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CORDIS

Exploring new applications of amino acid covariation analysis in modelling proteins and their complexes

CORDIS provides links to public deliverables and publications of HORIZON projects.

Links to deliverables and publications from FP7 projects, as well as links to some specific result types such as dataset and software, are dynamically retrieved from OpenAIRE .

Publications

Increasing the Accuracy of Single Sequence Prediction Methods Using a Deep Semi-Supervised Learning Framework. (opens in new window)

Author(s): Lewis Moffat; Lewis Moffat; David T. Jones; David T. Jones
Published in: Bioinformatics, Issue 3, 2021, ISSN 1367-4803
Publisher: Oxford University Press
DOI: 10.1093/bioinformatics/btab491

High precision in protein contact prediction using fully convolutional neural networks and minimal sequence features (opens in new window)

Author(s): David T Jones, Shaun M Kandathil
Published in: Bioinformatics, Issue Volume 34, Issue 19, 2018, Page(s) 3308-3315, ISSN 1367-4803
Publisher: Oxford University Press
DOI: 10.1093/bioinformatics/bty341

Design of metalloproteins and novel protein folds using variational autoencoders (opens in new window)

Author(s): Joe G. Greener, Lewis Moffat, David T Jones
Published in: Scientific Reports, Issue 8/1, 2018, ISSN 2045-2322
Publisher: Nature Publishing Group
DOI: 10.1038/s41598-018-34533-1

Deep learning extends de novo protein modelling coverage of genomes using iteratively predicted structural constraints (opens in new window)

Author(s): Joe G. Greener, Shaun M. Kandathil, David T. Jones
Published in: Nature Communications, Issue 10/1, 2019, ISSN 2041-1723
Publisher: Nature Publishing Group
DOI: 10.1038/s41467-019-11994-0

Prediction of interresidue contacts with DeepMetaPSICOV in CASP13 (opens in new window)

Author(s): Shaun M. Kandathil, Joe G. Greener, David T. Jones
Published in: Proteins: Structure, Function, and Bioinformatics, Issue 87/12, 2019, Page(s) 1092-1099, ISSN 0887-3585
Publisher: Wiley-Liss Inc
DOI: 10.1002/prot.25779

Recent developments in deep learning applied to protein structure prediction (opens in new window)

Author(s): Shaun M. Kandathil, Joe G. Greener, David T. Jones
Published in: Proteins: Structure, Function, and Bioinformatics, Issue 87/12, 2019, Page(s) 1179-1189, ISSN 0887-3585
Publisher: Wiley-Liss Inc
DOI: 10.1002/prot.25824

Differentiable molecular simulation can learn all the parameters in a coarse-grained force field for proteins. (opens in new window)

Author(s): Joe G Greener; David T. Jones
Published in: PLoS ONE, Issue 4, 2021, ISSN 1932-6203
Publisher: Public Library of Science
DOI: 10.1371/journal.pone.0256990

Ultrafast end-to-end protein structure prediction enables high-throughput exploration of uncharacterized proteins (opens in new window)

Author(s): Shaun M. Kandathil, Joe G. Greener, Andy M. Lau, David T. Jones
Published in: PNAS, 2022, ISSN 1091-6490
Publisher: National Academy of Sciences
DOI: 10.1073/pnas.2113348119

Improving protein function prediction with synthetic feature samples created by generative adversarial networks (opens in new window)

Author(s): Cen Wan; Cen Wan; David T. Jones; David T. Jones
Published in: Nature Machine Intelligence, Issue 5, 2020, ISSN 2522-5839
Publisher: Springer Nature
DOI: 10.1101/730143

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