Prediction of interresidue contacts with DeepMetaPSICOV in CASP13.
Shaun M Kandathil
Joe G Greener
David T Jones
10779/crick.11559027.v1
https://crick.figshare.com/articles/journal_contribution/Prediction_of_interresidue_contacts_with_DeepMetaPSICOV_in_CASP13_/11559027
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. This article is protected by copyright. All rights reserved.
2020-01-09 16:42:31
Deep learning
Machine learning
Metagenomics
Neural networks
Protein contact prediction
Protein structure prediction
deep learning
machine learning
metagenomics
neural networks
protein contact prediction
protein structure prediction
Jones - sec
06 Biological Sciences
08 Information and Computing Sciences
01 Mathematical Sciences
Bioinformatics