文章基本信息

标题：Inference of cancer progression from somatic mutation data
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作者：Hao Wu ; Lin Gao ; Nikola Kasabov 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2015
卷号：48
期号：28
页码：234-238
DOI：10.1016/j.ifacol.2015.12.131
语种：English
出版社：Elsevier
摘要：AbstractLarge-scale cancer genomics projects are providing a wealth of somatic mutation data. Therefore, one of the most challenging problems arising from the data is to infer the temporal order of somatic mutations. In the paper, we present a network-based method (NetInf) to infer cancer progression at the pathway level. We apply it to analyze somatic mutation data from real cancer studies. Experimental results show that these detected pathways overlap with known pathways, including RB, P53 signaling pathways. Our method reduces computational complexity and also provides new insights on the temporalorder of somatic mutations at the pathway level.
关键词：KeywordsCancer genomeCancer progressionNetwork modelsDynamic problemDriver mutation