SCODE: A Cytoscape app for supervised complex detection in protein-protein interaction graphs

Protein complexes are groups of interacting proteins unified by a common biological function. Identifying complexes amid a network of thousands of interacting proteins poses a difficult computational challenge. Traditional approaches to this problem rely on clique-like topography in order to identif...

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Bibliographic Details
Published in:F1000 research 2016, Vol.5, p.1699
Main Authors: Mohamed, Sarah, Janus, Nick, Qi, Yanjun
Format: Article
Language:English
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Summary:Protein complexes are groups of interacting proteins unified by a common biological function. Identifying complexes amid a network of thousands of interacting proteins poses a difficult computational challenge. Traditional approaches to this problem rely on clique-like topography in order to identify complexes. Supervised learning is an alternative approach that leverages real-valued data in order to extract the features of protein complexes and identify candidates that do not conform to traditional, dense clique structures. SCODE (Supervised Complex Detection), an application for the Cytoscape App Store, implements a supervised learning algorithm for the detection of protein complexes in protein-protein interaction networks.
ISSN:2046-1402
2046-1402
DOI:10.12688/f1000research.9184.1