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

被引:0
|
作者
Li Yang
Gang Wei
Kun Tang
Christine Nardini
Jing-Dong J. Han
机构
[1] Chinese Academy of Sciences,CAS Key Laboratory of Computational Biology, CAS
来源
关键词
genomics; epigenomics; phenomics; integration; data analysis;
D O I
暂无
中图分类号
学科分类号
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:6
相关论文
共 50 条
  • [1] Understanding human diseases with high-throughput quantitative measurement and analysis of molecular signatures
    YANG Li
    WEI Gang
    TANG Kun
    NARDINI Christine
    HAN Jing-Dong J.
    Science China(Life Sciences), 2013, 56 (03) : 213 - 219
  • [2] Understanding human diseases with high-throughput quantitative measurement and analysis of molecular signatures
    Yang Li
    Wei Gang
    Tang Kun
    Nardini, Christine
    Han, Jing-Dong J.
    SCIENCE CHINA-LIFE SCIENCES, 2013, 56 (03) : 213 - 219
  • [3] Understanding human diseases with high-throughput quantitative measurement and analysis of molecular signatures
    YANG Li
    WEI Gang
    TANG Kun
    NARDINI Christine
    HAN Jing-Dong J.
    Science China(Life Sciences) , 2013, (03) : 213 - 219
  • [4] Understanding molecular mechanisms with high-throughput analysis and data mining
    Sucularli, Ceren
    INTERNATIONAL JOURNAL OF MOLECULAR MEDICINE, 2016, 38 : S25 - S25
  • [5] A high-throughput assay for quantitative measurement of PCR errors
    Shagin, Dmitriy A.
    Shagina, Irina A.
    Zaretsky, Andrew R.
    Barsova, Ekaterina V.
    Kelmanson, Ilya V.
    Lukyanov, Sergey
    Chudakov, Dmitriy M.
    Shugay, Mikhail
    SCIENTIFIC REPORTS, 2017, 7
  • [6] A high-throughput assay for quantitative measurement of PCR errors
    Dmitriy A. Shagin
    Irina A. Shagina
    Andrew R. Zaretsky
    Ekaterina V. Barsova
    Ilya V. Kelmanson
    Sergey Lukyanov
    Dmitriy M. Chudakov
    Mikhail Shugay
    Scientific Reports, 7
  • [7] High-Throughput Quantitative Analysis of the Human Intestinal Microbiota with a Phylogenetic Microarray
    Paliy, Oleg
    Kenche, Harshavardhan
    Abernathy, Frank
    Michail, Sonia
    APPLIED AND ENVIRONMENTAL MICROBIOLOGY, 2009, 75 (11) : 3572 - 3579
  • [8] Bayesian Analysis of High-Throughput Quantitative Measurement of Protein-DNA Interactions
    Pollock, David D.
    de Koning, A. P. Jason
    Kim, Hyunmin
    Castoe, Todd A.
    Churchill, Mair E. A.
    Kechris, Katerina J.
    PLOS ONE, 2011, 6 (11):
  • [9] A high-throughput method for the quantitative analysis of auxins
    Barkawi, Lana S.
    Tam, Yuen-Yee
    Tillman, Julie A.
    Normanly, Jennifer
    Cohen, Jerry D.
    NATURE PROTOCOLS, 2010, 5 (10) : 1609 - 1618
  • [10] Quantitative analysis of high-throughput biological data
    Juan, Hsueh-Fen
    Huang, Hsuan-Cheng
    WILEY INTERDISCIPLINARY REVIEWS-COMPUTATIONAL MOLECULAR SCIENCE, 2023, 13 (04)