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Dataset of curcumin derivatives for QSAR modeling of anti cancer against P388 cell line
The dataset of curcumin derivatives consists of 45 compounds (Table 1) with their anti cancer biological activity (IC(50)) against P388 cell line. 45 curcumin derivatives were used in the model development where 30 of these compounds were in the training set and the remaining 15 compounds were in th...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5061127/ https://www.ncbi.nlm.nih.gov/pubmed/27752528 http://dx.doi.org/10.1016/j.dib.2016.09.036 |
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author | Eryanti, Yum Zamri, Adel Frimayanti, Neni Supratman, Unang Herlina, Tati |
author_facet | Eryanti, Yum Zamri, Adel Frimayanti, Neni Supratman, Unang Herlina, Tati |
author_sort | Eryanti, Yum |
collection | PubMed |
description | The dataset of curcumin derivatives consists of 45 compounds (Table 1) with their anti cancer biological activity (IC(50)) against P388 cell line. 45 curcumin derivatives were used in the model development where 30 of these compounds were in the training set and the remaining 15 compounds were in the test set. The development of the QSAR model involved the use of the multiple linear regression analysis (MLRA) method. Based on the method, r(2) value, r(2)(CV) value of 0.81, 0.67 were obtained. The QSAR model was also employed to predict the biological activity of compounds in the test set. Predictive correlation coefficient r(2) values of 0.88 were obtained for the test set. |
format | Online Article Text |
id | pubmed-5061127 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-50611272016-10-17 Dataset of curcumin derivatives for QSAR modeling of anti cancer against P388 cell line Eryanti, Yum Zamri, Adel Frimayanti, Neni Supratman, Unang Herlina, Tati Data Brief Data Article The dataset of curcumin derivatives consists of 45 compounds (Table 1) with their anti cancer biological activity (IC(50)) against P388 cell line. 45 curcumin derivatives were used in the model development where 30 of these compounds were in the training set and the remaining 15 compounds were in the test set. The development of the QSAR model involved the use of the multiple linear regression analysis (MLRA) method. Based on the method, r(2) value, r(2)(CV) value of 0.81, 0.67 were obtained. The QSAR model was also employed to predict the biological activity of compounds in the test set. Predictive correlation coefficient r(2) values of 0.88 were obtained for the test set. Elsevier 2016-10-03 /pmc/articles/PMC5061127/ /pubmed/27752528 http://dx.doi.org/10.1016/j.dib.2016.09.036 Text en © 2016 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Data Article Eryanti, Yum Zamri, Adel Frimayanti, Neni Supratman, Unang Herlina, Tati Dataset of curcumin derivatives for QSAR modeling of anti cancer against P388 cell line |
title | Dataset of curcumin derivatives for QSAR modeling of anti cancer against P388 cell line |
title_full | Dataset of curcumin derivatives for QSAR modeling of anti cancer against P388 cell line |
title_fullStr | Dataset of curcumin derivatives for QSAR modeling of anti cancer against P388 cell line |
title_full_unstemmed | Dataset of curcumin derivatives for QSAR modeling of anti cancer against P388 cell line |
title_short | Dataset of curcumin derivatives for QSAR modeling of anti cancer against P388 cell line |
title_sort | dataset of curcumin derivatives for qsar modeling of anti cancer against p388 cell line |
topic | Data Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5061127/ https://www.ncbi.nlm.nih.gov/pubmed/27752528 http://dx.doi.org/10.1016/j.dib.2016.09.036 |
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