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Identifying Cancer Subnetwork Markers Using Game Theory Method

  • Saman Farahmand
  • Sama Goliaei
  • Zahra Razaghi Moghadam Kashani
  • Sina Farahmand
Conference paper
Part of the IFMBE Proceedings book series (IFMBE, volume 64)

Abstract

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.

Keywords

Cancer subnetwork markers Microarray data analysis Game theory Cancer classification 

Notes

Acknowledgements

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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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Saman Farahmand
    • 1
  • Sama Goliaei
    • 1
  • Zahra Razaghi Moghadam Kashani
    • 2
  • Sina Farahmand
    • 3
  1. 1.Research Laboratory for Computational Biology, Network Science and Technology DepartmentUniversity of TehranTehranIran
  2. 2.Life Science Engineering DepartmentUniversity of TehranTehranIran
  3. 3.Laboratory of Neural Engineering Research, Biomedical Engineering DepartmentIllinois Institute of TechnologyChicagoUSA

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