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Predictive chemistry: machine learning for reaction deployment, reaction development, and reaction discovery

The field of predictive chemistry relates to the development of models able to describe how molecules interact and react. It encompasses the long-standing task of computer-aided retrosynthesis, but is far more reaching and ambitious in its goals. In this review, we summarize several areas where pred...

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Detalles Bibliográficos
Autores principales: Tu, Zhengkai, Stuyver, Thijs, Coley, Connor W.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Royal Society of Chemistry 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9811563/
https://www.ncbi.nlm.nih.gov/pubmed/36743887
http://dx.doi.org/10.1039/d2sc05089g
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author Tu, Zhengkai
Stuyver, Thijs
Coley, Connor W.
author_facet Tu, Zhengkai
Stuyver, Thijs
Coley, Connor W.
author_sort Tu, Zhengkai
collection PubMed
description The field of predictive chemistry relates to the development of models able to describe how molecules interact and react. It encompasses the long-standing task of computer-aided retrosynthesis, but is far more reaching and ambitious in its goals. In this review, we summarize several areas where predictive chemistry models hold the potential to accelerate the deployment, development, and discovery of organic reactions and advance synthetic chemistry.
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spelling pubmed-98115632023-02-03 Predictive chemistry: machine learning for reaction deployment, reaction development, and reaction discovery Tu, Zhengkai Stuyver, Thijs Coley, Connor W. Chem Sci Chemistry The field of predictive chemistry relates to the development of models able to describe how molecules interact and react. It encompasses the long-standing task of computer-aided retrosynthesis, but is far more reaching and ambitious in its goals. In this review, we summarize several areas where predictive chemistry models hold the potential to accelerate the deployment, development, and discovery of organic reactions and advance synthetic chemistry. The Royal Society of Chemistry 2022-11-28 /pmc/articles/PMC9811563/ /pubmed/36743887 http://dx.doi.org/10.1039/d2sc05089g Text en This journal is © The Royal Society of Chemistry https://creativecommons.org/licenses/by/3.0/
spellingShingle Chemistry
Tu, Zhengkai
Stuyver, Thijs
Coley, Connor W.
Predictive chemistry: machine learning for reaction deployment, reaction development, and reaction discovery
title Predictive chemistry: machine learning for reaction deployment, reaction development, and reaction discovery
title_full Predictive chemistry: machine learning for reaction deployment, reaction development, and reaction discovery
title_fullStr Predictive chemistry: machine learning for reaction deployment, reaction development, and reaction discovery
title_full_unstemmed Predictive chemistry: machine learning for reaction deployment, reaction development, and reaction discovery
title_short Predictive chemistry: machine learning for reaction deployment, reaction development, and reaction discovery
title_sort predictive chemistry: machine learning for reaction deployment, reaction development, and reaction discovery
topic Chemistry
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9811563/
https://www.ncbi.nlm.nih.gov/pubmed/36743887
http://dx.doi.org/10.1039/d2sc05089g
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AT coleyconnorw predictivechemistrymachinelearningforreactiondeploymentreactiondevelopmentandreactiondiscovery