The Discovery of Mutated Driver Pathways in Cancer: Models and Algorithms

被引：37

作者：

Zhang, Junhua ^{[1
,2
]}

Zhang, Shihua ^{[1
,2
]}

机构：

[1] Chinese Acad Sci, Acad Math & Syst Sci, Natl Ctr Math & Interdisciplinary Sci, Beijing 100190, Peoples R China

[2] Univ Chinese Acad Sci, Sch Math Sci, Beijing 100049, Peoples R China

来源：

IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS | 2018年 / 15卷 / 03期

基金：

中国国家自然科学基金;

关键词：

Bioinformatics; cancer genomics; driver gene; driver pathway; mutual exclusivity; co-occurring mutation; MUTUAL EXCLUSIVITY; SOMATIC MUTATIONS; GENETIC ALTERATIONS; NETWORK ANALYSIS; MODULES; BREAST; STRATIFICATION; IDENTIFICATION; COMBINATIONS; PROGRESSION;

D O I：

10.1109/TCBB.2016.2640963

中图分类号：

Q5 [生物化学];

学科分类号：

071010 ; 081704 ;

摘要：

The pathogenesis of cancer in human is still poorly understood. With the rapid development of high-throughput sequencing technologies, huge volumes of cancer genomics data have been generated. Deciphering that data poses great opportunities and challenges to computational biologists. One of such key challenges is to distinguish driver mutations, genes as well as pathways from passenger ones. Mutual exclusivity of gene mutations (each patient has no more than one mutation in the gene set) has been observed in various cancer types and thus has been used as an important property of a driver gene set or pathway. In this article, we aim to review the recent development of computational models and algorithms for discovering driver pathways or modules in cancer with the focus on mutual exclusivity-based ones.

引用

页码：988 / 998

页数：11

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