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      The European Bioinformatics Institute in 2017: data coordination and integration

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          Abstract

          The European Bioinformatics Institute (EMBL-EBI) supports life-science research throughout the world by providing open data, open-source software and analytical tools, and technical infrastructure ( https://www.ebi.ac.uk). We accommodate an increasingly diverse range of data types and integrate them, so that biologists in all disciplines can explore life in ever-increasing detail. We maintain over 40 data resources, many of which are run collaboratively with partners in 16 countries ( https://www.ebi.ac.uk/services). Submissions continue to increase exponentially: our data storage has doubled in less than two years to 120 petabytes. Recent advances in cellular imaging and single-cell sequencing techniques are generating a vast amount of high-dimensional data, bringing to light new cell types and new perspectives on anatomy. Accordingly, one of our main focus areas is integrating high-quality information from bioimaging, biobanking and other types of molecular data. This is reflected in our deep involvement in Open Targets, stewarding of plant phenotyping standards (MIAPPE) and partnership in the Human Cell Atlas data coordination platform, as well as the 2017 launch of the Omics Discovery Index. This update gives a birds-eye view of EMBL-EBI’s approach to data integration and service development as genomics begins to enter the clinic.

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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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            Ensembl 2018

            Abstract The Ensembl project has been aggregating, processing, integrating and redistributing genomic datasets since the initial releases of the draft human genome, with the aim of accelerating genomics research through rapid open distribution of public data. Large amounts of raw data are thus transformed into knowledge, which is made available via a multitude of channels, in particular our browser (http://www.ensembl.org). Over time, we have expanded in multiple directions. First, our resources describe multiple fields of genomics, in particular gene annotation, comparative genomics, genetics and epigenomics. Second, we cover a growing number of genome assemblies; Ensembl Release 90 contains exactly 100. Third, our databases feed simultaneously into an array of services designed around different use cases, ranging from quick browsing to genome-wide bioinformatic analysis. We present here the latest developments of the Ensembl project, with a focus on managing an increasing number of assemblies, supporting efforts in genome interpretation and improving our browser.
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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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                Author and article information

                Journal
                Nucleic Acids Res
                Nucleic Acids Res
                nar
                Nucleic Acids Research
                Oxford University Press
                0305-1048
                1362-4962
                04 January 2018
                25 November 2017
                25 November 2017
                : 46
                : Database issue , Database issue
                : D21-D29
                Affiliations
                European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
                Author notes
                To whom correspondence should be addressed. Tel: +44 1223 494 665; Fax: +44 1223 494 468; Email: mary@ 123456ebi.ac.uk
                Author information
                http://orcid.org/0000-0002-4145-8048
                Article
                gkx1154
                10.1093/nar/gkx1154
                5753251
                29186510
                25af32f2-9728-4c3f-a615-adacaf11c73b
                © The Author(s) 2017. 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
                : 20 November 2017
                : 30 October 2017
                : 13 October 2017
                Page count
                Pages: 9
                Categories
                Database Issue

                Genetics
                Genetics

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