• Xiaoping Liu, Jiguang Wang, and Luonan Chen.
• Key Laboratory of Systems Biology, SIBS-Novo Nordisk Translational Research Centre for PreDiabetes, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China.
• Cancer Lett. 2013 Nov 1;340(2):270-6.

AbstractThe second-generation sequencing technologies have been extensively used to reveal the mechanism of tumorigenesis and find critical genes in cancer progression that can be potential targets of clinic treatment. Exome is a part of genome formed by exons which are the protein-coding portions of genes. The whole-exome sequencing information can reflect the mutations of the protein-coding region in the genome and depict the causal relationship between the mutations and phenotypes. Now, many network-based methods have been developed to identify cancer driver modules or pathways, which not only provide new insights into molecular mechanism of disease progression at network level but also can avoid low coverage or lowly recurrent on disease samples in contrast to individual driver genes. In this review, we focus on the recent advances on network-based methods for identifying cancer driver modules or pathways, including methods of whole-exome sequencing, somatic mutation detection, driver mutation identification, and mutation network reconstruction.Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

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