Single‐sequence‐based prediction of protein secondary structures and solvent accessibility by deep whole‐sequence learning-Reference-Cited by-同舟云学术

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Single‐sequence‐based prediction of protein secondary structures and solvent accessibility by deep whole‐sequence learning

Published:2018-10-05 Issue:26 Volume:39 Page:2210-2216
ISSN:0192-8651
Container-title:Journal of Computational Chemistry
language:en
Short-container-title:J. Comput. Chem.

Author:

Heffernan Rhys¹^ORCID,Paliwal Kuldip¹,Lyons James¹,Singh Jaswinder¹,Yang Yuedong²,Zhou Yaoqi³^ORCID

Affiliation:

1. Signal Processing Laboratory Griffith University Brisbane QLD 4111 Australia

2. School of Data and Computer Science Sun Yet‐Sen University Guangzhou China

3. Institute for Glycomics and School of Information and Communication Technology Griffith University Southport QLD 4222 Australia

Funder

National Health and Medical Research Council

Australian Research Council

Publisher

Wiley

Subject

Computational Mathematics,General Chemistry

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/jcc.25534

Reference34 articles.

1. The Protein-Folding Problem, 50 Years On

2. Trends in template/fragment-free protein structure prediction

3. Minimization of polypeptide energy. I. Preliminary structures of bovine pancreatic ribonuclease S-peptide.

4. Protein structure determination using metagenome sequence data

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