Bioinformatics models for predicting antigenic variants of influenza A/H3N2 virus
Autor: | Min-Shi Lee, Chao A. Hsiung, Chin-Yu Ko, Yu-Chieh Liao |
---|---|
Rok vydání: | 2008 |
Předmět: |
Statistics and Probability
Models Molecular Orthomyxoviridae Molecular Sequence Data Hemagglutinin (influenza) Hemagglutinin Glycoproteins Influenza Virus medicine.disease_cause Bioinformatics Biochemistry Antigenic drift Virus Phylogenetics Influenza A virus medicine Amino Acid Sequence Molecular Biology Peptide sequence Antigens Viral Phylogeny Models Statistical biology Influenza A Virus H3N2 Subtype Antigenic shift Computational Biology biology.organism_classification Virology Antigenic Variation Computer Science Applications Computational Mathematics Computational Theory and Mathematics biology.protein Regression Analysis |
Zdroj: | Bioinformatics (Oxford, England). 24(4) |
ISSN: | 1367-4811 |
Popis: | Motivation: Continual and accumulated mutations in hemagglutinin (HA) protein of influenza A virus generate novel antigenic strains that cause annual epidemics. Results: We propose a model by incorporating scoring and regression methods to predict antigenic variants. Based on collected sequences of influenza A/H3N2 viruses isolated between 1971 and 2002, our model can be used to accurately predict the antigenic variants in 1999–2004 (agreement rate = 91.67%). Twenty amino acid positions identified in our model contribute significantly to antigenic difference and are potential immunodominant positions. Contact: hsiung@nhri.org.tw Supplementary information: The supplementary information includes 62 amino acid sequences of H3N2 viruses and 277 pair-wise antigenic distances. |
Databáze: | OpenAIRE |
Externí odkaz: |