Gene Expression Profile Analysis for Drug Discovery and Precision Medicine

被引：0
|
作者：
Liu Yang [1 ]
Bai Hui [2 ]
Tao Huan [3 ]
He Song [4 ]
Huang Xin [4 ]
Bo Xiao-Chen [4 ]
Wang Sheng-Qi [4 ]
机构：
[1] 302 Hosp PLA, Beijing 100039, Peoples R China
[2] 451 Hosp PLA, Xian 710054, Peoples R China
[3] Fourth Mil Med Univ, Xian 710032, Peoples R China
[4] Acad Mil Med Sci, Inst Radiat Med, Beijing 100850, Peoples R China
来源：
PROGRESS IN BIOCHEMISTRY AND BIOPHYSICS | 2016年 / 43卷 / 10期
基金：
中国国家自然科学基金;
关键词：
gene expression profile; connectivity map; library of integrated network-based cellular signatures; gene regulatory network; multi-omics data integration; precision medicine; REGULATORY NETWORK INFERENCE; CONNECTIVITY MAP; PROTEIN EXPRESSION; PATTERN DISCOVERY; BAYESIAN NETWORK; HUMAN-DISEASE; CANCER; IDENTIFICATION; DATABASE; GENOMICS;
D O I：
10.16476/j.pibb.2016.0140
中图分类号：
Q5 [生物化学]; Q7 [分子生物学];
学科分类号：
071010 ; 081704 ;
摘要：
As an important part of functional genomics, gene expression profiling plays an important role in many fields, such as biology, medicine and drug discovery. With the advent of precision medicine, integration of multi-omits data for personalized health care is becoming the trend of future medicine. In this review, Relevant databases of gene expression profile were introduced first. And then three general methods for gene expression profile analysis, i.e., connectivity map method, gene regulatory network method and multi-omics data integration methods were focused. The latest usage of these methods in drug discovery, especially in cancer drug development was reviewed. This review would serve as a guide for transcriptome-based drug discovery.
引用
收藏
页码：923 / 935
页数：13
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