Machine learning modelling of chemical reaction characteristics: yesterday, today, tomorrow
A Rakhimbekova
1
,
Valentina A Afonina
1
,
T R Gimadiev
2
,
Ravil N Mukhametgaleev
1
,
Ramil I Nugmanov
1
,
Igor I Baskin
3
,
A. A. Varnek
2, 4
1
2
Publication type: Journal Article
Publication date: 2021-11-01
scimago Q3
wos Q3
SJR: 0.305
CiteScore: 3.0
Impact factor: 1.7
ISSN: 09599436, 1364551X
General Chemistry
Abstract
The synthesis of the desired chemical compound is the main task of synthetic organic chemistry. The predictions of reaction conditions and some important quantitative characteristics of chemical reactions as yield and reaction rate can substantially help in the development of optimal synthetic routes and assessment of synthesis cost. Theoretical assessment of these parameters can be performed with the help of modern machine-learning approaches, which use available experimental data to develop predictive models called quantitative or qualitative structure–reactivity relationship (QSRR) modelling. In the article, we review the state-of-the-art in the QSRR area and give our opinion on emerging trends in this field.
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Total citations:
12
Citations from 2025:
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(8.33%)
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GOST
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Madzhidov T. I. et al. Machine learning modelling of chemical reaction characteristics: yesterday, today, tomorrow // Mendeleev Communications. 2021. Vol. 31. No. 6. pp. 769-780.
GOST all authors (up to 50)
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Madzhidov T. I., Rakhimbekova A., Afonina V. A., Gimadiev T. R., Mukhametgaleev R. N., Nugmanov R. I., Baskin I. I., Varnek A. A. Machine learning modelling of chemical reaction characteristics: yesterday, today, tomorrow // Mendeleev Communications. 2021. Vol. 31. No. 6. pp. 769-780.
Cite this
RIS
Copy
TY - JOUR
DO - 10.1016/j.mencom.2021.11.003
UR - https://doi.org/10.1016/j.mencom.2021.11.003
TI - Machine learning modelling of chemical reaction characteristics: yesterday, today, tomorrow
T2 - Mendeleev Communications
AU - Madzhidov, Timur I
AU - Rakhimbekova, A
AU - Afonina, Valentina A
AU - Gimadiev, T R
AU - Mukhametgaleev, Ravil N
AU - Nugmanov, Ramil I
AU - Baskin, Igor I
AU - Varnek, A. A.
PY - 2021
DA - 2021/11/01
PB - OOO Zhurnal "Mendeleevskie Soobshcheniya"
SP - 769-780
IS - 6
VL - 31
SN - 0959-9436
SN - 1364-551X
ER -
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BibTex (up to 50 authors)
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@article{2021_Madzhidov,
author = {Timur I Madzhidov and A Rakhimbekova and Valentina A Afonina and T R Gimadiev and Ravil N Mukhametgaleev and Ramil I Nugmanov and Igor I Baskin and A. A. Varnek},
title = {Machine learning modelling of chemical reaction characteristics: yesterday, today, tomorrow},
journal = {Mendeleev Communications},
year = {2021},
volume = {31},
publisher = {OOO Zhurnal "Mendeleevskie Soobshcheniya"},
month = {nov},
url = {https://doi.org/10.1016/j.mencom.2021.11.003},
number = {6},
pages = {769--780},
doi = {10.1016/j.mencom.2021.11.003}
}
Cite this
MLA
Copy
Madzhidov, Timur I., et al. “Machine learning modelling of chemical reaction characteristics: yesterday, today, tomorrow.” Mendeleev Communications, vol. 31, no. 6, Nov. 2021, pp. 769-780. https://doi.org/10.1016/j.mencom.2021.11.003.