Cited by 388Protein Structure and DynamicsMachine Learning in BioinformaticsEnzyme Catalysis and Immobilization

Expanding functional protein sequence spaces using generative adversarial networks

Open access
Repecka, Donatas, Jauniskis, Vykintas, Karpus, Laurynas, Rembeza, Elzbieta, Rokaitis, Irmantas, Zrimec, Jan, Poviloniene, Simona, Laurynenas, Audrius +6 more·2021·Nature Machine Intelligence

Published version of a preprint

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Registry

Crossref · 10.1038/s42256-021-00310-5

Cites

81 of 81 references verified0 citation errors · 0 not checkable

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Claims the paper makes

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Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • The model learned evolutionary conservation patterns without being trained on explicit alignment information.

    “This indicates that the model has captured evolutionary conservation patterns without training on explicit alignment information such as with Potts models51, as implemented in direct coupling analysis7,52–55.”

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Authors
Repecka, D., Jauniskis, V., Karpus, L., Rembeza, E., Rokaitis, I., Zrimec, J., Poviloniene, S., Laurynenas, A., Viknander, S., Abuajwa, W., Savolainen, O., Meskys, R., Engqvist, M. K. M., & Zelezniak, A.
Affiliations
  • Chalmers University of Technology (SE)
  • Science for Life Laboratory (SE)
Corresponding author
Zelezniak, Aleksej
Venue
Nature Machine Intelligence
Published
2021-03-04
Volume
3
Issue
4
Pages
324-333
ISSN
2522-5839 (ISSN-L)
OpenAlex
W3135130381
Cited by
388
References
81
Citations by year
2026: 68 · 2025: 70 · 2024: 93 · 2023: 67 · 2022: 51 · 2021: 30 · 2020: 8 · 2019: 1
FWCI
18.98
Type
journal article
Language
en
Open access
Locations
  • Nature Machine Intelligence (publishedVersion)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
  • Chalmers Research (Chalmers University of Technology) (submittedVersion)
Funders
  • Mokslo, Inovaciju ir Technologiju Agentura (31V-59/(1.78)SU-1687)
  • Science for Life Laboratory
  • Vetenskapsrådet (2019-05356, 2018-05973)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Machine Learning in Bioinformatics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Enzyme Catalysis and Immobilization
Keywords
de novo protein design, generative adversarial networks, self-attention, protein sequence space, malate dehydrogenase, enzyme catalysis, protein solubility, protein evolution, amino acid substitutions

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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

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