Data for DeepTMInter: Accurate sequence-based prediction of interaction sites in α-helical transmembrane proteins by deep learning

It contains five folders: 1). PDB. Crystallographic structures of TM proteins in the TrainData, IndepData, TestData, and CompData datasets. 2). Fasta. Sequences of TM proteins in the TrainData, IndepData, TestData, and CompData datasets. 3). Topology. Structure-derived and Phobius-predicted topologies of TM proteins in the TrainData, IndepData, TestData, and CompData datasets. 4). Cross Validation. 5-fold cross validations of the TrainData dataset by the stratified-shuffle method. 5). Prediction. Predictions of the 7 tools (DeepTMInter, DELPHI, MBPredAll, MBPredCombined, MBPredCyto, MBPredExtra, and MBPredTM) on the IndepData, TestData, and CompData datasets. Predictions of DeepTMInter on the human transmembrane proteome (5051 proteins).