A computational study identifies HIV progression-related genes using mRMR and shortest path tracing

Ma Chengcheng, Xiao Dong, Rudong Li, Lei Liu

Research output: Contribution to journalArticle

5 Scopus citations

Abstract

Since statistical relationships between HIV load and CD4+ T cell loss have been demonstrated to be weak, searching for host factors contributing to the pathogenesis of HIV infection becomes a key point for both understanding the disease pathology and developing treatments. We applied Maximum Relevance Minimum Redundancy (mRMR) algorithm to a set of microarray data generated from the CD4+ T cells of viremic non-progressors (VNPs) and rapid progressors (RPs) to identify host factors associated with the different responses to HIV infection. Using mRMR algorithm, 147 gene had been identified. Furthermore, we constructed a weighted molecular interaction network with the existing protein-protein interaction data from STRING database and identified 1331 genes on the shortest-paths among the genes identified with mRMR. Functional analysis shows that the functions relating to apoptosis play important roles during the pathogenesis of HIV infection. These results bring new insights of understanding HIV progression.

Original languageEnglish (US)
Article numbere78057
JournalPloS one
Volume8
Issue number11
DOIs
Publication statusPublished - Nov 11 2013
Externally publishedYes

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ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)
  • Agricultural and Biological Sciences(all)
  • General

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