computational analysis of hiv-1 resistance based on gene expression profiles and the virus-host interaction network计算分析的基于基因表达谱和抗hiv - 1病毒-宿主相互作用网络.pdfVIP

Computational Analysis of HIV-1 Resistance Based on Gene Expression Profiles and the Virus-Host Interaction Network 1,2 3 4,5 4,6 3,7 Tao Huang , Zhongping Xu , Lei Chen , Yu-Dong Cai *, Xiangyin Kong * 1 Key Laboratory of Systems Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, People’s Republic of China, 2 Shanghai Center for Bioinformation Technology, Shanghai, People’s Republic of China, 3 State Key Laboratory of Medical Genomics, Shanghai Institute of Hematology, Shanghai Jiao Tong University School of Medicine, RuiJin Hospital, Shanghai, People’s Republic of China, 4 Centre for Computational Systems Biology, Fudan University, Shanghai, People’s Republic of China, 5 College of Information Engineering, Shanghai Maritime University, Shanghai, People’s Republic of China, 6 Institute of Systems Biology, Shanghai University, Shanghai, People’s Republic of China, 7 Key Laboratory of Stem Cell Biology, Institute of Health Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences and Shanghai Jiao Tong University School of Medicine, Shanghai, People’s Republic of China Abstract A very small proportion of people remain negative for HIV infection after repeated HIV-1 viral exposure, which is called HIV-1 resistance. Understanding the mechanism of HIV-1 resistance is important for the development of HIV-1 vaccines and Acquired Immune Deficiency Syndrome (AIDS) therapies. In this study, we analyzed the gene expression profiles of CD4+ T cells from HIV-1-resistant individuals and HIV-susceptible individuals. One hundred eighty-five discriminative HIV-1 resistance genes were identified using the Minimum Redundancy-Maximum Relevance (mRMR) and Incre