CnnDTI: Predicting drug-target interactions from drug structure and protein sequence
using novel convolutional neural networks
To predict drug-targets by a CNN system ...
Background: Accurate identification of potential interactions between drugs and protein targets is a critical step to accelerate drug discovery. Despite many relative experimental researches have been done in the past decades, detecting drug-target interactions (DTIs) remains to be extremely resource-intensive and time-consuming. Therefore, many computational approaches have been developed for predicting drug-target associations on a large scale.
Additional file 1: This file records the detailed drug-target pairs on enzymes, ion channels, GPCRs and nuclear receptors of the Dataset2.
Additional file 2: In this file, to obtain the optimal learning rate of our model, a series of different learning rates are explored on each types of protein families of both Dataset1 and Dataset2.
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