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CytoGTA: a cytoscape plugin for identifying discriminative subnetwork markers using a game theoretic approach

Farahmand, S ; Sharif University of Technology

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  1. Type of Document: Article
  2. DOI: 10.1371/journal.pone.0185016
  3. Abstract:
  4. In recent years, analyzing genome-wide expression profiles to find genetic markers has received much attention as a challenging field of research aiming at unveiling biological mechanisms behind complex disorders. The identification of reliable and reproducible markers has lately been achieved by integrating genome-scale functional relationships and transcriptome datasets, and a number of algorithms have been developed to support this strategy. In this paper, we present a promising and easily applicable tool to accomplish this goal, namely CytoGTA, which is a Cytoscape plug-in that relies on an optimistic game theoretic approach (GTA) for identifying subnetwork markers. Given transcriptomic data of two phenotype classes and interactome data, this plug-in offers discriminative markers for the two classes. The high performance of CytoGTA would not have been achieved if the strategy of GTA was not implemented in Cytoscape. This plug-in provides a simple-to-use platform, convenient for biological researchers to interactively work with and visualize the structure of subnetwork markers. CytoGTA is one of the few available Cytoscape plug-ins for marker identification, which shows superior performance to existing methods. © 2017 Farahmand et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited
  5. Keywords:
  6. Transcriptome ; Data analysis software ; Game ; Gene expression profiling ; Genetic database ; Genetic marker ; Intermethod comparison ; Mathematical analysis ; Phenotype ; Reliability ; Reproducibility ; Transcriptomics ; Algorithm ; Game ; Algorithms ; Game Theory ; Gene Expression Profiling
  7. Source: PLoS ONE ; Volume 12, Issue 10 , 2017 ; 19326203 (ISSN)
  8. URL: http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0185016