Deep convolutional networks for quality assessment of protein folds-Reference-Cited by-同舟云学术

Deep convolutional networks for quality assessment of protein folds

Published:2018-06-19 Issue:23 Volume:34 Page:4046-4053
ISSN:1367-4803
Container-title:Bioinformatics
language:en
Short-container-title:

Author:

Derevyanko Georgy¹,Grudinin Sergei²^ORCID,Bengio Yoshua³,Lamoureux Guillaume¹^ORCID

Affiliation:

1. Department of Chemistry and Biochemistry and Centre for Research in Molecular Modeling (CERMM), Concordia University, Montréal, Québec, Canada

2. Inria, Université Grenoble Alpes, CNRS, Grenoble INP, LJK, Grenoble, France

3. Department of Computer Science and Operations Research, Université de Montréal, Montréal, Québec, Canada

Funder

Natural Sciences and Engineering Research Council of Canada

NSERC

Canada Research Chair

Canadian Institute for Advanced Research

CIFAR

Calcul Québec and Compute Canada

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

Link

http://academic.oup.com/bioinformatics/article-pdf/34/23/4046/26676600/bty494.pdf

Reference56 articles.

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2. Basic local alignment search tool;Altschul;J. Mol. Biol,1990

3. DeepQA: improving the estimation of single protein model quality with deep belief networks;Cao;BMC Bioinformatics,2016

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