Abstract
Genes and gene products interact in an integrated and coordinated way to support functions of a living cell. In this research, we analyze these interactions in 17 different types of cancers, focusing on the interactions presented in pathway maps in Kyoto Encyclopedia of Genes and Genomes repository. We extracted the gene-to-gene interactions from the pathway maps and integrated them to form a large integrated graph. We then utilized different techniques and filtering criteria to extract and shed lights on the gene-gene interaction patterns. We conclude that the graph motifs we identified in cancer pathways provide insights for cancer biologists to connect dots and generate strong hypotheses so further biological investigations into cancer initiation, progression, and treatment can be conducted effectively.
Short Research Paper.
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Paul, B.E., Kasem, O., Zhao, H., Duan, ZH. (2021). Common Motifs in KEGG Cancer Pathways. In: Arabnia, H.R., Deligiannidis, L., Shouno, H., Tinetti, F.G., Tran, QN. (eds) Advances in Computer Vision and Computational Biology. Transactions on Computational Science and Computational Intelligence. Springer, Cham. https://doi.org/10.1007/978-3-030-71051-4_60
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