<p>Developing sequence-based predictive models for protein-ligand and protein-protein interactions using machine learning strategies</p>

David Medina Ortiz; Pedro Salinas; Fabio  Durán-Verdugo; Álvaro  Olivera-Nappa; Roberto  Uribe-Paredes

doi:10.7490/f1000research.1119570.1

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Medina Ortiz D, Salinas P, Durán-Verdugo F et al. Developing sequence-based predictive models for protein-ligand and protein-protein interactions using machine learning strategies [version 1; not peer reviewed]. F1000Research 2023, 12:970 (poster) (https://doi.org/10.7490/f1000research.1119570.1)

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Developing sequence-based predictive models for protein-ligand and protein-protein interactions using machine learning strategies

David Medina Ortiz¹, Pedro Salinas, Fabio Durán-Verdugo, Álvaro Olivera-Nappa, Roberto Uribe-Paredes

Published 11 Aug 2023 (https://doi.org/10.7490/f1000research.1119570.1)

Author Affiliations

¹ Universidad de Magallanes, Punta Arenas, Chile

Copyright © 2023 Medina Ortiz D et al. 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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Published 11 Aug 2023

Developing sequence-based predictive models for protein-ligand and protein-protein interactions using machine learning strategies
[version 1; not peer reviewed]

David Medina Ortiz¹, Pedro Salinas, Fabio Durán-Verdugo, Álvaro Olivera-Nappa, Roberto Uribe-Paredes

Author Affiliations

¹ Universidad de Magallanes, Punta Arenas, Chile

Presented at

European Conference on Computational Biology (ECCB), 2023

Competing Interests

No competing interests were disclosed

Keywords

Protein networks, machine learning algorithms, protein language models, protein discovery, deep learning architectures

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