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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...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2014
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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. |
format | Online Article Text |
id | pubmed-4137739 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
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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