Before revision:  a development of the DeepMetaPSICOV contact predictor, which uses deep learning throughout to predict inter-atomic distance bounds, the main chain hydrogen bond network, and main chain torsion anglesand uses these to build models in an iterative procedure . DMPfold produces more accurate models than two popular methods for a test set of CASP12 free modelling domains, and is able to generate high quality models without any modifications for a set of transmembrane proteins.
After revision:  a development of the DeepMetaPSICOV contact predictor, which uses deep learning throughout to predict inter-atomic distance bounds, the main chain hydrogen bond network, and torsion angles, which it uses to build models in an iterative procedure . DMPfold produces more accurate models than two popular methods for a test set of CASP12 free modelling domains, and is able to generate high quality models without any modifications for a set of transmembrane proteins.