13 citations · 22 across the 6 of their papers we have counts for
7 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…
Joint alignment of multiple protein-protein interaction networks via convex optimization
Somaye Hashemifar, Qixing Huang, Jinbo XU
Motivation: High-throughput experimental techniques have been producing more and more protein-protein interaction (PPI) data. PPI network alignment greatly benefits the understandi…
Bermuda: Bidirectional de novo assembly of transcripts with new insights for handling uneven coverage
Qingming Tang, Sheng Wang, Jian Peng +2
Motivation: RNA-seq has made feasible the analysis of a whole set of expressed mRNAs. Mapping-based assembly of RNA-seq reads sometimes is infeasible due to lack of high-quality re…
iTreePack: Protein Complex Side-Chain Packing by Dual Decomposition
Jian Peng, Raghavendra Hosur, Bonnie Berger +1
Protein side-chain packing is a critical component in obtaining the 3D coordinates of a structure and drug discovery. Single-domain protein side-chain packing has been thoroughly s…
Learning Scale-Free Networks by Dynamic Node-Specific Degree Prior
Qingming Tang, Siqi Sun, Jinbo Xu
Learning the network structure underlying data is an important problem in machine learning. This paper introduces a novel prior to study the inference of scale-free networks, which…