Open Access
Scientific Reports, volume 11, issue 1, publication number 14798
Transformer-based artificial neural networks for the conversion between chemical notations
Publication type: Journal Article
Publication date: 2021-07-20
PubMed ID:
34285269
Multidisciplinary
Abstract
We developed a Transformer-based artificial neural approach to translate between SMILES and IUPAC chemical notations: Struct2IUPAC and IUPAC2Struct. The overall performance level of our model is comparable to the rule-based solutions. We proved that the accuracy and speed of computations as well as the robustness of the model allow to use it in production. Our showcase demonstrates that a neural-based solution can facilitate rapid development keeping the required level of accuracy. We believe that our findings will inspire other developers to reduce development costs by replacing complex rule-based solutions with neural-based ones.
Citations by journals
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1
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Chemistry - Methods
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Chemistry - Methods
1 publication, 10%
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European Journal of Drug Metabolism and Pharmacokinetics
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European Journal of Drug Metabolism and Pharmacokinetics
1 publication, 10%
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npj Computational Materials
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npj Computational Materials
1 publication, 10%
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ACS applied materials & interfaces
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ACS applied materials & interfaces
1 publication, 10%
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Journal of Chemical Information and Modeling
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Journal of Chemical Information and Modeling
1 publication, 10%
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Computers and Chemical Engineering
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Computers and Chemical Engineering
1 publication, 10%
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Synlett
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Synlett
1 publication, 10%
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Frontiers in Chemistry
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Frontiers in Chemistry
1 publication, 10%
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Scientific Reports
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Scientific Reports
1 publication, 10%
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1
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Citations by publishers
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1
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3
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Springer Nature
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Springer Nature
3 publications, 30%
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American Chemical Society (ACS)
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American Chemical Society (ACS)
2 publications, 20%
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Wiley
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Wiley
1 publication, 10%
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IEEE
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IEEE
1 publication, 10%
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Elsevier
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Elsevier
1 publication, 10%
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Thieme
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Thieme
1 publication, 10%
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Frontiers Media S.A.
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Frontiers Media S.A.
1 publication, 10%
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1
2
3
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- We do not take into account publications that without a DOI.
- Statistics recalculated only for publications connected to researchers, organizations and labs registered on the platform.
- Statistics recalculated weekly.
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Krasnov L. et al. Transformer-based artificial neural networks for the conversion between chemical notations // Scientific Reports. 2021. Vol. 11. No. 1. 14798
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Krasnov L., Khokhlov I., Fedorov M. V., Sosnin S. Transformer-based artificial neural networks for the conversion between chemical notations // Scientific Reports. 2021. Vol. 11. No. 1. 14798
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TY - JOUR
DO - 10.1038/s41598-021-94082-y
UR - https://doi.org/10.1038%2Fs41598-021-94082-y
TI - Transformer-based artificial neural networks for the conversion between chemical notations
T2 - Scientific Reports
AU - Krasnov, Lev
AU - Khokhlov, Ivan
AU - Fedorov, Maxim V
AU - Sosnin, Sergey
PY - 2021
DA - 2021/07/20 00:00:00
PB - Springer Nature
IS - 1
VL - 11
PMID - 34285269
SN - 2045-2322
ER -
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@article{2021_Krasnov,
author = {Lev Krasnov and Ivan Khokhlov and Maxim V Fedorov and Sergey Sosnin},
title = {Transformer-based artificial neural networks for the conversion between chemical notations},
journal = {Scientific Reports},
year = {2021},
volume = {11},
publisher = {Springer Nature},
month = {jul},
url = {https://doi.org/10.1038%2Fs41598-021-94082-y},
number = {1},
doi = {10.1038/s41598-021-94082-y}
}