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      Improving Interpretation of Cardiac Phenotypes and Enhancing Discovery With Expanded Knowledge in the Gene Ontology

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          Abstract

          Supplemental Digital Content is available in the text.

          Abstract

          Background:

          A systems biology approach to cardiac physiology requires a comprehensive representation of how coordinated processes operate in the heart, as well as the ability to interpret relevant transcriptomic and proteomic experiments. The Gene Ontology (GO) Consortium provides structured, controlled vocabularies of biological terms that can be used to summarize and analyze functional knowledge for gene products.

          Methods and Results:

          In this study, we created a computational resource to facilitate genetic studies of cardiac physiology by integrating literature curation with attention to an improved and expanded ontological representation of heart processes in the Gene Ontology. As a result, the Gene Ontology now contains terms that comprehensively describe the roles of proteins in cardiac muscle cell action potential, electrical coupling, and the transmission of the electrical impulse from the sinoatrial node to the ventricles. Evaluating the effectiveness of this approach to inform data analysis demonstrated that Gene Ontology annotations, analyzed within an expanded ontological context of heart processes, can help to identify candidate genes associated with arrhythmic disease risk loci.

          Conclusions:

          We determined that a combination of curation and ontology development for heart-specific genes and processes supports the identification and downstream analysis of genes responsible for the spread of the cardiac action potential through the heart. Annotating these genes and processes in a structured format facilitates data analysis and supports effective retrieval of gene-centric information about cardiac defects.

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          Most cited references51

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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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            Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources.

            DAVID bioinformatics resources consists of an integrated biological knowledgebase and analytic tools aimed at systematically extracting biological meaning from large gene/protein lists. This protocol explains how to use DAVID, a high-throughput and integrated data-mining environment, to analyze gene lists derived from high-throughput genomic experiments. The procedure first requires uploading a gene list containing any number of common gene identifiers followed by analysis using one or more text and pathway-mining tools such as gene functional classification, functional annotation chart or clustering and functional annotation table. By following this protocol, investigators are able to gain an in-depth understanding of the biological themes in lists of genes that are enriched in genome-scale studies.
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              Cytoscape 2.8: new features for data integration and network visualization

              Summary: Cytoscape is a popular bioinformatics package for biological network visualization and data integration. Version 2.8 introduces two powerful new features—Custom Node Graphics and Attribute Equations—which can be used jointly to greatly enhance Cytoscape's data integration and visualization capabilities. Custom Node Graphics allow an image to be projected onto a node, including images generated dynamically or at remote locations. Attribute Equations provide Cytoscape with spreadsheet-like functionality in which the value of an attribute is computed dynamically as a function of other attributes and network properties. Availability and implementation: Cytoscape is a desktop Java application released under the Library Gnu Public License (LGPL). Binary install bundles and source code for Cytoscape 2.8 are available for download from http://cytoscape.org. Contact: msmoot@ucsd.edu
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                Author and article information

                Journal
                Circ Cardiovasc Genet
                Circ Cardiovasc Genet
                HCG
                Circulation. Cardiovascular Genetics
                Lippincott Williams & Wilkins
                1942-325X
                1942-3268
                February 2018
                13 February 2018
                : 11
                : 2
                : e001813
                Affiliations
                From the Institute of Cardiovascular Science (R.C.L., V.K.K., R.E.F., N.H.C., R.P.H., P.J.T., P.D.L., P.M.E., L.C.) and Metabolism and Experimental Therapeutics, Division of Medicine (R.B.), University College London, United Kingdom; European Bioinformatics Institute (EMBL-EBI), European Molecular Biology Laboratory, Hinxton, United Kingdom (P.R., D.O.-S.); Gene Ontology Consortium (P.R., T.Z.B., D.O.-S., J.A.B., D.P.H.); The Zebrafish Model Organism Database, University of Oregon, Eugene (D.G.H.); Rat Genome Database, Human Molecular Genetics Center, Medical College of Wisconsin, Milwaukee (S.J.F.L.); Arabidopsis Information Resource, Phoenix Bioinformatics, Fremont, CA (T.Z.B.); FlyBase, University of Cambridge, United Kingdom (S.T.); Mouse Genome Informatics, The Jackson Laboratory, Bar Harbor, ME (J.A.B., D.P.H.); Oxbridge BHF Centre of Regenerative Medicine, Department of Physiology, Anatomy and Genetics, University of Oxford, United Kingdom (P.R.R.); and William Harvey Heart Centre, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, United Kingdom (A.T.).
                Author notes
                Correspondence to: Ruth C. Lovering, PhD, Functional Gene Annotation, Institute of Cardiovascular Genetics, University College London, Rayne Bldg, 5 University St, London WC1E 6JF, United Kingdom. E-mail r.lovering@ 123456ucl.ac.uk
                Article
                00010
                10.1161/CIRCGEN.117.001813
                5821137
                29440116
                f4c0fa7f-d50b-435f-87b4-6e5a4004beb0
                © 2018 The Authors.

                Circulation: Genomic and Precision Medicine is published on behalf of the American Heart Association, Inc., by Wolters Kluwer Health, Inc. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution, and reproduction in any medium, provided that the original work is properly cited.

                History
                : 4 May 2017
                : 11 January 2018
                Categories
                10001
                10003
                10085
                Original Articles
                Custom metadata
                TRUE

                arrhythmias, cardiac,data curation,electrophysiology,gene ontology,genetics,transcriptome

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