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Autor:
Laura Isigkeit, Tim Hörmann, Espen Schallmayer, Katharina Scholz, Felix F. Lillich, Johanna H. M. Ehrler, Benedikt Hufnagel, Jasmin Büchner, Julian A. Marschner, Jörg Pabel, Ewgenij Proschak, Daniel Merk
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-14 (2024)
Abstract Generative deep learning models enable data-driven de novo design of molecules with tailored features. Chemical language models (CLM) trained on string representations of molecules such as SMILES have been successfully employed to design new
Externí odkaz:
https://doaj.org/article/18a8f717a7c64c0f81f6b3644f448ee3
