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Indexed by:期刊论文

Date of Publication:2022-06-29

Journal:Journal of Electronic Measurement and Instrument

Volume:33

Issue:9

Page Number:183-191

ISSN No.:1000-7105

Key Words:"driver gene set; gene expression; optimization model; genetic algorithm"

CN No.:11-2488/TN

Abstract: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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