<p>Substrate specificity prediction of transporters using triplet loss and protein language models</p>

Sima Ataei; Gregory  Butler

doi:10.7490/f1000research.1119960.1

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Ataei S and Butler G. Substrate specificity prediction of transporters using triplet loss and protein language models [version 1; not peer reviewed]. F1000Research 2024, 13:1262 (poster) (https://doi.org/10.7490/f1000research.1119960.1)

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Substrate specificity prediction of transporters using triplet loss and protein language models

Sima Ataei¹, Gregory Butler

Published 21 Oct 2024 (https://doi.org/10.7490/f1000research.1119960.1)

Author Affiliations

¹ Concordia University Gina Cody School of Engineering and Computer Science, Montreal, Québec, Canada

Copyright © 2024 Ataei S and Butler G. This is an open access work distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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CITE

Published 21 Oct 2024

Substrate specificity prediction of transporters using triplet loss and protein language models
[version 1; not peer reviewed]

Sima Ataei¹, Gregory Butler

Author Affiliations

¹ Concordia University Gina Cody School of Engineering and Computer Science, Montreal, Québec, Canada

Presented at

Intelligent Systems for Molecular Biology Conference (ISMB), 2025

Competing Interests

No competing interests were disclosed

Keywords

Few-shot learning, Protein language models, Triplet loss function, transmembrane transport proteins

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