Cancer Classification With MicroRNA Expression Patterns Found By An Information Theory Approach

Abstract-- Some non-coding small RNAs, known as microRNAs (miRNAs), have been shown to play important roles in gene regulation and various biological processes. The abnormal expression of some specific miRNA genes often results in the development of cancer. In this paper, we find discriminatory miRNA patterns for cancer classification from miRNA expression profiles with an information theory approach. Our approach evaluates subset of miRNAs by checking the mutual information between these miRNAs and the class attribute I(X; Y ) with respect to the entropy of the class attribute H(Y ). Then, optimal subset of miRNAs that satisfies I(X; Y ) = H(Y ) or H(Y ) - I(X; Y )

• Type: Journal
• Year: 2006
• Where: JCP
• Authors: Yun Zheng, Chee Keong Kwoh
• Keywords: Discriminatory MiRNA Patterns, JCP 2006, MiRNA, Non-coding Small Rnas