A consensus method for prioritising drug-associated target proteins

Gang Shu, Xiaodi Huang, Shanfeng Zhu

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

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.
Original languageEnglish
Pages (from-to)178-195
Number of pages18
JournalInternational Journal of Data Mining and Bioinformatics
Volume6
Issue number2
DOIs
Publication statusPublished - 01 Jul 2012

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