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. 2004;49(19):2037–2040. doi: 10.1360/03wb0198

Identification of encoding proteins related to SARS-CoV

Hu Mei 1,2,3, Lili Sun 2,3, Yuan Zhou 1,2, Qing Xiong 2,3, Zhiliang Li 1,2,
PMCID: PMC7089014  PMID: 32214714

Abstract

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 2CV = 0.375. After removing 4 outliers, the quantitative modelling and cross-validation correlation coefficients were R 2= 0.743 and R 2CV = 0.543, respectively.

Keywords: SARS-CoV, coronavirus, multiple linear regression (MLR), stepwise multiple regression (SMR), encoding protein, identification

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Articles from Chinese Science Bulletin = Kexue Tongbao are provided here courtesy of Nature Publishing Group

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