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Identifying drug-target interactions is an important task in drug discovery. To reduce heavy time and financial cost in experimental way, many computational approaches have been proposed. Although these approaches have used many different principles, their performance is far from satisfactory, especially in predicting drug-target interactions of new candidate drugs or targets.

DrugE-Rank: improving drug–target interaction prediction of new candidate drugs or targets by ensemble learning to rank