Graph transformer neural network for chemical reactivity prediction
Graph transformer neural network for chemical reactivity prediction
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Publisher
Washington: American Chemical Society
Journal title
Language
English
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Publisher
Washington: American Chemical Society
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Scope and Contents
Contents
Optimizing the properties of advanced drug candidates can be facilitated by directly introducing certain chemical groups without having to synthesize the molecules from scratch. However, their chemical complexity often renders reactivity predictions and synthesis planning challenging. Herein, we introduce a graph transformer neural network (GTNN) a...
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Full title
Graph transformer neural network for chemical reactivity prediction
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TN_cdi_proquest_journals_2814106791
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2814106791
Other Identifiers
E-ISSN
2573-2293
DOI
10.26434/chemrxiv-2023-8hdmv
