Journal of Physical Chemistry Letters, volume 12, issue 38, pages 9213-9219
Size Doesn't Matter: Predicting Physico- or Biochemical Properties Based on Dozens of Molecules
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Science Data Software, LLC, 14909 Forest Landing Circle, Rockville, Maryland 20850, United States
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Publication type: Journal Article
Publication date: 2021-09-16
Quartile SCImago
Q1
Quartile WOS
Q1
Impact factor: 5.7
ISSN: 19487185
Physical and Theoretical Chemistry
General Materials Science
Abstract
The use of machine learning in chemistry has become a common practice. At the same time, despite the success of modern machine learning methods, the lack of data limits their use. Using a transfer learning methodology can help solve this problem. This methodology assumes that a model built on a sufficient amount of data captures general features of the chemical compound structure on which it was trained and that the further reuse of these features on a data set with a lack of data will greatly improve the quality of the new model. In this paper, we develop this approach for small organic molecules, implementing transfer learning with graph convolutional neural networks. The paper shows a significant improvement in the performance of the models for target properties with a lack of data. The effects of the data set composition on the model's quality and the applicability domain of the resulting models are also considered.
Citations by journals
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1
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Journal of Membrane Science Letters
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Journal of Membrane Science Letters
1 publication, 20%
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iScience
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iScience
1 publication, 20%
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Artificial Intelligence in the Life Sciences
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Artificial Intelligence in the Life Sciences
1 publication, 20%
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Journal of Chemical Information and Modeling
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Journal of Chemical Information and Modeling
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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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Elsevier
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Elsevier
3 publications, 60%
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American Chemical Society (ACS)
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American Chemical Society (ACS)
1 publication, 20%
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1
2
3
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- We do not take into account publications that without a DOI.
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Karpov K. et al. Size Doesn't Matter: Predicting Physico- or Biochemical Properties Based on Dozens of Molecules // Journal of Physical Chemistry Letters. 2021. Vol. 12. No. 38. pp. 9213-9219.
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Karpov K., Mitrofanov A., Korolev V., Tkachenko V. Size Doesn't Matter: Predicting Physico- or Biochemical Properties Based on Dozens of Molecules // Journal of Physical Chemistry Letters. 2021. Vol. 12. No. 38. pp. 9213-9219.
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TY - JOUR
DO - 10.1021/acs.jpclett.1c02477
UR - https://doi.org/10.1021%2Facs.jpclett.1c02477
TI - Size Doesn't Matter: Predicting Physico- or Biochemical Properties Based on Dozens of Molecules
T2 - Journal of Physical Chemistry Letters
AU - Tkachenko, Valery
AU - Karpov, Kirill
AU - Mitrofanov, Artem
AU - Korolev, Vadim
PY - 2021
DA - 2021/09/16 00:00:00
PB - American Chemical Society (ACS)
SP - 9213-9219
IS - 38
VL - 12
SN - 1948-7185
ER -
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@article{2021_Karpov,
author = {Valery Tkachenko and Kirill Karpov and Artem Mitrofanov and Vadim Korolev},
title = {Size Doesn't Matter: Predicting Physico- or Biochemical Properties Based on Dozens of Molecules},
journal = {Journal of Physical Chemistry Letters},
year = {2021},
volume = {12},
publisher = {American Chemical Society (ACS)},
month = {sep},
url = {https://doi.org/10.1021%2Facs.jpclett.1c02477},
number = {38},
pages = {9213--9219},
doi = {10.1021/acs.jpclett.1c02477}
}
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MLA
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Karpov, Kirill, et al. “Size Doesn't Matter: Predicting Physico- or Biochemical Properties Based on Dozens of Molecules.” Journal of Physical Chemistry Letters, vol. 12, no. 38, Sep. 2021, pp. 9213-9219. https://doi.org/10.1021%2Facs.jpclett.1c02477.