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Indexed by:期刊论文

Date of Publication:2022-06-29

Journal:大连理工大学学报

Volume:58

Issue:2

Page Number:180-186

ISSN No.:1000-8608

Abstract:The occurrence and development of tumor are mainly caused by the accumulation of gene mutations,which leads to the disorder of cell signal pathways.There are two properties of gene sets in a pathway,i.e.,high coverage and high exclusivity.A driver pathway searching method is proposed based on ant colony optimization algorithm by combining gene covariates with these two properties.In this way,cancer-causing driver pathways are identified by searching for highly covered and highly exclusive gene sets in a pathway based on the gene mutation data and covariate data.First, by analyzing the correlations between the three gene covariates,i.e.,gene expression level, replication time and hic compartment,and their correlations with the gene mutation frequency, replication time is selected as the weight covariate of the gene mutation frequency.Then,a novel maximum weight submatrix function is constructed by combining the weight covariate with existing methods as the obj ective function of the combinatorial optimization problem.Finally,the ant colony optimization algorithm is introduced to overcome the NP problem of this optimization problem.The proposed method is applied to the lung adenocarcinoma mutation data and the results show that compared with the existing methods the proposed method can identify more cancer genes,some of which are involved in known pathways.In addition,the detected gene pairs with significant exclusivity are contained,all of these prove the efficiency of the proposed method.

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