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      Using the Gene Ontology to Annotate Key Players in Parkinson’s Disease

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          Abstract

          The Gene Ontology (GO) is widely recognised as the gold standard bioinformatics resource for summarizing functional knowledge of gene products in a consistent and computable, information-rich language. GO describes cellular and organismal processes across all species, yet until now there has been a considerable gene annotation deficit within the neurological and immunological domains, both of which are relevant to Parkinson’s disease. Here we introduce the Parkinson’s disease GO Annotation Project, funded by Parkinson’s UK and supported by the GO Consortium, which is addressing this deficit by providing GO annotation to Parkinson’s-relevant human gene products, principally through expert literature curation. We discuss the steps taken to prioritise proteins, publications and cellular processes for annotation, examples of how GO annotations capture Parkinson’s-relevant information, and the advantages that a topic-focused annotation approach offers to users. Building on the existing GO resource, this project collates a vast amount of Parkinson’s-relevant literature into a set of high-quality annotations to be utilized by the research community.

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          Most cited references42

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          Cytoscape: a software environment for integrated models of biomolecular interaction networks.

          Cytoscape is an open source software project for integrating biomolecular interaction networks with high-throughput expression data and other molecular states into a unified conceptual framework. Although applicable to any system of molecular components and interactions, Cytoscape is most powerful when used in conjunction with large databases of protein-protein, protein-DNA, and genetic interactions that are increasingly available for humans and model organisms. Cytoscape's software Core provides basic functionality to layout and query the network; to visually integrate the network with expression profiles, phenotypes, and other molecular states; and to link the network to databases of functional annotations. The Core is extensible through a straightforward plug-in architecture, allowing rapid development of additional computational analyses and features. Several case studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in gene expression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.
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            Gene Ontology Consortium: going forward

            The Gene Ontology (GO; http://www.geneontology.org) is a community-based bioinformatics resource that supplies information about gene product function using ontologies to represent biological knowledge. Here we describe improvements and expansions to several branches of the ontology, as well as updates that have allowed us to more efficiently disseminate the GO and capture feedback from the research community. The Gene Ontology Consortium (GOC) has expanded areas of the ontology such as cilia-related terms, cell-cycle terms and multicellular organism processes. We have also implemented new tools for generating ontology terms based on a set of logical rules making use of templates, and we have made efforts to increase our use of logical definitions. The GOC has a new and improved web site summarizing new developments and documentation, serving as a portal to GO data. Users can perform GO enrichment analysis, and search the GO for terms, annotations to gene products, and associated metadata across multiple species using the all-new AmiGO 2 browser. We encourage and welcome the input of the research community in all biological areas in our continued effort to improve the Gene Ontology.
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              The IntAct molecular interaction database in 2012

              IntAct is an open-source, open data molecular interaction database populated by data either curated from the literature or from direct data depositions. Two levels of curation are now available within the database, with both IMEx-level annotation and less detailed MIMIx-compatible entries currently supported. As from September 2011, IntAct contains approximately 275 000 curated binary interaction evidences from over 5000 publications. The IntAct website has been improved to enhance the search process and in particular the graphical display of the results. New data download formats are also available, which will facilitate the inclusion of IntAct's data in the Semantic Web. IntAct is an active contributor to the IMEx consortium (http://www.imexconsortium.org). IntAct source code and data are freely available at http://www.ebi.ac.uk/intact.
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                Author and article information

                Contributors
                +44 (0)20-7679-6965 , rebecca.foulger@ucl.ac.uk
                p.denny@ucl.ac.uk
                j.hardy@ucl.ac.uk
                martin@ebi.ac.uk
                tonys@ebi.ac.uk
                r.lovering@ucl.ac.uk
                Journal
                Neuroinformatics
                Neuroinformatics
                Neuroinformatics
                Springer US (New York )
                1539-2791
                1559-0089
                29 January 2016
                29 January 2016
                2016
                : 14
                : 297-304
                Affiliations
                [ ]Centre for Cardiovascular Genetics, Institute of Cardiovascular Science, University College London, London, UK
                [ ]Department of Molecular Neuroscience, Institute of Neurology, University College London, London, UK
                [ ]European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridgeshire UK
                Article
                9293
                10.1007/s12021-015-9293-2
                4896971
                26825309
                8f1bc59c-abad-4b49-a7f8-abcff5d1cf69
                © The Author(s) 2016

                Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

                History
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100000304, Parkinson's UK (GB);
                Award ID: G-1307
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100000274, British Heart Foundation (GB);
                Award ID: RG/13/5/30112
                Award Recipient :
                Funded by: Wellcome Trust/MRC Joint Call in Neurodegeneration award
                Award ID: WT089698
                Award Recipient :
                Funded by: M.J.Fox Pritzker Prize
                Funded by: FundRef http://dx.doi.org/10.13039/100000051, National Human Genome Research Institute (US);
                Award ID: U41HG002273
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100000304, Parkinson's UK (GB);
                Award ID: G-1307
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100000304, Parkinson's UK (GB);
                Award ID: G-1307
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100000274, British Heart Foundation (GB);
                Award ID: RG/13/5/30112
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100000304, Parkinson's UK;
                Award ID: G-1307
                Award ID: G-1307
                Award ID: G-1307
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100000274, British Heart Foundation;
                Award ID: RG/13/5/30112
                Award Recipient :
                Categories
                Original Article
                Custom metadata
                © Springer Science+Business Media New York 2016

                Neurosciences
                annotation, database,functional annotation,gene ontology,high-throughput analysis,parkinson’s disease

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