Mining of MicroRNA expression data—a rough set approach

Authors:
Jianwen Fang;Jerzy W. Grzymala-Busse
Affiliations:
Bioinformatics Core Facility, Information and Telecommunication Technology Center, University of Kansas, Lawrence, KS;Department of Electrical Engineering and Computer Science, University of Kansas, Lawrence, KS
Venue:
RSKT'06 Proceedings of the First international conference on Rough Sets and Knowledge Technology
Year:
2006

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Abstract

In our research we used a microRNA expression level data set describing eleven types of human cancers. Our methodology was based on data mining (rule induction) using rough set theory. We used a novel methodology based on rule generations and cumulative rule sets. The original testing data set described only four types of cancer. We further restricted our attention to two types of cancer: breast and ovary. Using our combined rule set, all but one cases of breast cancer and all cases of ovary cancer were correctly classified