Abstract
Colorectal cancer is the third most commonly diagnosed cancer in the world. Microarray-based colorectal cancer diagnosis is increasingly paid more and more attentions. In view of a number of pathway information available in the KEGG database, this paper proposes to model pathways for colorectal cancer diagnosis, and as a result, a pathway-based classification method is developed. The proposed method can extract pathway information through modeling gene associations in a pathway via regression. Experimental results on six pathways show that the proposed method remarkably improves the performance of microarray-based colorectal cancer diagnosis.
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Wang, HQ., Xie, XP., Zheng, CH. (2012). A Pathway-Based Classification Method That Can Improve Microarray-Based Colorectal Cancer Diagnosis. In: Huang, DS., Gan, Y., Premaratne, P., Han, K. (eds) Bio-Inspired Computing and Applications. ICIC 2011. Lecture Notes in Computer Science(), vol 6840. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24553-4_81
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DOI: https://doi.org/10.1007/978-3-642-24553-4_81
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