Kandathil, S;
Greener, J;
Jones, DT;
(2019)
Prediction of inter-residue contacts with DeepMetaPSICOV in CASP13.
Proteins
, 87
(12)
pp. 1092-1099.
10.1002/prot.25779.
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Abstract
In this article, we describe our efforts in contact prediction in the CASP13 experiment. We employed a new deep learning-based contact prediction tool, DeepMetaPSICOV (or DMP for short), together with new methods and data sources for alignment generation. DMP evolved from MetaPSICOV and DeepCov and combines the input feature sets used by these methods as input to a deep, fully convolutional residual neural network. We also improved our method for multiple sequence alignment generation and included metagenomic sequences in the search. We discuss successes and failures of our approach and identify areas where further improvements may be possible. DMP is freely available at: https://github.com/psipred/DeepMetaPSICOV.
| Type: | Article |
|---|---|
| Title: | Prediction of inter-residue contacts with DeepMetaPSICOV in CASP13 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1002/prot.25779 |
| Publisher version: | https://doi.org/10.1002/prot.25779 |
| Language: | English |
| Additional information: | © 2019 The Authors. Proteins: Structure, Function, and Bioinformatics published by Wiley Periodicals, Inc. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
| Keywords: | Protein contact prediction, Protein structure prediction, Neural networks, Machine learning, Deep learning, Metagenomics |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10077561 |
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