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      Genes2GO: A web application for querying gene sets for specific GO terms

      research-article
      1 , 1 , *
      Bioinformation
      Biomedical Informatics
      Gene sets, GO terms, Web server

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          Abstract

          Gene ontology annotations have become an essential resource for biological interpretations of experimental findings. The process of gathering basic annotation information in tables that link gene sets with specific gene ontology terms can be cumbersome, in particular if it requires above average computer skills or bioinformatics expertise. We have therefore developed Genes2GO, an intuitive R-based web application. Genes2GO uses the biomaRt package of Bioconductor in order to retrieve custom sets of gene ontology annotations for any list of genes from organisms covered by the Ensembl database. Genes2GO produces a binary matrix file, indicating for each gene the presence or absence of specific annotations for a gene. It should be noted that other GO tools do not offer this user-friendly access to annotations.

          Availability:

          Genes2GO is freely available and listed under http://www.semantic-systems-biology.org/tools/externaltools/

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          Most cited references5

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          Gene Ontology: tool for the unification of biology

          Genomic sequencing has made it clear that a large fraction of the genes specifying the core biological functions are shared by all eukaryotes. Knowledge of the biological role of such shared proteins in one organism can often be transferred to other organisms. The goal of the Gene Ontology Consortium is to produce a dynamic, controlled vocabulary that can be applied to all eukaryotes even as knowledge of gene and protein roles in cells is accumulating and changing. To this end, three independent ontologies accessible on the World-Wide Web (http://www.geneontology.org) are being constructed: biological process, molecular function and cellular component.
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            DAVID: Database for Annotation, Visualization, and Integrated Discovery.

            Functional annotation of differentially expressed genes is a necessary and critical step in the analysis of microarray data. The distributed nature of biological knowledge frequently requires researchers to navigate through numerous web-accessible databases gathering information one gene at a time. A more judicious approach is to provide query-based access to an integrated database that disseminates biologically rich information across large datasets and displays graphic summaries of functional information. Database for Annotation, Visualization, and Integrated Discovery (DAVID; http://www.david.niaid.nih.gov) addresses this need via four web-based analysis modules: 1) Annotation Tool - rapidly appends descriptive data from several public databases to lists of genes; 2) GoCharts - assigns genes to Gene Ontology functional categories based on user selected classifications and term specificity level; 3) KeggCharts - assigns genes to KEGG metabolic processes and enables users to view genes in the context of biochemical pathway maps; and 4) DomainCharts - groups genes according to PFAM conserved protein domains. Analysis results and graphical displays remain dynamically linked to primary data and external data repositories, thereby furnishing in-depth as well as broad-based data coverage. The functionality provided by DAVID accelerates the analysis of genome-scale datasets by facilitating the transition from data collection to biological meaning.
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              Is Open Access

              OLSVis: an animated, interactive visual browser for bio-ontologies

              Background More than one million terms from biomedical ontologies and controlled vocabularies are available through the Ontology Lookup Service (OLS). Although OLS provides ample possibility for querying and browsing terms, the visualization of parts of the ontology graphs is rather limited and inflexible. Results We created the OLSVis web application, a visualiser for browsing all ontologies available in the OLS database. OLSVis shows customisable subgraphs of the OLS ontologies. Subgraphs are animated via a real-time force-based layout algorithm which is fully interactive: each time the user makes a change, e.g. browsing to a new term, hiding, adding, or dragging terms, the algorithm performs smooth and only essential reorganisations of the graph. This assures an optimal viewing experience, because subsequent screen layouts are not grossly altered, and users can easily navigate through the graph. URL: http://ols.wordvis.com Conclusions The OLSVis web application provides a user-friendly tool to visualise ontologies from the OLS repository. It broadens the possibilities to investigate and select ontology subgraphs through a smooth visualisation method.
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                Author and article information

                Journal
                Bioinformation
                Bioinformation
                Bioinformation
                Bioinformation
                Biomedical Informatics
                0973-2063
                2016
                15 June 2016
                : 12
                : 3
                : 231-232
                Affiliations
                [1 ]Department of Biology, Norwegian University of Science and Technology (NTNU), Hogskoleringen 5, 7491 Trondheim, Norway
                Author notes
                Article
                97320630012231
                10.6026/97320630012231
                5267968
                bf70ca2e-a00e-4693-ac12-aa8157e79da1
                © 2016 Biomedical Informatics

                This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License.

                History
                : 30 May 2016
                : 10 June 2016
                Categories
                Web Server

                Bioinformatics & Computational biology
                gene sets,go terms,web server
                Bioinformatics & Computational biology
                gene sets, go terms, web server

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