关键词: 药物-靶标相互作用, 机器学习, 贝叶斯排序, 分组策略

Abstract:

Drug-target interaction prediction based on Bayesian ranking has achieved good results, but neglects the correlation between drugs of the same target, which affects the accuracy. To solve this problem, a new method of drug-target interaction prediction based on grouped Bayesian ranking is proposed. In this method, according to the similarity of drugs interacting with specific targets, the grouping strategy is introduced to link these similar drugs, and the theoretical model based on grouping strategy is deduced. This method is comparing with five typical methods on five open datasets, and the experimental results are better than the comparison method.

Key words: drug-target interaction, machine learning, Bayesian ranking, grouping strategy