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Artificial intelligence in synthetic chemistry: achievements and prospects

Igor Iosifovich Baskin 1, 2
Igor Iosifovich Baskin
,  , 
Igor' Sergeevich Antipin 2
Igor' Sergeevich Antipin
, 
Aleksandr Alekseevich Varnek 2, 3
Aleksandr Alekseevich Varnek
1 Lomonosov Moscow State University, Faculty of Physics
2 Kazan State University A. Butlerov, Institute of Chemistry
3 Laboratory of Chemoinformatics (UMR 7140 CNRS/UniStra), University of Strasbourg, France
10.1070/RCR4746
Published 30 November 2016
Review , RCR4746, Volume 86, Issue 11, 1127-1156
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Baskin I. I. et al. Artificial intelligence in synthetic chemistry: achievements and prospects // Russian Chemical Reviews. 2016. Vol. 86. No. 11. pp. 1127-1156.
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Baskin I. I., Madzhidov T. I., Antipin I. S., Varnek A. A. Artificial intelligence in synthetic chemistry: achievements and prospects // Russian Chemical Reviews. 2016. Vol. 86. No. 11. pp. 1127-1156.
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TY - JOUR
DO - 10.1070/RCR4746
UR - https://rcr.colab.ws/publications/10.1070/RCR4746
TI - Artificial intelligence in synthetic chemistry: achievements and prospects
T2 - Russian Chemical Reviews
AU - Baskin, Igor Iosifovich
AU - Madzhidov, Timur Ismailovich
AU - Antipin, Igor' Sergeevich
AU - Varnek, Aleksandr Alekseevich
PY - 2016
DA - 2016/11/30
PB - ANO Editorial Board of the journal Uspekhi Khimii
SP - 1127-1156
IS - 11
VL - 86
ER -
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@article{2016_Baskin,
author = {Igor Iosifovich Baskin and Timur Ismailovich Madzhidov and Igor' Sergeevich Antipin and Aleksandr Alekseevich Varnek},
title = {Artificial intelligence in synthetic chemistry: achievements and prospects},
journal = {Russian Chemical Reviews},
year = {2016},
volume = {86},
publisher = {ANO Editorial Board of the journal Uspekhi Khimii},
month = {Nov},
url = {https://rcr.colab.ws/publications/10.1070/RCR4746},
number = {11},
pages = {1127--1156},
doi = {10.1070/RCR4746}
}
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Baskin, Igor Iosifovich, et al. “Artificial intelligence in synthetic chemistry: achievements and prospects.” Russian Chemical Reviews, vol. 86, no. 11, Nov. 2016, pp. 1127-1156. https://rcr.colab.ws/publications/10.1070/RCR4746.
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Abstract

The review is devoted to the achievements in analysis of information on chemical reactions using machine learning methods. Four large areas that actively use these methods are outlined: computer-assisted planning of synthesis, analysis and visualization of chemical reaction data, prediction of the quantitative characteristics of reactions and computer-aided design of catalysts.

The bibliography includes 346 references.

Funders

Russian Science Foundation
14-43-00024П