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      FlyBase: updates to the Drosophila melanogaster knowledge base

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          Abstract

          FlyBase (flybase.org) is an essential online database for researchers using Drosophila melanogaster as a model organism, facilitating access to a diverse array of information that includes genetic, molecular, genomic and reagent resources. Here, we describe the introduction of several new features at FlyBase, including Pathway Reports, paralog information, disease models based on orthology, customizable tables within reports and overview displays (‘ribbons’) of expression and disease data. We also describe a variety of recent important updates, including incorporation of a developmental proteome, upgrades to the GAL4 search tab, additional Experimental Tool Reports, migration to JBrowse for genome browsing and improvements to batch queries/downloads and the Fast-Track Your Paper tool.

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          Most cited references36

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          UniProt: a worldwide hub of protein knowledge

          (2018)
          Abstract The UniProt Knowledgebase is a collection of sequences and annotations for over 120 million proteins across all branches of life. Detailed annotations extracted from the literature by expert curators have been collected for over half a million of these proteins. These annotations are supplemented by annotations provided by rule based automated systems, and those imported from other resources. In this article we describe significant updates that we have made over the last 2 years to the resource. We have greatly expanded the number of Reference Proteomes that we provide and in particular we have focussed on improving the number of viral Reference Proteomes. The UniProt website has been augmented with new data visualizations for the subcellular localization of proteins as well as their structure and interactions. UniProt resources are available under a CC-BY (4.0) license via the web at https://www.uniprot.org/.
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            KEGG: new perspectives on genomes, pathways, diseases and drugs

            KEGG (http://www.kegg.jp/ or http://www.genome.jp/kegg/) is an encyclopedia of genes and genomes. Assigning functional meanings to genes and genomes both at the molecular and higher levels is the primary objective of the KEGG database project. Molecular-level functions are stored in the KO (KEGG Orthology) database, where each KO is defined as a functional ortholog of genes and proteins. Higher-level functions are represented by networks of molecular interactions, reactions and relations in the forms of KEGG pathway maps, BRITE hierarchies and KEGG modules. In the past the KO database was developed for the purpose of defining nodes of molecular networks, but now the content has been expanded and the quality improved irrespective of whether or not the KOs appear in the three molecular network databases. The newly introduced addendum category of the GENES database is a collection of individual proteins whose functions are experimentally characterized and from which an increasing number of KOs are defined. Furthermore, the DISEASE and DRUG databases have been improved by systematic analysis of drug labels for better integration of diseases and drugs with the KEGG molecular networks. KEGG is moving towards becoming a comprehensive knowledge base for both functional interpretation and practical application of genomic information.
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              The Gene Ontology Resource: 20 years and still GOing strong

              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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                Author and article information

                Contributors
                Journal
                Nucleic Acids Res
                Nucleic Acids Res
                nar
                Nucleic Acids Research
                Oxford University Press
                0305-1048
                1362-4962
                08 January 2021
                21 November 2020
                21 November 2020
                : 49
                : D1
                : D899-D907
                Affiliations
                Department of Physiology, Development and Neuroscience, University of Cambridge , Downing Street, Cambridge CB2 3DY, UK
                Department of Physiology, Development and Neuroscience, University of Cambridge , Downing Street, Cambridge CB2 3DY, UK
                Department of Physiology, Development and Neuroscience, University of Cambridge , Downing Street, Cambridge CB2 3DY, UK
                Department of Physiology, Development and Neuroscience, University of Cambridge , Downing Street, Cambridge CB2 3DY, UK
                The Biological Laboratories, Harvard University , 16 Divinity Avenue, Cambridge, MA 02138, USA
                Department of Physiology, Development and Neuroscience, University of Cambridge , Downing Street, Cambridge CB2 3DY, UK
                Department of Biology, Indiana University , Bloomington, IN 47405, USA
                The Biological Laboratories, Harvard University , 16 Divinity Avenue, Cambridge, MA 02138, USA
                Department of Physiology, Development and Neuroscience, University of Cambridge , Downing Street, Cambridge CB2 3DY, UK
                Department of Biology, Indiana University , Bloomington, IN 47405, USA
                The Biological Laboratories, Harvard University , 16 Divinity Avenue, Cambridge, MA 02138, USA
                Department of Biology, Indiana University , Bloomington, IN 47405, USA
                Author notes
                To whom correspondence should be addressed. Tel: +44 1223333865; Email: al806@ 123456cam.ac.uk

                The members of the FlyBase Consortium are listed in the Acknowledgements.

                Author information
                http://orcid.org/0000-0003-4970-5901
                http://orcid.org/0000-0003-2759-266X
                http://orcid.org/0000-0003-3212-6364
                http://orcid.org/0000-0002-6700-3797
                Article
                gkaa1026
                10.1093/nar/gkaa1026
                7779046
                33219682
                f847ba51-4909-43f2-b473-7af87fb81a91
                © The Author(s) 2020. 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
                : 22 October 2020
                : 13 October 2020
                : 15 September 2020
                Page count
                Pages: 9
                Funding
                Funded by: National Institutes of Health, DOI 10.13039/100000002;
                Funded by: National Human Genome Research Institute, DOI 10.13039/100000051;
                Award ID: U41HG000739
                Funded by: Medical Research Council, DOI 10.13039/501100000265;
                Award ID: MR/N030117/1
                Funded by: UKRI Open Access Block;
                Categories
                AcademicSubjects/SCI00010
                Database Issue

                Genetics
                Genetics

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