1k citations · 1.2k across the 13 of their papers we have counts for
13 papers
Real-value and confidence prediction of protein backbone dihedral angles through a hybrid method of clustering and deep learning
Yujuan Gao, Sheng Wang, Minghua Deng +1
Background. Protein dihedral angles provide a detailed description of protein local conformation. Predicted dihedral angles can be used to narrow down the conformational space of t…
Folding membrane proteins by deep transfer learning
Sheng Wang, Zhen Li, Yizhou Yu +1
Computational elucidation of membrane protein (MP) structures is challenging partially due to lack of sufficient solved structures for homology modeling. Here we describe a high-th…
Predicting membrane protein contacts from non-membrane proteins by deep transfer learning
Zhen Li, Sheng Wang, Yizhou Yu +1
Computational prediction of membrane protein (MP) structures is very challenging partially due to lack of sufficient solved structures for homology modeling. Recently direct evolut…
Accurate De Novo Prediction of Protein Contact Map by Ultra-Deep Learning Model
Sheng Wang, Siqi Sun, Zhen Li +2
Recently exciting progress has been made on protein contact prediction, but the predicted contacts for proteins without many sequence homologs is still of low quality and not very…
Protein secondary structure prediction using deep convolutional neural fields
Sheng Wang, Jian Peng, Jianzhu Ma +1
Protein secondary structure (SS) prediction is important for studying protein structure and function. When only the sequence (profile) information is used as input feature, current…
Predicting diverse M-best protein contact maps
Siqi Sun, Jianzhu Ma, Sheng Wang +1
Protein contacts contain important information for protein structure and functional study, but contact prediction from sequence information remains very challenging. Recently evolu…