Bidirectional Graphormer for Reactivity Understanding: Neural Network Trained to Reaction Atom-to-Atom Mapping Task-Reference-Cited by-同舟云学术

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Bidirectional Graphormer for Reactivity Understanding: Neural Network Trained to Reaction Atom-to-Atom Mapping Task

Published:2022-07-06 Issue:14 Volume:62 Page:3307-3315
ISSN:1549-9596
Container-title:Journal of Chemical Information and Modeling
language:en
Short-container-title:J. Chem. Inf. Model.

Author:

Nugmanov Ramil¹^ORCID,Dyubankova Natalia¹^ORCID,Gedich Andrey²^ORCID,Wegner Joerg Kurt³^ORCID

Affiliation:

1. Janssen Research & Development, Janssen Pharmaceutica N.V., Turnhoutseweg 30, Beerse B-2340, Belgium

2. Arcadia Inc., 28 k2, Bolshoy Sampsonievskiy pr., St. Petersburg 194044, Russia

3. Janssen Research & Development, LLC, 255 Main St, Cambridge, Massachusetts 02142, United States

Publisher

American Chemical Society (ACS)

Subject

Library and Information Sciences,Computer Science Applications,General Chemical Engineering,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jcim.2c00344

Reference41 articles.

1. SMILES, a chemical language and information system. 1. Introduction to methodology and encoding rules

2. Self-referencing embedded strings (SELFIES): A 100% robust molecular string representation

3. Extraction of organic chemistry grammar from unsupervised learning of chemical reactions

4. Atom‐to‐atom Mapping: A Benchmarking Study of Popular Mapping Algorithms and Consensus Strategies

5. The problem of atom-to-atom mapping. An application of genetic algorithms

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