Efficient generative modeling of protein sequences using simple autoregressive models

Generative models emerge as promising candidates for novel sequence-data driven approaches to protein design, and for the extraction of structural and functional information about proteins deeply hidden in rapidly growing sequence databases. Here we propose simple autoregressive models as highly acc...

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Detalles Bibliográficos
Autores principales: Trinquier, Jeanne, Uguzzoni, Guido, Pagnani, Andrea, Zamponi, Francesco, Weigt, Martin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8490405/
https://www.ncbi.nlm.nih.gov/pubmed/34608136
http://dx.doi.org/10.1038/s41467-021-25756-4

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8490405/
https://www.ncbi.nlm.nih.gov/pubmed/34608136
http://dx.doi.org/10.1038/s41467-021-25756-4

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