Abstract
Influenza A viruses cause a significant threat to public health as highlighted by the recent introduction of the swine-derived H1N1 virus (pandemic H1N1/09) into human populations. Pandemics were primarily initiated by introduction from animal sources and successive adaptation among humans through human-to-human transmission. We established a sequence alignment-free clustering method “BLSOM”, which can analyze and compare all influenza A virus genome sequences on one map. Separation according to host animal, subtype and epidemic year could be efficiently visualized. Notably, H1N1/09 strains have oligonucleotide and codon compositions clearly distinct from those of seasonal human flu strains. This enabled us to make inferences about directional changes of H1N1/09 sequences in the near future and to list codons and oligonucleotides with the potential of reduction in H1N1/09 sequences. The strong visualization power of BLSOM also provides surveillance strategies for efficiently detecting potential precursors to pandemic viruses.
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Iwasaki, Y., Wada, K., Itoh, M., Ikemura, T., Abe, T. (2011). A Novel Bioinformatics Strategy to Predict Directional Changes of Influenza A Virus Genome Sequences. In: Laaksonen, J., Honkela, T. (eds) Advances in Self-Organizing Maps. WSOM 2011. Lecture Notes in Computer Science, vol 6731. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21566-7_20
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DOI: https://doi.org/10.1007/978-3-642-21566-7_20
Publisher Name: Springer, Berlin, Heidelberg
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