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Graph transformer neural network for chemical reactivity prediction

Graph transformer neural network for chemical reactivity prediction

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2814106791

Graph transformer neural network for chemical reactivity prediction

About this item

Full title

Graph transformer neural network for chemical reactivity prediction

Publisher

Washington: American Chemical Society

Journal title

ChemRxiv, 2023-05

Language

English

Formats

Publication information

Publisher

Washington: American Chemical Society

More information

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...

Alternative Titles

Full title

Graph transformer neural network for chemical reactivity prediction

Identifiers

Primary Identifiers

Record Identifier

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

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