Before revision:  Here we introduce DMPfold, a development of the DeepMetaPSICOV contact predictor, that predicts inter-atomic distances and uses these to build models . Unsatisfied constraints are removed in an iterative process . DMPfold produces more accurate models than two popular methods for the CASP12 free modelling domains, and is able to generate high quality models without any modifications for a set of transmembrane proteins.
After revision:  Here we introduce DMPfold, a development of the DeepMetaPSICOV contact predictor, which uses deep learning throughout to predict inter-atomic distances and uses these to build models . Unsatisfied constraints are removed in an iterative process . DMPfold produces more accurate models than two popular methods for the CASP12 free modelling domains, and is able to generate high quality models without any modifications for a set of transmembrane proteins.