High precision in protein contact prediction using fully convolutional neural networks and minimal sequence features-Reference-Cited by-同舟云学术

High precision in protein contact prediction using fully convolutional neural networks and minimal sequence features

Published:2018-04-26 Issue:19 Volume:34 Page:3308-3315
ISSN:1367-4803
Container-title:Bioinformatics
language:en
Short-container-title:

Author:

Jones David T¹²,Kandathil Shaun M¹²^ORCID

Affiliation:

1. Department of Computer Science, University College London, London, UK

2. Biomedical Data Science Laboratory, The Francis Crick Institute, London, UK

Funder

Francis Crick Institute

Cancer Research UK

UK Medical Research Council

Wellcome Trust

European Research Council Advanced Grant

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/34/19/3308/25839647/bty341.pdf

Reference55 articles.

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2. Learning generative models for protein fold families;Balakrishnan;Proteins Struct. Funct. Bioinf,2011

3. EigenTHREADER: analogous protein fold recognition by efficient contact map threading;Buchan;Bioinformatics,2017

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