Spectrochimica Acta - Part A: Molecular and Biomolecular Spectroscopy, volume 279, pages 121442
Can machine learning methods accurately predict the molar absorption coefficient of different classes of dyes?
Publication type: Journal Article
Publication date: 2022-10-01
Quartile SCImago
Q2
Quartile WOS
Q1
Impact factor: 4.4
ISSN: 13861425
Spectroscopy
Analytical Chemistry
Atomic and Molecular Physics, and Optics
Instrumentation
Abstract
In this article, we provide a convenient tool for all researchers to predict the value of the molar absorption coefficient for a wide number of dyes without any computer costs. The new model is based on RFR method (ALogPS, OEstate + Fragmentor + QNPR) and is able to predict the molar absorption coefficient with an accuracy (5-fold cross-validation RMSE) of 0.26 log unit. This accuracy was achieved due to the fact that the model was trained on data for more than 20,000 unique dye molecules. To our knowledge, this is the first model for predicting the molar absorption coefficient trained on such a large and diverse set of dyes. The model is available at https://ochem.eu/article/145413. We hope that the new model will allow researchers to predict dyes with practically significant spectral characteristics and verify existing experimental data.
Citations by journals
1
|
|
Physical Chemistry Chemical Physics
|
Physical Chemistry Chemical Physics
1 publication, 10%
|
Computational Biology and Chemistry
|
Computational Biology and Chemistry
1 publication, 10%
|
Journal of Chemical Theory and Computation
|
Journal of Chemical Theory and Computation
1 publication, 10%
|
World Journal of Gastroenterology
|
World Journal of Gastroenterology
1 publication, 10%
|
Small Methods
|
Small Methods
1 publication, 10%
|
Journal of Computational Science
|
Journal of Computational Science
1 publication, 10%
|
Chemical Physics Letters
|
Chemical Physics Letters
1 publication, 10%
|
Spectrochimica Acta - Part A: Molecular and Biomolecular Spectroscopy
|
Spectrochimica Acta - Part A: Molecular and Biomolecular Spectroscopy
1 publication, 10%
|
APL Machine Learning
|
APL Machine Learning
1 publication, 10%
|
1
|
Citations by publishers
1
2
3
4
|
|
Elsevier
|
Elsevier
4 publications, 40%
|
Royal Society of Chemistry (RSC)
|
Royal Society of Chemistry (RSC)
1 publication, 10%
|
American Chemical Society (ACS)
|
American Chemical Society (ACS)
1 publication, 10%
|
Baishideng Publishing Group
|
Baishideng Publishing Group
1 publication, 10%
|
Wiley
|
Wiley
1 publication, 10%
|
American Institute of Physics (AIP)
|
American Institute of Physics (AIP)
1 publication, 10%
|
1
2
3
4
|
- 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.
{"yearsCitations":{"type":"bar","data":{"show":true,"labels":[2022,2023,2024],"ids":[0,0,0],"codes":[0,0,0],"imageUrls":["","",""],"datasets":[{"label":"Citations number","data":[1,6,3],"backgroundColor":["#3B82F6","#3B82F6","#3B82F6"],"percentage":["10","60","30"],"barThickness":null}]},"options":{"indexAxis":"x","maintainAspectRatio":true,"scales":{"y":{"ticks":{"precision":0,"autoSkip":false,"font":{"family":"Montserrat"},"color":"#000000"}},"x":{"ticks":{"stepSize":1,"precision":0,"font":{"family":"Montserrat"},"color":"#000000"}}},"plugins":{"legend":{"position":"top","labels":{"font":{"family":"Montserrat"},"color":"#000000"}},"title":{"display":true,"text":"Citations per year","font":{"size":24,"family":"Montserrat","weight":600},"color":"#000000"}}}},"journals":{"type":"bar","data":{"show":true,"labels":["Physical Chemistry Chemical Physics","Computational Biology and Chemistry","Journal of Chemical Theory and Computation","World Journal of Gastroenterology","Small Methods","Journal of Computational Science","Chemical Physics Letters","Spectrochimica Acta - Part A: Molecular and Biomolecular Spectroscopy","APL Machine Learning"],"ids":[1773,16827,58,19469,4145,21058,5579,6337,35222],"codes":[0,0,0,0,0,0,0,0,0],"imageUrls":["\/storage\/images\/resized\/leiAYcRDGTSl5B1eCnwpSGqmDEUEfDPPoYisFGhT_medium.webp","\/storage\/images\/resized\/GDnYOu1UpMMfMMRV6Aqle4H0YLLsraeD9IP9qScG_medium.webp","\/storage\/images\/resized\/iLiQsFqFaSEx6chlGQ5fbAwF6VYU3WWa08hkss0g_medium.webp","\/storage\/images\/resized\/bKOjgSt9mSGUD9fzKZyqcKSIgDCDSMd1ZWjJOZzx_medium.webp","\/storage\/images\/resized\/bRyGpdm98BkAUYiK1YFNpl5Z7hPu6Gd87gbIeuG3_medium.webp","\/storage\/images\/resized\/GDnYOu1UpMMfMMRV6Aqle4H0YLLsraeD9IP9qScG_medium.webp","\/storage\/images\/resized\/GDnYOu1UpMMfMMRV6Aqle4H0YLLsraeD9IP9qScG_medium.webp","\/storage\/images\/resized\/GDnYOu1UpMMfMMRV6Aqle4H0YLLsraeD9IP9qScG_medium.webp","\/storage\/images\/resized\/ARM4e6URKRsbRZvIF0vFis9DjxGloBjnBYJXbHmZ_medium.webp"],"datasets":[{"label":"","data":[1,1,1,1,1,1,1,1,1],"backgroundColor":["#3B82F6","#3B82F6","#3B82F6","#3B82F6","#3B82F6","#3B82F6","#3B82F6","#3B82F6","#3B82F6"],"percentage":[10,10,10,10,10,10,10,10,10],"barThickness":13}]},"options":{"indexAxis":"y","maintainAspectRatio":false,"scales":{"y":{"ticks":{"precision":0,"autoSkip":false,"font":{"family":"Montserrat"},"color":"#000000"}},"x":{"ticks":{"stepSize":null,"precision":0,"font":{"family":"Montserrat"},"color":"#000000"}}},"plugins":{"legend":{"position":"top","labels":{"font":{"family":"Montserrat"},"color":"#000000"}},"title":{"display":true,"text":"Journals","font":{"size":24,"family":"Montserrat","weight":600},"color":"#000000"}}}},"publishers":{"type":"bar","data":{"show":true,"labels":["Elsevier","Royal Society of Chemistry (RSC)","American Chemical Society (ACS)","Baishideng Publishing Group","Wiley","American Institute of Physics (AIP)"],"ids":[17,123,40,7719,11,250],"codes":[0,0,0,0,0,0],"imageUrls":["\/storage\/images\/resized\/GDnYOu1UpMMfMMRV6Aqle4H0YLLsraeD9IP9qScG_medium.webp","\/storage\/images\/resized\/leiAYcRDGTSl5B1eCnwpSGqmDEUEfDPPoYisFGhT_medium.webp","\/storage\/images\/resized\/iLiQsFqFaSEx6chlGQ5fbAwF6VYU3WWa08hkss0g_medium.webp","\/storage\/images\/resized\/bKOjgSt9mSGUD9fzKZyqcKSIgDCDSMd1ZWjJOZzx_medium.webp","\/storage\/images\/resized\/bRyGpdm98BkAUYiK1YFNpl5Z7hPu6Gd87gbIeuG3_medium.webp","\/storage\/images\/resized\/ARM4e6URKRsbRZvIF0vFis9DjxGloBjnBYJXbHmZ_medium.webp"],"datasets":[{"label":"","data":[4,1,1,1,1,1],"backgroundColor":["#3B82F6","#3B82F6","#3B82F6","#3B82F6","#3B82F6","#3B82F6"],"percentage":[40,10,10,10,10,10],"barThickness":13}]},"options":{"indexAxis":"y","maintainAspectRatio":false,"scales":{"y":{"ticks":{"precision":0,"autoSkip":false,"font":{"family":"Montserrat"},"color":"#000000"}},"x":{"ticks":{"stepSize":null,"precision":0,"font":{"family":"Montserrat"},"color":"#000000"}}},"plugins":{"legend":{"position":"top","labels":{"font":{"family":"Montserrat"},"color":"#000000"}},"title":{"display":true,"text":"Publishers","font":{"size":24,"family":"Montserrat","weight":600},"color":"#000000"}}}}}
Metrics
Cite this
GOST |
RIS |
BibTex
Cite this
GOST
Copy
Ksenofontov A. A. et al. Can machine learning methods accurately predict the molar absorption coefficient of different classes of dyes? // Spectrochimica Acta - Part A: Molecular and Biomolecular Spectroscopy. 2022. Vol. 279. p. 121442.
GOST all authors (up to 50)
Copy
Ksenofontov A. A., Lukanov M. M., Bocharov P. S. Can machine learning methods accurately predict the molar absorption coefficient of different classes of dyes? // Spectrochimica Acta - Part A: Molecular and Biomolecular Spectroscopy. 2022. Vol. 279. p. 121442.
Cite this
RIS
Copy
TY - JOUR
DO - 10.1016/j.saa.2022.121442
UR - https://doi.org/10.1016%2Fj.saa.2022.121442
TI - Can machine learning methods accurately predict the molar absorption coefficient of different classes of dyes?
T2 - Spectrochimica Acta - Part A: Molecular and Biomolecular Spectroscopy
AU - Ksenofontov, Alexander A
AU - Lukanov, Michail M
AU - Bocharov, Pavel S
PY - 2022
DA - 2022/10/01 00:00:00
PB - Elsevier
SP - 121442
VL - 279
SN - 1386-1425
ER -
Cite this
BibTex
Copy
@article{2022_Ksenofontov,
author = {Alexander A Ksenofontov and Michail M Lukanov and Pavel S Bocharov},
title = {Can machine learning methods accurately predict the molar absorption coefficient of different classes of dyes?},
journal = {Spectrochimica Acta - Part A: Molecular and Biomolecular Spectroscopy},
year = {2022},
volume = {279},
publisher = {Elsevier},
month = {oct},
url = {https://doi.org/10.1016%2Fj.saa.2022.121442},
pages = {121442},
doi = {10.1016/j.saa.2022.121442}
}