Computational Prediction of HIV-1 Drug Targets Based on Gene Expression and the Virus-Host Interaction Network

被引：0

作者：

Zhao, Liping ^{[1
]}

Xiao, Xuan ^{[1
]}

Jia, Jianhua

机构：

[1] Jingdezhen Ceram Inst, Jingdezhen 333001, Jiangxi, Peoples R China

来源：

INTERNATIONAL CONFERENCE ON COMPUTATIONAL AND INFORMATION SCIENCES (ICCIS 2014) | 2014年

关键词：

INFECTION; SELECTION;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, we identified 4.626 records from 100.010 records by using the Minimum Redundancy-Maximum Relevance (mRMR) principle and Incremental Feature Selection (IFS) method. We investigated the virus-host protein interaction network. These proteins are located on the shortest paths between virus-targeted proteins and are important for exchanging information between virus-targeted proteins and coordinating virus invasion. Targeting of these proteins may disrupt the communication between virus-targeted proteins and infection, and they may serve as novel drug targets for Acquired Immune Deficiency Syndrome (AIDS) therapy or prevention.

引用

页码：784 / 789

页数：6

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