Hertzsch, Jan-Martin; Sturman, Rob; Wiggins, Stephen

    2007-02-01

    In this article we show that models of flows in DNA microarrays generated by pulsed source-sink pairs can be studied as linked twist maps. The significance of this is that it enables us to relate the flow to mathematically precise notions of chaotic mixing that can be realized through specific design criteria. We apply these techniques to three different mixing protocols, two of which have been previously described in the literature, and we are able to isolate the features of each mixer that lead to "good" or "bad" mixing. Based on this, we propose a new design to generate a "well-mixed" flow in a DNA microarray. PMID:17262763

  5. Hand-held portable microarray reader for biodetection

    DOEpatents

    Thompson, Deanna Lynn; Coleman, Matthew A; Lane, Stephen M; Matthews, Dennis L; Albala, Joanna; Wachsmann-Hogiu, Sebastian

    2013-04-23

    A hand-held portable microarray reader for biodetection includes a microarray reader engineered to be small enough for portable applications. The invention includes a high-powered light-emitting diode that emits excitation light, an excitation filter positioned to receive the excitation light, a slide, a slide holder assembly for positioning the slide to receive the excitation light from the excitation filter, an emission filter positioned to receive the excitation light from the slide, a lens positioned to receive the excitation light from the emission filter, and a CCD camera positioned to receive the excitation light from the lens.

  6. Are glycan biosensors an alternative to glycan microarrays?

    PubMed Central

    Hushegyi, A.

    2016-01-01

    Complex carbohydrates (glycans) play an important role in nature and study of their interaction with proteins or intact cells can be useful for understanding many physiological and pathological processes. Such interactions have been successfully interrogated in a highly parallel way using glycan microarrays, but this technique has some limitations. Thus, in recent years glycan biosensors in numerous progressive configurations have been developed offering distinct advantages compared to glycan microarrays. Thus, in this review advances achieved in the field of label-free glycan biosensors are discussed.

  7. Genome Rearrangements Detected by SNP Microarrays in Individuals with Intellectual Disability Referred with Possible Williams Syndrome

    PubMed Central

    Pani, Ariel M.; Hobart, Holly H.; Morris, Colleen A.; Mervis, Carolyn B.; Bray-Ward, Patricia; Kimberley, Kendra W.; Rios, Cecilia M.; Clark, Robin C.; Gulbronson, Maricela D.; Gowans, Gordon C.; Gregg, Ronald G.

    2010-01-01

    Background Intellectual disability (ID) affects 2–3% of the population and may occur with or without multiple congenital anomalies (MCA) or other medical conditions. Established genetic syndromes and visible chromosome abnormalities account for a substantial percentage of ID diagnoses, although for ∼50% the molecular etiology is unknown. Individuals with features suggestive of various syndromes but lacking their associated genetic anomalies pose a formidable clinical challenge. With the advent of microarray techniques, submicroscopic genome alterations not associated with known syndromes are emerging as a significant cause of ID and MCA. Methodology/Principal Findings High-density SNP microarrays were used to determine genome wide copy number in 42 individuals: 7 with confirmed alterations in the WS region but atypical clinical phenotypes, 31 with ID and/or MCA, and 4 controls. One individual from the first group had the most telomeric gene in the WS critical region deleted along with 2 Mb of flanking sequence. A second person had the classic WS deletion and a rearrangement on chromosome 5p within the Cri du Chat syndrome (OMIM:123450) region. Six individuals from the ID/MCA group had large rearrangements (3 deletions, 3 duplications), one of whom had a large inversion associated with a deletion that was not detected by the SNP arrays. Conclusions/Significance Combining SNP microarray analyses and qPCR allowed us to clone and sequence 21 deletion breakpoints in individuals with atypical deletions in the WS region and/or ID or MCA. Comparison of these breakpoints to databases of genomic variation revealed that 52% occurred in regions harboring structural variants in the general population. For two probands the genomic alterations were flanked by segmental duplications, which frequently mediate recurrent genome rearrangements; these may represent new genomic disorders. While SNP arrays and related technologies can identify potentially pathogenic deletions and

  8. Decentralized Data Sharing of Tissue Microarrays for Investigative Research in Oncology

    PubMed Central

    Chen, Wenjin; Schmidt, Cristina; Parashar, Manish; Reiss, Michael; Foran, David J.

    2007-01-01

    Tissue microarray technology (TMA) is a relatively new approach for efficiently and economically assessing protein and gene expression across large ensembles of tissue specimens. Tissue microarray technology holds great potential for reducing the time and cost associated with conducting research in tissue banking, proteomics, and outcome studies. However, the sheer volume of images and other data generated from even limited studies involving tissue microarrays quickly approach the processing capacity and resources of a division or department. This challenge is compounded by the fact that large-scale projects in several areas of modern research rely upon multi-institutional efforts in which investigators and resources are spread out over multiple campuses, cities, and states. To address some of the data management issues several leading institutions have begun to develop their own “in-house” systems, independently, but such data will be only minimally useful if it isn’t accessible to others in the scientific community. Investigators at different institutions studying the same or related disorders might benefit from the synergy of sharing results. To facilitate sharing of TMA data across different database implementations, the Technical Standards Committee of the Association for Pathology Informatics organized workshops in efforts to establish a standardized TMA data exchange specification. The focus of our research does not relate to the establishment of standards for exchange, but rather builds on these efforts and concentrates on the design, development and deployment of a decentralized collaboratory for the unsupervised characterization, and seamless and secure discovery and sharing of TMA data. Specifically, we present a self-organizing, peer-to-peer indexing and discovery infrastructure for quantitatively assessing digitized TMA’s. The system utilizes a novel, optimized decentralized search engine that supports flexible querying, while guaranteeing that

  9. Improving PLS-RFE based gene selection for microarray data classification.

    PubMed

    Wang, Aiguo; An, Ning; Chen, Guilin; Li, Lian; Alterovitz, Gil

    2015-07-01

    Gene selection plays a crucial role in constructing efficient classifiers for microarray data classification, since microarray data is characterized by high dimensionality and small sample sizes and contains irrelevant and redundant genes. In practical use, partial least squares-based gene selection approaches can obtain gene subsets of good qualities, but are considerably time-consuming. In this paper, we propose to integrate partial least squares based recursive feature elimination (PLS-RFE) with two feature elimination schemes: simulated annealing and square root, respectively, to speed up the feature selection process. Inspired from the strategy of annealing schedule, the two proposed approaches eliminate a number of features rather than one least informative feature during each iteration and the number of removed features decreases as the iteration proceeds. To verify the effectiveness and efficiency of the proposed approaches, we perform extensive experiments on six publicly available microarray data with three typical classifiers, including Naïve Bayes, K-Nearest-Neighbor and Support Vector Machine, and compare our approaches with ReliefF, PLS and PLS-RFE feature selectors in terms of classification accuracy and running time. Experimental results demonstrate that the two proposed approaches accelerate the feature selection process impressively without degrading the classification accuracy and obtain more compact feature subsets for both two-category and multi-category problems. Further experimental comparisons in feature subset consistency show that the proposed approach with simulated annealing scheme not only has better time performance, but also obtains slightly better feature subset consistency than the one with square root scheme. PMID:25912984

  10. ArraySolver: An Algorithm for Colour-Coded Graphical Display and Wilcoxon Signed-Rank Statistics for Comparing Microarray Gene Expression Data

    PubMed Central

    2004-01-01

    The massive surge in the production of microarray data poses a great challenge for proper analysis and interpretation. In recent years numerous computational tools have been developed to extract meaningful interpretation of microarray gene expression data. However, a convenient tool for two-groups comparison of microarray data is still lacking and users have to rely on commercial statistical packages that might be costly and require special skills, in addition to extra time and effort for transferring data from one platform to other. Various statistical methods, including the t-test, analysis of variance, Pearson test and Mann–Whitney U test, have been reported for comparing microarray data, whereas the utilization of the Wilcoxon signed-rank test, which is an appropriate test for two-groups comparison of gene expression data, has largely been neglected in microarray studies. The aim of this investigation was to build an integrated tool, ArraySolver, for colour-coded graphical display and comparison of gene expression data using the Wilcoxon signed-rank test. The results of software validation showed similar outputs with ArraySolver and SPSS for large datasets. Whereas the former program appeared to be more accurate for 25 or fewer pairs (n ≤ 25), suggesting its potential application in analysing molecular signatures that usually contain small numbers of genes. The main advantages of ArraySolver are easy data selection, convenient report format, accurate statistics and the familiar Excel platform. PMID:18629036

  11. A modified hyperplane clustering algorithm allows for efficient and accurate clustering of extremely large datasets

    PubMed Central

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

    2009-01-01

    Motivation: As the number of publically available microarray experiments increases, the ability to analyze extremely large datasets across multiple experiments becomes critical. There is a requirement to develop algorithms which are fast and can cluster extremely large datasets without affecting the cluster quality. Clustering is an unsupervised exploratory technique applied to microarray data to find similar data structures or expression patterns. Because of the high input/output costs involved and large distance matrices calculated, most of the algomerative clustering algorithms fail on large datasets (30 000 + genes/200 + arrays). In this article, we propose a new two-stage algorithm which partitions the high-dimensional space associated with microarray data using hyperplanes. The first stage is based on the Balanced Iterative Reducing and Clustering using Hierarchies algorithm with the second stage being a conventional k-means clustering technique. This algorithm has been implemented in a software tool (HPCluster) designed to cluster gene expression data. We compared the clustering results using the two-stage hyperplane algorithm with the conventional k-means algorithm from other available programs. Because, the first stage traverses the data in a single scan, the performance and speed increases substantially. The data reduction accomplished in the first stage of the algorithm reduces the memory requirements allowing us to cluster 44 460 genes without failure and significantly decreases the time to complete when compared with popular k-means programs. The software was written in C# (.NET 1.1). Availability: The program is freely available and can be downloaded from http://www.amdcc.org/bioinformatics/bioinformatics.aspx. Contact: rmcindoe@mail.mcg.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:19261720

  12. The Effects of Pre-Kindergarten Participation on Reading Achievement among English Language Learners Who Are Socioeconomically Disadvantaged in Grades 1, 2 and 3 in a Large Urban Public School District in North Texas

    ERIC Educational Resources Information Center

    Permenter, Diane Aldrich

    2013-01-01

    This study compared the standardized reading achievement scores in grades 1, 2 and 3 of two groups of students: one group who participated in Pre-Kindergarten (PK) in a large urban public school district in North Texas, with the assessment results of a group of grade level peers with similar ethnic and socioeconomic characteristics, who did not…

  13. Genome-wide polymorphisms and development of a microarray platform to detect genetic variations in Plasmodium yoelii.

    PubMed

    Nair, Sethu C; Pattaradilokrat, Sittiporn; Zilversmit, Martine M; Dommer, Jennifer; Nagarajan, Vijayaraj; Stephens, Melissa T; Xiao, Wenming; Tan, John C; Su, Xin-Zhuan

    2014-01-01

    The rodent malaria parasite Plasmodium yoelii is an important model for studying malaria immunity and pathogenesis. One approach for studying malaria disease phenotypes is genetic mapping, which requires typing a large number of genetic markers from multiple parasite strains and/or progeny from genetic crosses. Hundreds of microsatellite (MS) markers have been developed to genotype the P. yoelii genome; however, typing a large number of MS markers can be labor intensive, time consuming, and expensive. Thus, development of high-throughput genotyping tools such as DNA microarrays that enable rapid and accurate large-scale genotyping of the malaria parasite will be highly desirable. In this study, we sequenced the genomes of two P. yoelii strains (33X and N67) and obtained a large number of single nucleotide polymorphisms (SNPs). Based on the SNPs obtained, we designed sets of oligonucleotide probes to develop a microarray that could interrogate ∼11,000 SNPs across the 14 chromosomes of the parasite in a single hybridization. Results from hybridizations of DNA samples of five P. yoelii strains or cloned lines (17XNL, YM, 33X, N67 and N67C) and two progeny from a genetic cross (N67×17XNL) to the microarray showed that the array had a high call rate (∼97%) and accuracy (99.9%) in calling SNPs, providing a simple and reliable tool for typing the P. yoelii genome. Our data show that the P. yoelii genome is highly polymorphic, although isogenic pairs of parasites were also detected. Additionally, our results indicate that the 33X parasite is a progeny of 17XNL (or YM) and an unknown parasite. The highly accurate and reliable microarray developed in this study will greatly facilitate our ability to study the genetic basis of important traits and the disease it causes. PMID:24685548

  14. A highly oriented hybrid microarray modified electrode fabricated by a template-free method for ultrasensitive electrochemical DNA recognition.

    PubMed

    Shi, Lei; Chu, Zhenyu; Dong, Xueliang; Jin, Wanqin; Dempsey, Eithne

    2013-11-01

    Highly oriented growth of a hybrid microarray was realized by a facile template-free method on gold substrates for the first time. The proposed formation mechanism involves an interfacial structure-directing force arising from self-assembled monolayers (SAMs) between gold substrates and hybrid crystals. Different SAMs and variable surface coverage of the assembled molecules play a critical role in the interfacial directing forces and influence the morphologies of hybrid films. A highly oriented hybrid microarray was formed on the highly aligned and vertical SAMs of 1,4-benzenedithiol molecules with rigid backbones, which afforded an intense structure-directing power for the oriented growth of hybrid crystals. Additionally, the density of the microarray could be adjusted by controlling the surface coverage of assembled molecules. Based on the hybrid microarray modified electrode with a large specific area (ca. 10 times its geometrical area), a label-free electrochemical DNA biosensor was constructed for the detection of an oligonucleotide fragment of the avian flu virus H5N1. The DNA biosensor displayed a significantly low detection limit of 5 pM (S/N = 3), a wide linear response from 10 pM to 10 nM, as well as excellent selectivity, good regeneration and high stability. We expect that the proposed template-free method can provide a new reference for the fabrication of a highly oriented hybrid array and the as-prepared microarray modified electrode will be a promising paradigm in constructing highly sensitive and selective biosensors. PMID:24061929

  15. Combining resources to obtain a comprehensive survey of the bovine embryo transcriptome through deep sequencing and microarrays.

    PubMed

    Robert, Claude; Nieminen, Julie; Dufort, Isabelle; Gagné, Dominic; Grant, Jason R; Cagnone, Gaël; Plourde, Dany; Nivet, Anne-Laure; Fournier, Éric; Paquet, Éric; Blazejczyk, Michal; Rigault, Philippe; Juge, Nicolas; Sirard, Marc-André

    2011-09-01

    While most assisted reproductive technologies (ART) are considered routine for the reproduction of species of economical importance, such as the bovine, the impact of these manipulations on the developing embryo remains largely unknown. In an effort to obtain a comprehensive survey of the bovine embryo transcriptome and how it is modified by ART, resources were combined to design an embryo-specific microarray. Close to one million high-quality reads were produced from subtracted bovine embryo libraries using Roche 454 Titanium deep sequencing technology, which enabled the creation of an augmented bovine genome catalog. This catalog was enriched with bovine embryo transcripts, and included newly discovered indel type and 3'UTR variants. Using this augmented bovine genome catalog, the EmbryoGENE Bovine Microarray was designed and is composed of a total of 42,242 probes, including 21,139 known reference genes; 9,322 probes for novel transcribed regions (NTRs); 3,677 alternatively spliced exons; 3,353 3'-tiling probes; and 3,723 controls. A suite of bioinformatics tools was also developed to facilitate microrarray data analysis and database creation; it includes a quality control module, a Laboratory Information Management System (LIMS) and microarray analysis software. Results obtained during this study have already led to the identification of differentially expressed blastocyst targets, NTRs, splice variants of the indel type, and 3'UTR variants. We were able to confirm microarray results by real-time PCR, indicating that the EmbryoGENE bovine microarray has the power to detect physiologically relevant changes in gene expression. PMID:21812063

  16. Transcriptome assembly and microarray construction for Enchytraeus crypticus, a model oligochaete to assess stress response mechanisms derived from soil conditions

    PubMed Central

    2014-01-01

    Background The soil worm Enchytraeus crypticus (Oligochaeta) is an ecotoxicology model species that, until now, was without genome or transcriptome sequence information. The present research aims at studying the transcriptome of Enchytraeus crypticus, sampled from multiple test conditions, and the construction of a high-density microarray for functional genomic studies. Results Over 1.5 million cDNA sequence reads were obtained representing 645 million nucleotides. After assembly, 27,296 contigs and 87,686 singletons were obtained, from which 44% and 25% are annotated as protein-coding genes, respectively, sharing homology with other animal proteomes. Concerning assembly quality, 84% of the contig sequences contain an open reading frame with a start codon while E. crypticus homologs were identified for 92% of the core eukaryotic genes. Moreover, 65% and 77% of the singletons and contigs without known homologs, respectively, were shown to be transcribed in an independent microarray experiment. An Agilent 180 K microarray platform was designed and validated by hybridizing cDNA from 4 day zinc- exposed E. crypticus to the concentration corresponding to 50% reduction in reproduction after three weeks (EC50). Overall, 70% of all probes signaled expression above background levels (mean signal + 1x standard deviation). More specifically, the probes derived from contigs showed a wider range of average intensities when compared to probes derived from singletons. In total, 522 significantly differentially regulated transcripts were identified upon zinc exposure. Several significantly regulated genes exerted predicted functions (e.g. zinc efflux, zinc transport) associated with zinc stress. Unexpectedly, the microarray data suggest that zinc exposure alters retro transposon activity in the E. crypticus genome. Conclusion An initial investigation of the E. crypticus transcriptome including an associated microarray platform for future studies proves to be a valuable

  17. Microarray platform for the detection of a range of plant viruses and viroids.

    PubMed

    Adams, Ian; Harrison, Catherine; Tomlinson, Jenny; Boonham, Neil

    2015-01-01

    Diagnostic microarrays are a useful tool for the simultaneous detection of multiple targets. In this chapter we describe the use of a simple tube-based microarray platform for the detection of plant infecting viruses and viroids. PMID:25981261

  18. IMPROVING THE RELIABILITY OF MICROARRAYS FOR TOXICOLOGY RESEARCH: A COLLABORATIVE APPROACH

    EPA Science Inventory

    Microarray-based gene expression profiling is a critical tool to identify molecular biomarkers of specific chemical stressors. Although current microarray technologies have progressed from their infancy, biological and technical repeatability and reliability are often still limit...

  19. THE MAQC PROJECT: ESTABLISHING QC METRICS AND THRESHOLDS FOR MICROARRAY QUALITY CONTROL

    EPA Science Inventory

    Microarrays represent a core technology in pharmacogenomics and toxicogenomics; however, before this technology can successfully and reliably be applied in clinical practice and regulatory decision-making, standards and quality measures need to be developed. The Microarray Qualit...

  20. Challenges of microarray applications for microbial detection and gene expression profiling in food

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Microarray technology represents one of the latest advances in molecular biology. The diverse types of microarrays have been applied to clinical and environmental microbiology, microbial ecology, and in human, veterinary, and plant diagnostics. Since multiple genes can be analyzed simultaneously, ...

  1. Genetic mapping in grapevine using a SNP microarray: intensity values

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Genotyping microarrays are widely used for genome wide association studies, but in high-diversity organisms, the quality of SNP calls can be diminished by genetic variation near the assayed nucleotide. To address this limitation in grapevine, we developed a simple heuristic that uses hybridization i...

  2. Disc-based microarrays: principles and analytical applications.

    PubMed

    Morais, Sergi; Puchades, Rosa; Maquieira, Ángel

    2016-07-01

    The idea of using disk drives to monitor molecular biorecognition events on regular optical discs has received considerable attention during the last decade. CDs, DVDs, Blu-ray discs and other new optical discs are universal and versatile supports with the potential for development of protein and DNA microarrays. Besides, standard disk drives incorporated in personal computers can be used as compact and affordable optical reading devices. Consequently, a CD technology, resulting from the audio-video industry, has been used to develop analytical applications in health care, environmental monitoring, food safety and quality assurance. The review presents and critically evaluates the current state of the art of disc-based microarrays with illustrative examples, including past, current and future developments. Special mention is made of the analytical developments that use either chemically activated or raw standard CDs where proteins, oligonucleotides, peptides, haptens or other biological probes are immobilized. The discs are also used to perform the assays and must maintain their readability with standard optical drives. The concept and principle of evolving disc-based microarrays and the evolution of disk drives as optical detectors are also described. The review concludes with the most relevant uses ordered chronologically to provide an overview of the progress of CD technology applications in the life sciences. Also, it provides a selection of important references to the current literature. Graphical Abstract High density disc-based microarrays. PMID:26922341

  3. See what you eat--broad GMO screening with microarrays.

    PubMed

    von Götz, Franz

    2010-03-01

    Despite the controversy of whether genetically modified organisms (GMOs) are beneficial or harmful for humans, animals, and/or ecosystems, the number of cultivated GMOs is increasing every year. Many countries and federations have implemented safety and surveillance systems for GMOs. Potent testing technologies need to be developed and implemented to monitor the increasing number of GMOs. First, these GMO tests need to be comprehensive, i.e., should detect all, or at least the most important, GMOs on the market. This type of GMO screening requires a high degree of parallel tests or multiplexing. To date, DNA microarrays have the highest number of multiplexing capabilities when nucleic acids are analyzed. This trend article focuses on the evolution of DNA microarrays for GMO testing. Over the last 7 years, combinations of multiplex PCR detection and microarray detection have been developed to qualitatively assess the presence of GMOs. One example is the commercially available DualChip GMO (Eppendorf, Germany; http://www.eppendorf-biochip.com), which is the only GMO screening system successfully validated in a multicenter study. With use of innovative amplification techniques, promising steps have recently been taken to make GMO detection with microarrays quantitative. PMID:19862507

  4. A microarray immunoassay for simultaneous detection of proteins and bacteria

    NASA Technical Reports Server (NTRS)

    Delehanty, James B.; Ligler, Frances S.

    2002-01-01

    We report the development and characterization of an antibody microarray biosensor for the rapid detection of both protein and bacterial analytes under flow conditions. Using a noncontact microarray printer, biotinylated capture antibodies were immobilized at discrete locations on the surface of an avidin-coated glass microscope slide. Preservation of capture antibody function during the deposition process was accomplished with the use of a low-salt buffer containing sucrose and bovine serum albumin. The slide was fitted with a six-channel flow module that conducted analyte-containing solutions over the array of capture antibody microspots. Detection of bound analyte was subsequently achieved using fluorescent tracer antibodies. The pattern of fluorescent complexes was interrogated using a scanning confocal microscope equipped with a 635-nm laser. This microarray system was employed to detect protein and bacterial analytes both individually and in samples containing mixtures of analytes. Assays were completed in 15 min, and detection of cholera toxin, staphylococcal enterotoxin B, ricin, and Bacillus globigii was demonstrated at levels as low as 8 ng/mL, 4 ng/mL, 10 ng/mL, and 6.2 x 10(4) cfu/mL, respectively. The assays presented here are very fast, as compared to previously published methods for measuring antibody-antigen interactions using microarrays (minutes versus hours).

  5. Application of Microarray Technology to Investigate Salmonella genomics

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Microarrays were developed for the molecular study of various genes in Salmonella species, which may be important in causing illness in both humans and animals. There are over 2400 Salmonella serotypes each of which differs in their ability to cause disease in humans and animals, persist within the ...

  6. Detection of bacterial pathogens in environmental samples using DNA microarrays.

    PubMed

    Call, Douglas R; Borucki, Monica K; Loge, Frank J

    2003-05-01

    Polymerase chain reaction (PCR) is an important tool for pathogen detection, but historically, it has not been possible to accurately identify PCR products without sequencing, Southern blots, or dot-blots. Microarrays can be coupled with PCR where they serve as a set of parallel dot-blots to enhance product detection and identification. Microarrays are composed of many discretely located probes on a solid substrate such as glass. Each probe is composed of a sequence that is complimentary to a pathogen-specific gene sequence. PCR is used to amplify one or more genes and the products are then hybridized to the array to identify species-specific polymorphism within one or more genes. We illustrate this type of array using 16S rDNA probes suitable for distinguishing between several salmonid pathogens. We also describe the use of microarrays for direct detection of either RNA or DNA without the aid of PCR, although the sensitivity of these systems currently limits their application for pathogen detection. Finally, microarrays can also be used to "fingerprint" bacterial isolates and they can be used to identify diagnostic markers suitable for developing new PCR-based detection assays. We illustrate this type of array for subtyping an important food-borne pathogen, Listeria monocytogenes. PMID:12654494

  7. IDENTIFYING AND MONITORING ENVIRONMENTAL TOXICITY USING CERIODAPHNIA MICROARRAYS - PHASE I

    EPA Science Inventory

    The current U.S. Environmental Protection Agency (EPA) SBIR solicitation states that “technology is needed to better identify and monitor sources of pollution and protect water quality.” Microarrays may be particularly well suited to identifying environmental toxic...

  8. Improved microarray methods for profiling the yeast knockout strain collection

    PubMed Central

    Yuan, Daniel S.; Pan, Xuewen; Ooi, Siew Loon; Peyser, Brian D.; Spencer, Forrest A.; Irizarry, Rafael A.; Boeke, Jef D.

    2005-01-01

    A remarkable feature of the Yeast Knockout strain collection is the presence of two unique 20mer TAG sequences in almost every strain. In principle, the relative abundances of strains in a complex mixture can be profiled swiftly and quantitatively by amplifying these sequences and hybridizing them to microarrays, but TAG microarrays have not been widely used. Here, we introduce a TAG microarray design with sophisticated controls and describe a robust method for hybridizing high concentrations of dye-labeled TAGs in single-stranded form. We also highlight the importance of avoiding PCR contamination and provide procedures for detection and eradication. Validation experiments using these methods yielded false positive (FP) and false negative (FN) rates for individual TAG detection of 3–6% and 15–18%, respectively. Analysis demonstrated that cross-hybridization was the chief source of FPs, while TAG amplification defects were the main cause of FNs. The materials, protocols, data and associated software described here comprise a suite of experimental resources that should facilitate the use of TAG microarrays for a wide variety of genetic screens. PMID:15994458

  9. Comparison of Comparative Genomic Hybridization Technologies across Microarray Platforms

    EPA Science Inventory

    In the 2007 Association of Biomolecular Resource Facilities (ABRF) Microarray Research Group (MARG) project, we analyzed HL-60 DNA with five platforms: Agilent, Affymetrix 500K, Affymetrix U133 Plus 2.0, Illumina, and RPCI 19K BAC arrays. Copy number variation (CNV) was analyzed ...

  10. Electrostatic readout of DNA microarrays with charged microspheres

    SciTech Connect

    Clack, Nathan G.; Salaita, Khalid; Groves, Jay T.

    2008-06-29

    DNA microarrays are used for gene-expression profiling, single-nucleotide polymorphism detection and disease diagnosis. A persistent challenge in this area is the lack of microarray screening technology suitable for integration into routine clinical care. In this paper, we describe a method for sensitive and label-free electrostatic readout of DNA or RNA hybridization on microarrays. The electrostatic properties of the microarray are measured from the position and motion of charged microspheres randomly dispersed over the surface. We demonstrate nondestructive electrostatic imaging with 10-μm lateral resolution over centimeter-length scales, which is four-orders of magnitude larger than that achievable with conventional scanning electrostatic force microscopy. Changes in surface charge density as a result of specific hybridization can be detected and quantified with 50-pM sensitivity, single base-pair mismatch selectivity and in the presence of complex background. Lastly, because the naked eye is sufficient to read out hybridization, this approach may facilitate broad application of multiplexed assays.

  11. Assessing Agreement between miRNA Microarray Platforms

    PubMed Central

    Bassani, Niccolò P.; Ambrogi, Federico; Biganzoli, Elia M.

    2014-01-01

    Over the last few years, miRNA microarray platforms have provided great insights into the biological mechanisms underlying the onset and development of several diseases. However, only a few studies have evaluated the concordance between different microarray platforms using methods that took into account measurement error in the data. In this work, we propose the use of a modified version of the Bland–Altman plot to assess agreement between microarray platforms. To this aim, two samples, one renal tumor cell line and a pool of 20 different human normal tissues, were profiled using three different miRNA platforms (Affymetrix, Agilent, Illumina) on triplicate arrays. Intra-platform reliability was assessed by calculating pair-wise concordance correlation coefficients (CCC) between technical replicates and overall concordance correlation coefficient (OCCC) with bootstrap percentile confidence intervals, which revealed moderate-to-good repeatability of all platforms for both samples. Modified Bland–Altman analysis revealed good patterns of concordance for Agilent and Illumina, whereas Affymetrix showed poor-to-moderate agreement for both samples considered. The proposed method is useful to assess agreement between array platforms by modifying the original Bland–Altman plot to let it account for measurement error and bias correction and can be used to assess patterns of concordance between other kinds of arrays other than miRNA microarrays.

  12. Exploiting fluorescence for multiplex immunoassays on protein microarrays

    NASA Astrophysics Data System (ADS)

    Herbáth, Melinda; Papp, Krisztián; Balogh, Andrea; Matkó, János; Prechl, József

    2014-09-01

    Protein microarray technology is becoming the method of choice for identifying protein interaction partners, detecting specific proteins, carbohydrates and lipids, or for characterizing protein interactions and serum antibodies in a massively parallel manner. Availability of the well-established instrumentation of DNA arrays and development of new fluorescent detection instruments promoted the spread of this technique. Fluorescent detection has the advantage of high sensitivity, specificity, simplicity and wide dynamic range required by most measurements. Fluorescence through specifically designed probes and an increasing variety of detection modes offers an excellent tool for such microarray platforms. Measuring for example the level of antibodies, their isotypes and/or antigen specificity simultaneously can offer more complex and comprehensive information about the investigated biological phenomenon, especially if we take into consideration that hundreds of samples can be measured in a single assay. Not only body fluids, but also cell lysates, extracted cellular components, and intact living cells can be analyzed on protein arrays for monitoring functional responses to printed samples on the surface. As a rapidly evolving area, protein microarray technology offers a great bulk of information and new depth of knowledge. These are the features that endow protein arrays with wide applicability and robust sample analyzing capability. On the whole, protein arrays are emerging new tools not just in proteomics, but glycomics, lipidomics, and are also important for immunological research. In this review we attempt to summarize the technical aspects of planar fluorescent microarray technology along with the description of its main immunological applications.

  13. Microtiter plate-based antibody microarrays for bacteria and toxins

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Research has focused on the development of rapid biosensor-based, high-throughput, and multiplexed detection of pathogenic bacteria in foods. Specifically, antibody microarrays in 96-well microtiter plates have been generated for the purpose of selective detection of Shiga toxin-producing E. coli (...

  14. Low-density microarray technologies for rapid human norovirus genotyping

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Human noroviruses cause up to 21 million cases of foodborne disease in the United States annually and are the most common cause of acute gastroenteritis in industrialized countries. To reduce the burden of foodborne disease associated with viruses, the use of low density DNA microarrays in conjuncti...

  15. Microarrays/DNA Chips for the Detection of Waterborne Pathogens.

    PubMed

    Vale, Filipa F

    2016-01-01

    DNA microarrays are useful for the simultaneous detection of microorganisms in water samples. Specific probes targeting waterborne pathogens are selected with bioinformatics tools, synthesized and spotted onto a DNA array. Here, the construction of a DNA chip for waterborne pathogen detection is described, including the processes of probe in silico selection, synthesis, validation, and data analysis. PMID:27460375

  16. Bulk segregant analysis using single nucleotide polymorphism microarrays

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Bulk segregant analysis using microarrays, and extreme array mapping have recently been used to rapidly identify genomic regions associated with phenotypes in multiple species. These experiments, however require the identification of single feature polymorphisms between the cross parents for each ne...

  17. Analysis of microarray experiments of gene expression profiling

    PubMed Central

    Tarca, Adi L.; Romero, Roberto; Draghici, Sorin

    2008-01-01

    The study of gene expression profiling of cells and tissue has become a major tool for discovery in medicine. Microarray experiments allow description of genome-wide expression changes in health and disease. The results of such experiments are expected to change the methods employed in the diagnosis and prognosis of disease in obstetrics and gynecology. Moreover, an unbiased and systematic study of gene expression profiling should allow the establishment of a new taxonomy of disease for obstetric and gynecologic syndromes. Thus, a new era is emerging in which reproductive processes and disorders could be characterized using molecular tools and fingerprinting. The design, analysis, and interpretation of microarray experiments require specialized knowledge that is not part of the standard curriculum of our discipline. This article describes the types of studies that can be conducted with microarray experiments (class comparison, class prediction, class discovery). We discuss key issues pertaining to experimental design, data preprocessing, and gene selection methods. Common types of data representation are illustrated. Potential pitfalls in the interpretation of microarray experiments, as well as the strengths and limitations of this technology, are highlighted. This article is intended to assist clinicians in appraising the quality of the scientific evidence now reported in the obstetric and gynecologic literature. PMID:16890548

  18. CONFIRMING MICROARRAY DATA--IS IT REALLY NECESSARY?

    EPA Science Inventory

    The generation of corroborative data has become a commonly used approach for ensuring the veracity of microarray data. Indeed, the need to conduct corroborative studies has now become official editorial policy for at least two journals, and several more are considering introducin...

  19. Carboxymethyl cellulose film as a substrate for microarray fabrication.

    PubMed

    Shlyapnikov, Yuri M; Shlyapnikova, Elena A; Morozov, Victor N

    2014-02-18

    Magnetic beads (MB) are widely used for quick and highly sensitive signal detection in microarray-based assays. However, this technique imposes stringent requirements for smoothness and adhesive properties of the surface, which most common substrates do not satisfy. We report here a new type of substrate for microarrays with a low adhesion to MB-thermally cross-linked carboxymethyl cellulose (CMC) film. This substrate can be readily fabricated on a conventional glass slide. A highly cross-linked CMC film (∼1 cross-link per monomer unit) possesses a surface smooth on a nanometer scale and a low adhesion to protein-coated MB, which partly originates from electrostatic repulsion of MB from negatively charged CMC surface. The efficiency of the CMC substrate is demonstrated hereby in fabrication of microarrays for the detection of three bacterial toxins: cholera toxin, staphylococcal enterotoxin A, and toxic shock syndrome toxin. The assay employing a primary antibodies arrayed on a CMC surface and detection of the bound bacterial toxins with a biotinylated secondary antibodies and streptavidin-coated MB resulted in a limits of detection as low as 0.1 ng/mL. The CMC-based microarrays demonstrated very high storage stability; their activity did not change after one year storage at room temperature. PMID:24446727

  20. USING MICROARRAY TECHNOLOGY TO OPTIMIZE ARTIFICIAL DIETS FOR BENEFICIAL INSECTS

    Technology Transfer Automated Retrieval System (TEKTRAN)

    An optimized artificial diet is key for the production of high quality beneficial insects at affordable cost. Using a Drosophila microarray chip with 7000 unigenes, several hundred dietary regulated genes were identified in Perillus bioculatus that fed on a suboptimal artificial diet. These dietary ...