A consensus method for prioritising drug-associated target proteins

Authors:
Gang Shu;Xiaodi Huang;Shanfeng Zhu
Affiliations:
The School of Computer Science and Shanghai Key Lab. of Intelligent Information Processing, Fudan University, Shanghai 200433, China;School of Computing and Mathematics, Charles Sturt University, Albury, NSW 2640, Australia;The School of Computer Science and Shanghai Key Lab. of Intelligent Information Processing, Fudan University, Shanghai 200433, China
Venue:
International Journal of Data Mining and Bioinformatics
Year:
2012

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Abstract

It is generally believed that the degree of a relation between two entities is likely to be stronger if they co-occur more often in the literature. Based on this assumption, several methods are used in biomedical text mining such as support, confidence, chi-square, odds ratio, lift, all-confidence, coherence, and pof. Comparing these eight methods, our work aims to find the best one. Also, we present a consensus approach that can further improve the performance. Experimental results on prioritising drug targets have shown that pof, coherence, and all-confidence in sequence are the top three. By integrating coherence into pof, the consensus method is the best one among all compared methods.