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      Cytoscape.js: a graph theory library for visualisation and analysis

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          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

          Summary: Cytoscape.js is an open-source JavaScript-based graph library. Its most common use case is as a visualization software component, so it can be used to render interactive graphs in a web browser. It also can be used in a headless manner, useful for graph operations on a server, such as Node.js.

          Availability and implementation: Cytoscape.js is implemented in JavaScript. Documentation, downloads and source code are available at http://js.cytoscape.org.

          Contact: gary.bader@ 123456utoronto.ca

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          Cytoscape Web: an interactive web-based network browser

          Christian T. Lopes, Max Franz, Farzana Kazi … (2010)
          Summary: Cytoscape Web is a web-based network visualization tool–modeled after Cytoscape–which is open source, interactive, customizable and easily integrated into web sites. Multiple file exchange formats can be used to load data into Cytoscape Web, including GraphML, XGMML and SIF. Availability and Implementation: Cytoscape Web is implemented in Flex/ActionScript with a JavaScript API and is freely available at http://cytoscapeweb.cytoscape.org/ Contact: gary.bader@utoronto.ca Supplementary information: Supplementary data are available at Bioinformatics online.
          Article 0 comments Cited 365 times – based on 0 reviews     Review now
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            Saccharomyces genome database provides new regulation data

            Maria Costanzo, Stacia R. Engel, Edith Wong … (2013)
            The Saccharomyces Genome Database (SGD; http://www.yeastgenome.org) is the community resource for genomic, gene and protein information about the budding yeast Saccharomyces cerevisiae, containing a variety of functional information about each yeast gene and gene product. We have recently added regulatory information to SGD and present it on a new tabbed section of the Locus Summary entitled ‘Regulation’. We are compiling transcriptional regulator–target gene relationships, which are curated from the literature at SGD or imported, with permission, from the YEASTRACT database. For nearly every S. cerevisiae gene, the Regulation page displays a table of annotations showing the regulators of that gene, and a graphical visualization of its regulatory network. For genes whose products act as transcription factors, the Regulation page also shows a table of their target genes, accompanied by a Gene Ontology enrichment analysis of the biological processes in which those genes participate. We additionally synthesize information from the literature for each transcription factor in a free-text Regulation Summary, and provide other information relevant to its regulatory function, such as DNA binding site motifs and protein domains. All of the regulation data are available for querying, analysis and download via YeastMine, the InterMine-based data warehouse system in use at SGD.
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              The BioJS article collection of open source components for biological data visualisation

              Manuel Corpas (2014)
              Data-driven research has gained momentum in the life sciences. Visualisation of these data is essential for quick generation of hypotheses and their translation into useful knowledge. BioJS is a new proposed standard for JavaScript-based components to visualise biological data. BioJS is an open source community project that to date provides 39 different components contributed by a global community. Here, we present the BioJS F1000Research collection series. A total of 12 components and a project status article are published in bulk. This collection does not intend to be an all-encompassing, comprehensive source of BioJS articles, but an initial set; future submissions from BioJS contributors are welcome.
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                Author and article information

                Journal
                Journal ID (nlm-ta): Bioinformatics
                Journal ID (iso-abbrev): Bioinformatics
                Journal ID (publisher-id): bioinformatics
                Journal ID (hwp): bioinfo
                Title: Bioinformatics
                Publisher: Oxford University Press
                ISSN (Print): 1367-4803
                ISSN (Electronic): 1367-4811
                Publication date (Print): 15 January 2016
                Publication date (Electronic): 28 September 2015
                Publication date PMC-release: 28 September 2015
                Volume: 32
                Issue: 2
                Pages: 309-311
                Affiliations
                The Donnelly Centre, University of Toronto, Toronto, ON M5S 3E1, Canada
                Author notes
                *To whom correspondence should be addressed.

                Associate Editor: Jonathan Wren

                Article
                Publisher ID: btv557
                DOI: 10.1093/bioinformatics/btv557
                PMC ID: 4708103
                PubMed ID: 26415722
                SO-VID: af115d70-0e00-4e3f-ba78-6882c6ee0c02
                Copyright © © The Author 2015. Published by Oxford University Press.
                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 received : 29 May 2015
                Date revision received : 10 August 2015
                Date accepted : 20 September 2015
                Page count
                Pages: 3
                Categories
                Subject: Applications Notes
                Subject: Data and Text Mining

                ScienceOpen disciplines: Bioinformatics & Computational biology
                Data availability:
                ScienceOpen disciplines: Bioinformatics & Computational biology

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