title: Interacting gene selection via cooperative game analysis for cancer diagnosis.
abstract: Microarray technologies offer practical diagnostic tools for cancer detection. One great challenge is to identify salient genes from the high dimensionality of microarray data that can directly contribute to the symptom of cancer. Interactions among genes have been recognized to be fundamentally important for understanding biological function. This paper proposes an interacting gene selection method for cancer classification by identifying useful interacting genes. The method firstly evaluates the interactivity degree of each gene according to the intricate interrelation among genes by cooperative game analysis. Then genes are selected in a forward way by considering both interactivity and relevance characters. Experimental comparisons are carried out on four publicly available microarray data sets with three outstanding gene selection methods. Moreover a gene set enrichment analysis is also performed on the selected gene subset. The results show that the proposed method achieves better classification performance and enrichment score than other gene selection methods.
authors.affiliation: College of Information Science and Engineering, Ocean University of China, Qingdao 266100, China.
authors.forename: Xin
authors.initials: X
authors.lastname: Sun
authors.affiliation: College of Information Science and Engineering, Ocean University of China, Qingdao 266100, China.
authors.forename: Junyu
authors.initials: J
authors.lastname: Dong
authors.affiliation: School of Computing, University of Eastern Finland, Joensuu 111 FIN-80101, Finland School of Medical Instrument and Food Engineering, University of Shanghai for Science and Technology, Shanghai 200031, China.
authors.forename: Mantao
authors.initials: M
authors.lastname: Xu
authors.affiliation: College of Information Science and Engineering, Ocean University of China, Qingdao 266100, China.
authors.forename: Shengke
authors.initials: S
authors.lastname: Wang
authors.affiliation: College of Information Science and Engineering, Ocean University of China, Qingdao 266100, China.
authors.forename: Cui
authors.initials: C
authors.lastname: Xie
mesh_terms: D014408:Biomarkers, Tumor / Q000378:metabolism*; D003936:Diagnosis, Computer-Assisted / Q000379:methods; D005716:Game Theory; D020869:Gene Expression Profiling / Q000379:methods; D006801:Humans; D009363:Neoplasm Proteins / Q000235:genetics / Q000378:metabolism*; D009369:Neoplasms / Q000175:diagnosis* / Q000378:metabolism*; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D025941:Protein Interaction Mapping / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity
chemical_list: D014408:Biomarkers, Tumor; D009363:Neoplasm Proteins
keywords: Medical diagnosis; cancer classification; cooperative game analysis; gene selection; information theory