Identifying Cancer Subnetwork Markers Using Game Theory Method
In this paper, a novel game theory method is proposed to identify subnetwork markers by integrating gene expression profile and protein-protein interaction network. The proposed method has been evaluated on different cancer datasets in order to classify cancer phenotypes. To verify the performance of our approach, the identified subnetwork markers are compared with a greedy search method. The proposed method is capable of identifying robust subnetwork markers and presents higher classification performance.
KeywordsCancer subnetwork markers Microarray data analysis Game theory Cancer classification
The authors are grateful to the anonymous referees for their constructive and insightful comments. They also thank Dr. Lage Kasper, Dr. Naser Ansaripour, and Navadon Khunlertgit for their helpful discussions and comments.
Conflicts of Interest
The authors declare that they have no conflict of interest.
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