Getting to Know Your Neighbor: Protein Structure Prediction Comes of Age with Contextual Machine Learning-Reference-Cited by-同舟云学术

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Getting to Know Your Neighbor: Protein Structure Prediction Comes of Age with Contextual Machine Learning

Published:2020-05-01 Issue:5 Volume:27 Page:796-814
ISSN:1557-8666
Container-title:Journal of Computational Biology
language:en
Short-container-title:Journal of Computational Biology

Author:

Hanson Jack¹,Paliwal Kuldip K.¹,Litfin Thomas²,Yang Yuedong³,Zhou Yaoqi²

Affiliation:

1. Institute for Intelligent & Integrated Systems, Signal Processing Laboratory, Griffith University, Brisbane, Australia.

2. Institute for Glycomics and School of Information and Communication Technology, Griffith University, Gold Coast, Australia.

3. School of Data and Computer Science, Sun-Yat Sen University, Guangzhou, China.

Publisher

Mary Ann Liebert Inc

Subject

Computational Theory and Mathematics,Computational Mathematics,Genetics,Molecular Biology,Modeling and Simulation

Link

https://www.liebertpub.com/doi/pdf/10.1089/cmb.2019.0193

Reference142 articles.

1. DNCON2: improved protein contact prediction using two-level deep convolutional neural networks

2. Randomized Subspace Learning for Proline Cis-Trans Isomerization Prediction

3. End-to-End Differentiable Learning of Protein Structure

4. Gapped BLAST and PSI-BLAST: a new generation of protein database search programs

5. Principles that Govern the Folding of Protein Chains

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2. Machine learning in computational modelling of membrane protein sequences and structures: From methodologies to applications;Computational and Structural Biotechnology Journal;2023

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4. Sequence-based prediction of protein binding regions and drug–target interactions;Journal of Cheminformatics;2022-02-08

5. SPOT-Contact-LM: improving single-sequence-based prediction of protein contact map using a transformer language model;Bioinformatics;2022-02-01

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