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Prediction of Mutations in H3N2 Hemagglutinins of Influenza A Virus from North America Based on Different Datasets

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Abstract:

With rapid increase in influenza A virus database, an important issue is whether the predictions are similar based on different datasets. Here we stratify 482 H3N2 hemagglutinins from influenza A virus in North America to different datasets. The predictions are made using logistic regression. The results show that the different datasets have significant impact on the predictions.





Keywords: Hemagglutinin; influenza; logistic regression; mutation; prediction

Document Type: Research Article

DOI: https://doi.org/10.2174/092986608783489571

Publication date: 2008-02-01

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  • Protein & Peptide Letters publishes short papers in all important aspects of protein and peptide research, including structural studies, recombinant expression, function, synthesis, enzymology, immunology, molecular modeling, drug design etc. Manuscripts must have a significant element of novelty, timeliness and urgency that merit rapid publication. Reports of crystallisation, and preliminary structure determinations of biologically important proteins are acceptable. Purely theoretical papers are also acceptable provided they provide new insight into the principles of protein/peptide structure and function.
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