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Identification of encoding proteins related to SARS-CoV

By sampling 100 encoding proteins from SARS-coronavirus (SARS-CoV, NC 004718) and other six coronaviruses and selecting 23 variables through stepwise multiple regression (SMR) from 172 variables, the multiple linear regression (MLR) model was established with good results of the quantitative modelli...

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Detalles Bibliográficos
Autores principales: Mei, Hu, Sun, Lili, Zhou, Yuan, Xiong, Qing, Li, Zhiliang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Science in China Press 2004
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7089014/
https://www.ncbi.nlm.nih.gov/pubmed/32214714
http://dx.doi.org/10.1360/03wb0198
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author Mei, Hu
Sun, Lili
Zhou, Yuan
Xiong, Qing
Li, Zhiliang
author_facet Mei, Hu
Sun, Lili
Zhou, Yuan
Xiong, Qing
Li, Zhiliang
author_sort Mei, Hu
collection PubMed
description By sampling 100 encoding proteins from SARS-coronavirus (SARS-CoV, NC 004718) and other six coronaviruses and selecting 23 variables through stepwise multiple regression (SMR) from 172 variables, the multiple linear regression (MLR) model was established with good results of the quantitative modelling correlation coefficient R (2) = 0.645 and the cross-validation correlation coefficient R (CV)(2) = 0.375. After removing 4 outliers, the quantitative modelling and cross-validation correlation coefficients were R (2)= 0.743 and R (CV)(2) = 0.543, respectively.
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spelling pubmed-70890142020-03-23 Identification of encoding proteins related to SARS-CoV Mei, Hu Sun, Lili Zhou, Yuan Xiong, Qing Li, Zhiliang Chin Sci Bull Articles By sampling 100 encoding proteins from SARS-coronavirus (SARS-CoV, NC 004718) and other six coronaviruses and selecting 23 variables through stepwise multiple regression (SMR) from 172 variables, the multiple linear regression (MLR) model was established with good results of the quantitative modelling correlation coefficient R (2) = 0.645 and the cross-validation correlation coefficient R (CV)(2) = 0.375. After removing 4 outliers, the quantitative modelling and cross-validation correlation coefficients were R (2)= 0.743 and R (CV)(2) = 0.543, respectively. Science in China Press 2004 /pmc/articles/PMC7089014/ /pubmed/32214714 http://dx.doi.org/10.1360/03wb0198 Text en © Science in China Press 2004 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Articles
Mei, Hu
Sun, Lili
Zhou, Yuan
Xiong, Qing
Li, Zhiliang
Identification of encoding proteins related to SARS-CoV
title Identification of encoding proteins related to SARS-CoV
title_full Identification of encoding proteins related to SARS-CoV
title_fullStr Identification of encoding proteins related to SARS-CoV
title_full_unstemmed Identification of encoding proteins related to SARS-CoV
title_short Identification of encoding proteins related to SARS-CoV
title_sort identification of encoding proteins related to sars-cov
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7089014/
https://www.ncbi.nlm.nih.gov/pubmed/32214714
http://dx.doi.org/10.1360/03wb0198
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