Literature DB >> 25527096

The Cyni framework for network inference in Cytoscape.

Oriol Guitart-Pla1, Manjunath Kustagi1, Frank Rügheimer1, Andrea Califano1, Benno Schwikowski1.   

Abstract

MOTIVATION: Research on methods for the inference of networks from biological data is making significant advances, but the adoption of network inference in biomedical research practice is lagging behind. Here, we present Cyni, an open-source 'fill-in-the-algorithm' framework that provides common network inference functionality and user interface elements. Cyni allows the rapid transformation of Java-based network inference prototypes into apps of the popular open-source Cytoscape network analysis and visualization ecosystem. Merely placing the resulting app in the Cytoscape App Store makes the method accessible to a worldwide community of biomedical researchers by mouse click. In a case study, we illustrate the transformation of an ARACNE implementation into a Cytoscape app.
AVAILABILITY AND IMPLEMENTATION: Cyni, its apps, user guides, documentation and sample code are available from the Cytoscape App Store http://apps.cytoscape.org/apps/cynitoolbox CONTACT: benno.schwikowski@pasteur.fr.
© The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

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Year:  2014        PMID: 25527096      PMCID: PMC4410647          DOI: 10.1093/bioinformatics/btu812

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  9 in total

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  9 in total
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Review 7.  Leveraging User-Friendly Network Approaches to Extract Knowledge From High-Throughput Omics Datasets.

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  7 in total

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