A consensus method for prioritising drug-associated target proteins.
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.
The School of Computer Science and Shanghai Key Lab. of Intelligent Information Processing, Fudan University, Shanghai 200433, China. 09210240030@fudan.edu.cn
Gang
G
Shu
Xiaodi
X
Huang
Shanfeng
S
Zhu
D032921:Consensus; D057225:Data Mining / Q000379:methods*; D004364:Pharmaceutical Preparations / Q000737:chemistry*; D011506:Proteins / Q000037:antagonists & inhibitors / Q000737:chemistry* / Q000378:metabolism
D004364:Pharmaceutical Preparations; D011506:Proteins