2021
DOI: 10.1021/acs.jproteome.1c00156
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Identification and Characterization of Species-Specific Severe Acute Respiratory Syndrome Coronavirus 2 Physicochemical Properties

Abstract: There is an urgent need to elucidate the underlying mechanisms of coronavirus disease (COVID-19) so that vaccines and treatments can be devised. Severe acute respiratory syndrome coronavirus 2 has genetic similarity with bats and pangolin viruses, but a comprehensive understanding of the functions of its proteins at the amino acid sequence level is lacking. A total of 4320 sequences of human and nonhuman coronaviruses was retrieved from the Global Initiative on Sharing All Influenza Data and the National Cente… Show more

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Cited by 4 publications
(2 citation statements)
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“…Next, we extracted enzyme features at amino acid and global sequence-levels as additional informative inputs. The amino acid-level features capture the physicochemical properties of individual amino acid residues within a protein and are of importance in the development of predictive models for protein classification. , The global sequence-levels features capture the characteristics of a whole sequence and have been shown to help solve protein classification problems . When amino acid- and global sequence-level features were incorporated into the CESR model, the new C/AA/GS model outperformed the CESR model in all evaluation metrics (Table S4 and Section S7).…”
Section: Resultsmentioning
confidence: 99%
“…Next, we extracted enzyme features at amino acid and global sequence-levels as additional informative inputs. The amino acid-level features capture the physicochemical properties of individual amino acid residues within a protein and are of importance in the development of predictive models for protein classification. , The global sequence-levels features capture the characteristics of a whole sequence and have been shown to help solve protein classification problems . When amino acid- and global sequence-level features were incorporated into the CESR model, the new C/AA/GS model outperformed the CESR model in all evaluation metrics (Table S4 and Section S7).…”
Section: Resultsmentioning
confidence: 99%
“…The IBCGA uses an intelligent evolutionary algorithm ( Ho et al, 2004a ), which is good at deriving an optimized SVM with feature selection. The IBCGA has been successfully applied in solving several biological problems ( Yerukala Sathipati et al, 2016 , 2019 ; Yerukala Sathipati and Ho, 2017 , 2018 , 2020 , 2021 ).…”
Section: Methodsmentioning
confidence: 99%