Ensembling multiple raw coevolutionary features with deep residual neural networks for contact‐map prediction in CASP13-Reference-Cited by-同舟云学术

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Ensembling multiple raw coevolutionary features with deep residual neural networks for contact‐map prediction in CASP13

Published:2019-08-22 Issue:12 Volume:87 Page:1082-1091
ISSN:0887-3585
Container-title:Proteins: Structure, Function, and Bioinformatics
language:en
Short-container-title:Proteins

Author:

Li Yang¹²^ORCID,Zhang Chengxin²^ORCID,Bell Eric W.²,Yu Dong‐Jun¹²,Zhang Yang²^ORCID

Affiliation:

1. School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing China

2. Department of Computational Medicine and Bioinformatics University of Michigan Ann Arbor Michigan USA

Funder

Fundamental Research Funds for the Central Universities

National Institute of General Medical Sciences

National Natural Science Foundation of China

National Science Foundation

Publisher

Wiley

Subject

Molecular Biology,Biochemistry,Structural Biology

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/prot.25798

Reference41 articles.

1. A possible three-dimensional structure of bovine α-lactalbumin based on that of hen's egg-white lysozyme

2. Computer simulation of protein folding

3. Comparative Protein Modelling by Satisfaction of Spatial Restraints

4. Improving Protein Structure Prediction Using Multiple Sequence-Based Contact Predictions

5. Improved de novo structure prediction in CASP11 by incorporating coevolution information into Rosetta

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