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      The Gene Ontology Resource: 20 years and still GOing strong

      research-article
      The Gene Ontology Consortium
      Nucleic Acids Research
      Oxford University Press

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          Abstract

          The Gene Ontology resource (GO; http://geneontology.org) provides structured, computable knowledge regarding the functions of genes and gene products. Founded in 1998, GO has become widely adopted in the life sciences, and its contents are under continual improvement, both in quantity and in quality. Here, we report the major developments of the GO resource during the past two years. Each monthly release of the GO resource is now packaged and given a unique identifier (DOI), enabling GO-based analyses on a specific release to be reproduced in the future. The molecular function ontology has been refactored to better represent the overall activities of gene products, with a focus on transcription regulator activities. Quality assurance efforts have been ramped up to address potentially out-of-date or inaccurate annotations. New evidence codes for high-throughput experiments now enable users to filter out annotations obtained from these sources. GO-CAM, a new framework for representing gene function that is more expressive than standard GO annotations, has been released, and users can now explore the growing repository of these models. We also provide the ‘GO ribbon’ widget for visualizing GO annotations to a gene; the widget can be easily embedded in any web page.

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          The Reactome Pathway Knowledgebase

          Abstract The Reactome Knowledgebase (https://reactome.org) provides molecular details of signal transduction, transport, DNA replication, metabolism, and other cellular processes as an ordered network of molecular transformations—an extended version of a classic metabolic map, in a single consistent data model. Reactome functions both as an archive of biological processes and as a tool for discovering unexpected functional relationships in data such as gene expression profiles or somatic mutation catalogues from tumor cells. To support the continued brisk growth in the size and complexity of Reactome, we have implemented a graph database, improved performance of data analysis tools, and designed new data structures and strategies to boost diagram viewer performance. To make our website more accessible to human users, we have improved pathway display and navigation by implementing interactive Enhanced High Level Diagrams (EHLDs) with an associated icon library, and subpathway highlighting and zooming, in a simplified and reorganized web site with adaptive design. To encourage re-use of our content, we have enabled export of pathway diagrams as ‘PowerPoint’ files.
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            ChEBI in 2016: Improved services and an expanding collection of metabolites

            ChEBI is a database and ontology containing information about chemical entities of biological interest. It currently includes over 46 000 entries, each of which is classified within the ontology and assigned multiple annotations including (where relevant) a chemical structure, database cross-references, synonyms and literature citations. All content is freely available and can be accessed online at http://www.ebi.ac.uk/chebi. In this update paper, we describe recent improvements and additions to the ChEBI offering. We have substantially extended our collection of endogenous metabolites for several organisms including human, mouse, Escherichia coli and yeast. Our front-end has also been reworked and updated, improving the user experience, removing our dependency on Java applets in favour of embedded JavaScript components and moving from a monthly release update to a ‘live’ website. Programmatic access has been improved by the introduction of a library, libChEBI, in Java, Python and Matlab. Furthermore, we have added two new tools, namely an analysis tool, BiNChE, and a query tool for the ontology, OntoQuery.
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              Expansion of the Gene Ontology knowledgebase and resources

              The Gene Ontology (GO) is a comprehensive resource of computable knowledge regarding the functions of genes and gene products. As such, it is extensively used by the biomedical research community for the analysis of -omics and related data. Our continued focus is on improving the quality and utility of the GO resources, and we welcome and encourage input from researchers in all areas of biology. In this update, we summarize the current contents of the GO knowledgebase, and present several new features and improvements that have been made to the ontology, the annotations and the tools. Among the highlights are 1) developments that facilitate access to, and application of, the GO knowledgebase, and 2) extensions to the resource as well as increasing support for descriptions of causal models of biological systems and network biology. To learn more, visit http://geneontology.org/.
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                Author and article information

                Journal
                Nucleic Acids Res
                Nucleic Acids Res
                nar
                Nucleic Acids Research
                Oxford University Press
                0305-1048
                1362-4962
                08 January 2019
                05 November 2018
                05 November 2018
                : 47
                : Database issue , Database issue
                : D330-D338
                Author notes
                To whom correspondence should be addressed. Email: pdthomas@ 123456usc.edu

                Full list provided in Appendix.

                Article
                gky1055
                10.1093/nar/gky1055
                6323945
                30395331
                72426377-4ee0-4dc2-9f02-fbd7560b20f0
                © The Author(s) 2018. Published by Oxford University Press on behalf of Nucleic Acids Research.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 17 October 2018
                : 16 October 2018
                : 22 September 2018
                Page count
                Pages: 9
                Funding
                Funded by: National Human Genome Research Institute 10.13039/100000051
                Award ID: U41 HG02273
                Award ID: U41 HG001315
                Award ID: U24 HG002223
                Funded by: National Institute of General Medical Sciences 10.13039/100000057
                Award ID: GM064426
                Award ID: GM087371
                Funded by: National Institutes of Health 10.13039/100000002
                Award ID: GM089636
                Funded by: National Science Foundation 10.13039/100000001
                Award ID: 1565146
                Funded by: UK Medical Research Council 10.13039/501100000265
                Award ID: MR/N030117/1
                Funded by: National Human Genome Research Institute 10.13039/100000051
                Award ID: U41HG000739
                Funded by: Wellcome Trust 10.13039/100004440
                Award ID: 108433/Z/15/Z
                Funded by: Biotechnology and Biological Sciences Research Council 10.13039/501100000268
                Award ID: BB/N00521X/1
                Award ID: BB/N019172/1
                Award ID: BB/L024136/1
                Funded by: National Science Foundation 10.13039/100000001
                Award ID: 1458400
                Funded by: Gene Regulation Ensemble Effort for the Knowledge Commons
                Award ID: CA15205
                Funded by: Research Council of Norway 10.13039/501100005416
                Award ID: 247727
                Funded by: University College London 10.13039/501100000765
                Award ID: RG/13/5/30112
                Funded by: Parkinson's UK 10.13039/100008487
                Award ID: G-1307
                Funded by: Wellcome Trust 10.13039/100004440
                Award ID: 104967/Z/14/Z
                Funded by: National Human Genome Research Institute 10.13039/100000051
                Award ID: HG 000330
                Award ID: HG 002273
                Funded by: National Heart, Lung, and Blood Institute 10.13039/100000050
                Award ID: HL 64541
                Funded by: National Institutes of Health 10.13039/100000002
                Award ID: U24HG007822
                Funded by: National Human Genome Research Institute 10.13039/100000051
                Award ID: U41HG007822
                Award ID: U41HG002273
                Funded by: National Institute of General Medical Sciences 10.13039/100000057
                Award ID: R01GM080646
                Award ID: P20GM103446
                Award ID: U01GM120953
                Funded by: Biotechnology and Biological Sciences Research Council 10.13039/501100000268
                Award ID: BB/M011674/1
                Funded by: British Heart Foundation 10.13039/501100000274
                Award ID: RG/13/5/30112
                Funded by: National Human Genome Research Institute 10.13039/100000051
                Award ID: U24-HG002223
                Funded by: UK Medical Research Council 10.13039/501100000265
                Award ID: MR/L001220
                Funded by: UK Biotechnology and Biological Sciences Research Council 10.13039/501100000268
                Award ID: BB/K020080
                Funded by: National Human Genome Research Institute 10.13039/100000051
                Award ID: U41 HG002659
                Categories
                Database Issue

                Genetics
                Genetics

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