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Updated: May 10, 2026

Detecting Somatic Genetic Alterations in Tumor Specimens by Exon Capture and Massively Parallel Sequencing
Published on: October 18, 2013
Identifying driver mutations from sequencing data of heterogeneous tumors in the era of personalized genome
Jing Zhang1, Jie Liu, Jianbo Sun
1Hangzhou, 310003, China; biaoylin@gmail.com.
Abstract:
Distinguishing driver mutations from passenger mutations is critical to the understanding of the molecular mechanisms of carcinogenesis and for identifying prognostic and diagnostic markers as well as therapeutic targets. We reviewed the current approaches and software for identifying driver mutations from passenger mutations including both biology-based approaches and machine-learning-based approaches. We also reviewed approaches to identify driver mutations in the context of pathways or gene sets. Finally, we discussed the challenges of predicting driver mutations considering the complexities of inter- and intra-tumor heterogeneity as well as the evolution and progression of tumors.
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