Skip to main content

Prediction of Mutations in H5N1 Hemagglutinins from Influenza A Virus

Buy Article:

$63.00 plus tax (Refund Policy)

Abstract:

In this study, we determine the mutation relation among 333 H5N1 hemagglutinins of influenza A viruses according to their amino acid and RNA codon sequences. Then, we calculate seven probabilistic numbers, which have been developed by us since 1999, for each amino acid in these hemagglutinins. With the seven numeric numbers as independents and the probability of occurrence of mutation at each hemagglutinin position as depend- ent, we use the logistic regression to model 967 missense point mutations from 333 hemagglutinins to get the population estimates. Thereafter, we predict the future mutation positions in H5N1 hemagglutinin. Finally, we use the translation probabilities between RNA codons and mutated amino acids to predict the would-be-mutated amino acids in H5N1 hemagglutinin.





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

Document Type: Research Article

DOI: http://dx.doi.org/10.2174/092986606778777533

Affiliations: Computational Mutation Project, DreamSciTech Consulting, 301, Building 12, Nanyou A-zone,Jiannan Road, Shenzhen, Guangdong Province CN-518054, China.

Publication date: October 1, 2006

More about this publication?
  • 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.
ben/ppl/2006/00000013/00000010/art00003
dcterms_title,dcterms_description,pub_keyword
6
5
20
40
5

Access Key

Free Content
Free content
New Content
New content
Open Access Content
Open access content
Subscribed Content
Subscribed content
Free Trial Content
Free trial content
Cookie Policy
X
Cookie Policy
ingentaconnect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more