Literature DB >> 33536642

Machine learning made easy for optimizing chemical reactions.

Jason E Hein.   

Abstract

Keywords:  Chemistry; Computer science; Organic chemistry; Synthesis

Year:  2021        PMID： 33536642     DOI： 10.1038/d41586-021-00209-6

Source DB:  PubMed          Journal:  Nature        ISSN： 0028-0836            Impact factor:   49.962


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  3 in total

1.  Prediction of higher-selectivity catalysts by computer-driven workflow and machine learning.

Authors:  Andrew F Zahrt; Jeremy J Henle; Brennan T Rose; Yang Wang; William T Darrow; Scott E Denmark
Journal:  Science       Date:  2019-01-18       Impact factor: 47.728

2.  Holistic prediction of enantioselectivity in asymmetric catalysis.

Authors:  Jolene P Reid; Matthew S Sigman
Journal:  Nature       Date:  2019-07-17       Impact factor: 49.962
  3 in total
  1 in total

1.  Non-linearity of Metabolic Pathways Critically Influences the Choice of Machine Learning Model.

Authors:  Ophélie Lo-Thong-Viramoutou; Philippe Charton; Xavier F Cadet; Brigitte Grondin-Perez; Emma Saavedra; Cédric Damour; Frédéric Cadet
Journal:  Front Artif Intell       Date:  2022-06-10
  1 in total

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