Before revision:  Further, computer scientists can use DeepPurpose to train customized DTI prediction models with 15 drug and target encodings and 50 + novel DL architectures. To tackle method development challenges, DeepPurpose also supports various data split settings and preloads five benchmarking datasets. We demonstrated that DeepPurpose allows users to obtain state-of-the-art prediction performance on several benchmark datasets .
After revision:  Further, computer scientists can use DeepPurpose to train customized DTI prediction models with 15 drug and target encodings and 50 neural architectures, along with providing many other useful features. We demonstrate state-of-the-art prediction performance on several benchmark datasets .