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Computational and Mathematical Methods in Medicine
Volume 2015 (2015), Article ID 353146, 11 pages
Research Article

Finding Top- Covering Irreducible Contrast Sequence Rules for Disease Diagnosis

1College of Information Science and Engineering, Northeastern University, Shenyang, Liaoning 110819, China
2Software Center, Northeastern University, Shenyang, Liaoning 110004, China

Received 1 October 2014; Accepted 20 January 2015

Academic Editor: Lev Klebanov

Copyright © 2015 Yuhai Zhao et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Diagnostic genes are usually used to distinguish different disease phenotypes. Most existing methods for diagnostic genes finding are based on either the individual or combinatorial discriminative power of gene(s). However, they both ignore the common expression trends among genes. In this paper, we devise a novel sequence rule, namely, top- irreducible covering contrast sequence rules (TopIRs for short), which helps to build a sample classifier of high accuracy. Furthermore, we propose an algorithm called MineTopIRs to efficiently discover TopIRs. Extensive experiments conducted on synthetic and real datasets show that MineTopIRs is significantly faster than the previous methods and is of a higher classification accuracy. Additionally, many diagnostic genes discovered provide a new insight into disease diagnosis.