For Publishers
DiscoveryMetadataPeer reviewHostingPublishing
For Researchers
JoinPublishReviewCollect
Register
Blog
About
Search
Advanced search
My ScienceOpen
Search
For Publishers
For Researchers
Blog
About
47
views
5
references
 Top references
cited by
733
    
0 reviews
 Review
0
comments
 Comment
0
recommends
+1 Recommend
0 collections
    0
    shares
      121
      similar
       All similar
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      The Reactome Pathway Knowledgebase

      research-article

      Read this article at

      ScienceOpenPublisherPMC
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          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.

          Related collections

          Most cited references5

          • Record: found
          • Abstract: found
          • Article: not found

          The Systems Biology Graphical Notation.

          Nicolas Le Novère, Michael Hucka, Huaiyu Mi … (2009)
          Circuit diagrams and Unified Modeling Language diagrams are just two examples of standard visual languages that help accelerate work by promoting regularity, removing ambiguity and enabling software tool support for communication of complex information. Ironically, despite having one of the highest ratios of graphical to textual information, biology still lacks standard graphical notations. The recent deluge of biological knowledge makes addressing this deficit a pressing concern. Toward this goal, we present the Systems Biology Graphical Notation (SBGN), a visual language developed by a community of biochemists, modelers and computer scientists. SBGN consists of three complementary languages: process diagram, entity relationship diagram and activity flow diagram. Together they enable scientists to represent networks of biochemical interactions in a standard, unambiguous way. We believe that SBGN will foster efficient and accurate representation, visualization, storage, exchange and reuse of information on all kinds of biological knowledge, from gene regulation, to metabolism, to cellular signaling.
          Article 0 comments Cited 344 times – based on 0 reviews     Review now
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Global functional profiling of gene expression.

            Sorin Drăghici, Purvesh Khatri, Rui Martins … (2003)
            The typical result of a microarray experiment is a list of tens or hundreds of genes found to be differentially regulated in the condition under study. Independent of the methods used to select these genes, the common task faced by any researcher is to translate these lists of genes into a better understanding of the biological phenomena involved. Currently, this is done through a tedious combination of searches through the literature and a number of public databases. We developed Onto-Express (OE) as a novel tool able to automatically translate such lists of differentially regulated genes into functional profiles characterizing the impact of the condition studied. OE constructs functional profiles (using Gene Ontology terms) for the following categories: biochemical function, biological process, cellular role, cellular component, molecular function, and chromosome location. Statistical significance values are calculated for each category. We demonstrate the validity and the utility of this comprehensive global analysis of gene function by analyzing two breast cancer datasets from two separate laboratories. OE was able to identify correctly all biological processes postulated by the original authors, as well as discover novel relevant mechanisms.
            Article 0 comments Cited 180 times – based on 0 reviews     Review now
              Bookmark
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              Updates in Rhea – an expert curated resource of biochemical reactions

              Anne Morgat, Thierry Lombardot, Kristian Axelsen … (2016)
              Rhea (http://www.rhea-db.org) is a comprehensive and non-redundant resource of expert-curated biochemical reactions designed for the functional annotation of enzymes and the description of metabolic networks. Rhea describes enzyme-catalyzed reactions covering the IUBMB Enzyme Nomenclature list as well as additional reactions, including spontaneously occurring reactions, using entities from the ChEBI (Chemical Entities of Biological Interest) ontology of small molecules. Here we describe developments in Rhea since our last report in the database issue of Nucleic Acids Research. These include the first implementation of a simple hierarchical classification of reactions, improved coverage of the IUBMB Enzyme Nomenclature list and additional reactions through continuing expert curation, and the development of a new website to serve this improved dataset.
              Article 0 comments Cited 28 times – based on 0 reviews     Review now
                Bookmark
                All references

                Author and article information

                Journal
                Journal ID (nlm-ta): Nucleic Acids Res
                Journal ID (iso-abbrev): Nucleic Acids Res
                Journal ID (publisher-id): nar
                Title: Nucleic Acids Research
                Publisher: Oxford University Press
                ISSN (Print): 0305-1048
                ISSN (Electronic): 1362-4962
                Publication date (Print): 04 January 2018
                Publication date (Electronic): 14 November 2017
                Publication date PMC-release: 14 November 2017
                Volume: 46
                Issue: Database issue , Database issue
                Pages: D649-D655
                Affiliations
                European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
                Open Targets, Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
                NYU School of Medicine, New York, NY 10016, USA
                Ontario Institute for Cancer Research, Toronto, ON, M5G 0A3, Canada
                College of Pharmacy and Health Sciences, St. John's University, Queens, NY 11439, USA
                Oregon Health Sciences University, Portland, OR 97239, USA
                Department of Molecular Genetics, University of Toronto, Toronto, ON M5S 1A1, Canada
                National Center for Protein Sciences, Beijing, China
                Author notes
                To whom correspondence should be addressed. Tel: +1 212 263 5779; Fax: +1 212 263 8166; Email: deustp01@ 123456med.nyu.edu . Correspondence may also be addressed to Henning Hermjakob. Tel: +44 1223 494 671; Email: hhe@ 123456ebi.ac.uk . Correspondence may also be addressed to Lincoln Stein. Tel: +1 416 673 8514; Email: Lincoln.Stein@ 123456oicr.on.ca . Correspondence may also be addressed to Guanming Wu. Tel: +1 503 494 4502; Fax: +1 503 346 6815; Email: wug@ 123456ohsu.edu

                These authors contributed equally to this work as first authors.

                Author information
                http://orcid.org/0000-0002-3288-8599
                http://orcid.org/0000-0002-5494-626X
                Article
                Publisher ID: gkx1132
                DOI: 10.1093/nar/gkx1132
                PMC ID: 5753187
                PubMed ID: 29145629
                SO-VID: 2a657e43-67ed-4577-a3da-dd7b77ce25cf
                Copyright © © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.
                License:

                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
                Date accepted : 26 October 2017
                Date revision received : 20 October 2017
                Date received : 07 October 2017
                Page count
                Pages: 7
                Categories
                Subject: Database Issue

                ScienceOpen disciplines: Genetics
                Data availability:
                ScienceOpen disciplines: Genetics

                Comments

                Comment on this article

                scite_

                Similar content121

                See all similar

                Cited by1,157

                See all cited by

                Most referenced authors616

                See all reference authors