DTI-CDF: a cascade deep forest model towards the prediction of drug-target interactions based on hybrid features

Volume: 22, Issue: 1, Pages: 451 - 462
Published: Dec 23, 2019
Abstract
Drug–target interactions (DTIs) play a crucial role in target-based drug discovery and development. Computational prediction of DTIs can effectively complement experimental wet-lab techniques for the identification of DTIs, which are typically time- and resource-consuming. However, the performances of the current DTI prediction approaches suffer from a problem of low precision and high false-positive rate. In this study, we aim to develop a...
Paper Details
Title
DTI-CDF: a cascade deep forest model towards the prediction of drug-target interactions based on hybrid features
Published Date
Dec 23, 2019
Volume
22
Issue
1
Pages
451 - 462
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