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论文类型：期刊论文

发表时间：2022-06-29

发表刊物：Journal of Electronic Measurement and Instrument

卷号：33

期号：9

页面范围：183-191

ISSN号：1000-7105

关键字："driver gene set; gene expression; optimization model; genetic algorithm"

CN号：11-2488/TN

摘要：In order to explore the molecular mechanisms and develop efficient therapies for cancer,an optimizationmodel for searching cancer driver gene sets is proposed. The method,called expression covariate based Driver gene set discovery algorithm (ExpDS), combines coverage, exclusivity and the covariate of gene expression level to build the maximum weight submatrix for identifying driver gene sets. The optimization of the maximum weight submatrix is an NP problem, so the genetic algorithm is applied to optimize the function. ExpDS is applied to the lung adenocarcinoma dataset (TSP, Nature 2008) for validation, and the results indicate that ExpDSis more efficient than several other methods in identifying genes involved in validated cellular signaling pathways,which are highly covered, significantly exclusive, and with high weight.

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