A novel cancer classifier based on differentially expressed gene network

Authors:
Jaegyoon Ahn;Youngmi Yoon;Sanghyun Park
Affiliations:
Yonsei University, Shinchondong, Seodaemun-gu, Seoul, Korea;Gachon Univ. of Medicine & Science, Gachon-Kwan, Yonsu-dong, Yonsu-gu, Incheon, Korea;Yonsei University, Shinchondong, Seodaemun-gu, Seoul, Korea
Venue:
Proceedings of the First ACM International Conference on Bioinformatics and Computational Biology
Year:
2010

Citing 3
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Abstract

It is fundamental and essential to elucidate how cancer-related genes interact with each other. In this study, we build two undirected graphs: one is a graph consisting of edges only observed in tumor samples, and the other is a graph consisting of edges only observed in normal samples. We apply a genetic algorithm for searching sub-networks of these genetic networks. Those gene sub-networks identify new cancer-related genes that might be related with previously known cancer-related genes, and also show a higher accuracy in classifying tumor and normal samples than the current methods.