BARTReact: SELFIES-driven precision in reaction modeling

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BARTReact: SELFIES-driven precision in reaction modeling

Farfán, Daniel; Gómez-Márquez, Carolina; Sandoval-Nuñez, Dania; Paredes, Omar; Morales, J. Alejandro

Franklin Open, June 2024, Volume: 7

Journal Article

We introduce Bidirectional and Auto-Regressive Transformer for Reactions (BARTReact), a self-supervised deep learning model designed to predict chemical reactions. Built on the powerful Bidirectional and Auto-Regressive Transformer (BART) architecture, BARTReact is trained using the SELF-referencIng Embedded Strings (SELFIES), a molecular representation that ensures the production of only viable molecules, achieving an outstanding accuracy of 98.6 %.

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Farfán, Daniel | Gómez-Márquez, Carolina | Sandoval-Nuñez, Dania | Paredes, Omar | Morales, J. Alejandro

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