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