SLiMScape: a protein short linear motif analysis plugin for Cytoscape.

BMC Bioinformatics

UCD Conway, Institute of Biomolecular and Biomedical Sciences, University College Dublin, Dublin, Ireland.

Published: July 2013

AI Article Synopsis

  • SLiMScape is a Cytoscape plugin designed for discovering and visualizing short linear motifs within protein interaction networks.
  • It allows users to conduct both new motif discovery and searches for known motifs while utilizing Cytoscape's visualization capabilities for easier interpretation of data.
  • By automatically retrieving protein domains and displaying motif distributions, SLiMScape enhances the analysis of protein interactions and aids in identifying novel motifs.

Article Abstract

Background: Computational protein short linear motif discovery can use protein interaction information to search for motifs among proteins which share a common interactor. Cytoscape provides a visual interface for protein networks but there is no streamlined way to rapidly visualize motifs in a network of proteins, or to integrate computational discovery with such visualizations.

Results: We present SLiMScape, a Cytoscape plugin, which enables both de novo motif discovery and searches for instances of known motifs. Data is presented using Cytoscape's visualization features thus providing an intuitive interface for interpreting results. The distribution of discovered or user-defined motifs may be selectively displayed and the distribution of protein domains may be viewed simultaneously. To facilitate this SLiMScape automatically retrieves domains for each protein.

Conclusion: SLiMScape provides a platform for performing short linear motif analyses of protein interaction networks by integrating motif discovery and search tools in a network visualization environment. This significantly aids in the discovery of novel short linear motifs and in visualizing the distribution of known motifs.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3750528PMC
http://dx.doi.org/10.1186/1471-2105-14-224DOI Listing

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