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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Bibliographic Details
Published in:Nature communications 2021-10, Vol.12 (1), p.5800-11, Article 5800
Main Authors: Trinquier, Jeanne, Uguzzoni, Guido, Pagnani, Andrea, Zamponi, Francesco, Weigt, Martin
Format: Article
Language:English
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