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2L-PCA: a two-level principal component analyzer for quantitative drug design and its applications
A two-level principal component predictor (2L-PCA) was proposed based on the principal component analysis (PCA) approach. It can be used to quantitatively analyze various compounds and peptides about their functions or potentials to become useful drugs. One level is for dealing with the physicochemi...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Impact Journals LLC
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5642577/ https://www.ncbi.nlm.nih.gov/pubmed/29050302 http://dx.doi.org/10.18632/oncotarget.19757 |
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author | Du, Qi-Shi Wang, Shu-Qing Xie, Neng-Zhong Wang, Qing-Yan Huang, Ri-Bo Chou, Kuo-Chen |
author_facet | Du, Qi-Shi Wang, Shu-Qing Xie, Neng-Zhong Wang, Qing-Yan Huang, Ri-Bo Chou, Kuo-Chen |
author_sort | Du, Qi-Shi |
collection | PubMed |
description | A two-level principal component predictor (2L-PCA) was proposed based on the principal component analysis (PCA) approach. It can be used to quantitatively analyze various compounds and peptides about their functions or potentials to become useful drugs. One level is for dealing with the physicochemical properties of drug molecules, while the other level is for dealing with their structural fragments. The predictor has the self-learning and feedback features to automatically improve its accuracy. It is anticipated that 2L-PCA will become a very useful tool for timely providing various useful clues during the process of drug development. |
format | Online Article Text |
id | pubmed-5642577 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Impact Journals LLC |
record_format | MEDLINE/PubMed |
spelling | pubmed-56425772017-10-18 2L-PCA: a two-level principal component analyzer for quantitative drug design and its applications Du, Qi-Shi Wang, Shu-Qing Xie, Neng-Zhong Wang, Qing-Yan Huang, Ri-Bo Chou, Kuo-Chen Oncotarget Research Paper A two-level principal component predictor (2L-PCA) was proposed based on the principal component analysis (PCA) approach. It can be used to quantitatively analyze various compounds and peptides about their functions or potentials to become useful drugs. One level is for dealing with the physicochemical properties of drug molecules, while the other level is for dealing with their structural fragments. The predictor has the self-learning and feedback features to automatically improve its accuracy. It is anticipated that 2L-PCA will become a very useful tool for timely providing various useful clues during the process of drug development. Impact Journals LLC 2017-08-01 /pmc/articles/PMC5642577/ /pubmed/29050302 http://dx.doi.org/10.18632/oncotarget.19757 Text en Copyright: © 2017 Du et al. http://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/) 3.0 (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Paper Du, Qi-Shi Wang, Shu-Qing Xie, Neng-Zhong Wang, Qing-Yan Huang, Ri-Bo Chou, Kuo-Chen 2L-PCA: a two-level principal component analyzer for quantitative drug design and its applications |
title | 2L-PCA: a two-level principal component analyzer for quantitative drug design and its applications |
title_full | 2L-PCA: a two-level principal component analyzer for quantitative drug design and its applications |
title_fullStr | 2L-PCA: a two-level principal component analyzer for quantitative drug design and its applications |
title_full_unstemmed | 2L-PCA: a two-level principal component analyzer for quantitative drug design and its applications |
title_short | 2L-PCA: a two-level principal component analyzer for quantitative drug design and its applications |
title_sort | 2l-pca: a two-level principal component analyzer for quantitative drug design and its applications |
topic | Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5642577/ https://www.ncbi.nlm.nih.gov/pubmed/29050302 http://dx.doi.org/10.18632/oncotarget.19757 |
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