Understanding human diseases with high-throughput quantitative measurement and analysis of molecular signatures

被引:0
|
作者
YANG Li [1 ]
WEI Gang [1 ]
TANG Kun [1 ]
NARDINI Christine [1 ]
HAN Jing-Dong J. [1 ]
机构
[1] CAS Key Laboratory of Computational Biology,CAS-MPG Institute for Computational Biology,Shanghai Institutes of Biological Sciences,Chinese Academy of Sciences
关键词
genomics; epigenomics; phenomics; integration; data analysis;
D O I
暂无
中图分类号
R346 [];
学科分类号
1001 ;
摘要
Microarray and deep sequencing technologies have provided unprecedented opportunities for mapping genome mutations,RNA transcripts,transcription factor binding,and histone modifications at high resolution at the genome-wide level.This has revolutionized the way in which transcriptomes,regulatory networks and epigenetic regulations have been studied and large amounts of heterogeneous data have been generated.Although efforts are being made to integrate these datasets unbiasedly and efficiently,how best to do this still remains a challenge.Here we review major impacts of high-throughput genome-wide data generation,their relevance to human diseases,and various bioinformatics approaches for data integration.Finally,we provide a case study on inflammatory diseases.
引用
收藏
页码:213 / 219
页数:7
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