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integrativecancergenomicsmodelsalgorithmsandanalysis
Chen Jinyu; Zhang Shihua
2017
Source Publicationfrontiersofcomputerscience
ISSN2095-2228
Volume11Issue:3Pages:392
AbstractIn 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.
Language英语
Funding Project[National Natural Science Foundation of China] ; [Strategic Priority Research Program of the Chinese Academy of Sciences (CAS)] ; [Outstanding Young Scientist Program of CAS] ; [Key Research Program of Frontier Sciences, CAS] ; [Key Laboratory of Random Complex Structures and Data Science, CAS]
Document Type期刊论文
Identifierhttp://ir.amss.ac.cn/handle/2S8OKBNM/43834
Collection应用数学研究所
Affiliation中国科学院数学与系统科学研究院
Recommended Citation
GB/T 7714
Chen Jinyu,Zhang Shihua. integrativecancergenomicsmodelsalgorithmsandanalysis[J]. frontiersofcomputerscience,2017,11(3):392.
APA Chen Jinyu,&Zhang Shihua.(2017).integrativecancergenomicsmodelsalgorithmsandanalysis.frontiersofcomputerscience,11(3),392.
MLA Chen Jinyu,et al."integrativecancergenomicsmodelsalgorithmsandanalysis".frontiersofcomputerscience 11.3(2017):392.
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