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Comparison of Two Methods Forecasting Binding Rate of Plasma Protein

By introducing the descriptors calculated from the molecular structure, the binding rates of plasma protein (BRPP) with seventy diverse drugs are modeled by a quantitative structure-activity relationship (QSAR) technique. Two algorithms, heuristic algorithm (HA) and support vector machine (SVM), are...

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Detalles Bibliográficos
Autores principales: Hongjiu, Liu, Yanrong, Hu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4137739/
https://www.ncbi.nlm.nih.gov/pubmed/25161695
http://dx.doi.org/10.1155/2014/957154
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author Hongjiu, Liu
Yanrong, Hu
author_facet Hongjiu, Liu
Yanrong, Hu
author_sort Hongjiu, Liu
collection PubMed
description By introducing the descriptors calculated from the molecular structure, the binding rates of plasma protein (BRPP) with seventy diverse drugs are modeled by a quantitative structure-activity relationship (QSAR) technique. Two algorithms, heuristic algorithm (HA) and support vector machine (SVM), are used to establish linear and nonlinear models to forecast BRPP. Empirical analysis shows that there are good performances for HA and SVM with cross-validation correlation coefficients R (cv) (2) of 0.80 and 0.83. Comparing HA with SVM, it was found that SVM has more stability and more robustness to forecast BRPP.
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spelling pubmed-41377392014-08-26 Comparison of Two Methods Forecasting Binding Rate of Plasma Protein Hongjiu, Liu Yanrong, Hu Comput Math Methods Med Research Article By introducing the descriptors calculated from the molecular structure, the binding rates of plasma protein (BRPP) with seventy diverse drugs are modeled by a quantitative structure-activity relationship (QSAR) technique. Two algorithms, heuristic algorithm (HA) and support vector machine (SVM), are used to establish linear and nonlinear models to forecast BRPP. Empirical analysis shows that there are good performances for HA and SVM with cross-validation correlation coefficients R (cv) (2) of 0.80 and 0.83. Comparing HA with SVM, it was found that SVM has more stability and more robustness to forecast BRPP. Hindawi Publishing Corporation 2014 2014-08-04 /pmc/articles/PMC4137739/ /pubmed/25161695 http://dx.doi.org/10.1155/2014/957154 Text en Copyright © 2014 L. Hongjiu and H. Yanrong. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Hongjiu, Liu
Yanrong, Hu
Comparison of Two Methods Forecasting Binding Rate of Plasma Protein
title Comparison of Two Methods Forecasting Binding Rate of Plasma Protein
title_full Comparison of Two Methods Forecasting Binding Rate of Plasma Protein
title_fullStr Comparison of Two Methods Forecasting Binding Rate of Plasma Protein
title_full_unstemmed Comparison of Two Methods Forecasting Binding Rate of Plasma Protein
title_short Comparison of Two Methods Forecasting Binding Rate of Plasma Protein
title_sort comparison of two methods forecasting binding rate of plasma protein
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4137739/
https://www.ncbi.nlm.nih.gov/pubmed/25161695
http://dx.doi.org/10.1155/2014/957154
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