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Frontiers of Computer Science

ISSN 2095-2228

ISSN 2095-2236(Online)

CN 10-1014/TP

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2018 Impact Factor: 1.129

Front. Comput. Sci.    2017, Vol. 11 Issue (3) : 392-406    https://doi.org/10.1007/s11704-016-5568-5
REVIEW ARTICLE
Integrative cancer genomics: models, algorithms and analysis
Jinyu CHEN, Shihua ZHANG()
National Center for Mathematics and Interdisciplinary Sciences, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, China
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Abstract

In the past decade, the remarkable development of high-throughput sequencing technology accelerates the generation of large amount of multiple dimensional data such as genomic, epigenomic, transcriptomic and proteomic data. The comprehensive data make it possible to understand the underlying mechanisms of biology and disease such as cancer systematically. It also provides great challenges for computational cancer genomics due to the complexity, scale and noise of data. In this article, we aim to review the recent developments and progresses of computational models, algorithms and analysis of complex data in cancer genomics. These topics of this paper include the identification of driver mutations, the genetic heterogeneity analysis, genomic markers discovery of drug response, pan-cancer scale analysis and so on.

Keywords cancer genomics      model      algorithm      data integration      bioinformatics      computational biology     
Corresponding Author(s): Shihua ZHANG   
Just Accepted Date: 21 July 2016   Online First Date: 31 October 2016    Issue Date: 25 May 2017
 Cite this article:   
Jinyu CHEN,Shihua ZHANG. Integrative cancer genomics: models, algorithms and analysis[J]. Front. Comput. Sci., 2017, 11(3): 392-406.
 URL:  
https://academic.hep.com.cn/fcs/EN/10.1007/s11704-016-5568-5
https://academic.hep.com.cn/fcs/EN/Y2017/V11/I3/392
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