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volume 11 issue 1 publication number 14798

Transformer-based artificial neural networks for the conversion between chemical notations

Publication typeJournal Article
Publication date2021-07-20
scimago Q1
wos Q1
SJR0.874
CiteScore6.7
Impact factor3.9
ISSN20452322
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.

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GOST Copy
Krasnov L. et al. Transformer-based artificial neural networks for the conversion between chemical notations // Scientific Reports. 2021. Vol. 11. No. 1. 14798
GOST all authors (up to 50) Copy
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
RIS |
Cite this
RIS Copy
TY - JOUR
DO - 10.1038/s41598-021-94082-y
UR - https://www.nature.com/articles/s41598-021-94082-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
PB - Springer Nature
IS - 1
VL - 11
PMID - 34285269
SN - 2045-2322
ER -
BibTex
Cite this
BibTex (up to 50 authors) Copy
@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://www.nature.com/articles/s41598-021-94082-y},
number = {1},
pages = {14798},
doi = {10.1038/s41598-021-94082-y}
}