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A computational study identifies HIV progression-related genes using mRMR and shortest path tracing
Chengcheng Ma1, Xiao Dong, Rudong Li
1Key Laboratory of Systems Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, P.R. China ; University of Chinese Academy of Sciences, Beijing, P.R. China.
Plos One
|November 19, 2013
Summary
Identifying host factors is crucial for understanding HIV pathogenesis. This study used mRMR and network analysis to find genes, particularly those involved in apoptosis, linked to different HIV progression rates.
Area of Science:
- Immunology
- Computational Biology
- Genetics
Background:
- The relationship between HIV viral load and CD4+ T cell decline is weak.
- Understanding host factors is vital for HIV pathogenesis research and treatment development.
Purpose of the Study:
- To identify host factors associated with varying HIV infection responses.
- To investigate the role of these factors in disease progression.
Main Methods:
- Applied the Maximum Relevance Minimum Redundancy (mRMR) algorithm to microarray data from CD4+ T cells.
- Analyzed data from viremic non-progressors (VNPs) and rapid progressors (RPs).
- Constructed a weighted molecular interaction network using STRING database data.
Main Results:
- Identified 147 genes using the mRMR algorithm.
- Identified 1331 genes on shortest paths within the molecular network.
- Functional analysis highlighted the significant role of apoptosis-related functions in HIV pathogenesis.
Conclusions:
- Apoptosis plays a key role in the pathogenesis of HIV infection.
- The identified host factors provide new insights into HIV progression mechanisms.
