CORDIS Project
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This project develops advanced deep learning frameworks to model organic and enzymatic reactions, focusing on selectivity in chemical processes. By improving prediction accuracy, it aims to facilitate the discovery of sustainable synthesis pathways in chemistry.
The exploration of reactions is a central topic in chemistry.
Compared to the success of machine learning for molecules, the modeling of reactions is lagging behind, especially for stereo- and regioselective reactions.
Since current efforts toward sustainable synthesis such as asymmetric organocatalysis or biocatalysis rely on the accurate prediction of enantio- and regioselective reaction pathways, new modeling approaches are needed.
The proposed project aims toward developing new, data-driven…
TECHNISCHE UNIVERSITAET WIEN
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