<p>ModCRE: a structure homology-modeling approach to predict TF binding in cis-regulatory elements</p>

Oriol Fornes; Alberto Meseguer; Joaquim Aguirre-Plans; Patrick Gohl; Patricia Mirela Bota; Rubén Molina-Fernández; Jaume Bonet; Altaïr Chinchilla; Ferran Pegenaute; Oriol Gallego; Narcis Fernandez-Fuentes; Baldomero Oliva

doi:10.7490/f1000research.1119321.1

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Fornes O, Meseguer A, Aguirre-Plans J et al. ModCRE: a structure homology-modeling approach to predict TF binding in cis-regulatory elements [version 1; not peer reviewed]. F1000Research 2022, 11:1508 (poster) (https://doi.org/10.7490/f1000research.1119321.1)

NOTE: it is important to ensure the information in square brackets after the title is included in this citation.

ModCRE: a structure homology-modeling approach to predict TF binding in cis-regulatory elements

Oriol Fornes, Alberto Meseguer, Joaquim Aguirre-Plans, Patrick Gohl, Patricia Mirela Bota, Rubén Molina-Fernández, Jaume Bonet, Altaïr Chinchilla, Ferran Pegenaute, Oriol Gallego, Narcis Fernandez-Fuentes, Baldomero Oliva¹

Published 13 Dec 2022 (https://doi.org/10.7490/f1000research.1119321.1)

Author Affiliations

¹ Pompeu Fabra University, Spain

Copyright © 2022 Fornes O 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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CITE

Published 13 Dec 2022

ModCRE: a structure homology-modeling approach to predict TF binding in cis-regulatory elements
[version 1; not peer reviewed]

Author Affiliations

¹ Pompeu Fabra University, Spain

Presented at

European Conference on Computational Biology (ECCB) 2022

Bioinformatics and Genomics Symposium, 2022

Abstract

Competing Interests

No competing interests were disclosed

Keywords

cis-regulatory modules, transcription factors co-operativity, structure-modeling of enhancers’ complexes and pioneering transcription factors, structure-based learning.

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