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Authors: Keiko Sato ; Toshihide Hara and Masanori Ohya

Affiliation: Tokyo Univiersity of Science, Japan

ISBN: 978-989-758-170-0

Keyword(s): Receptor Binding Domain, H5N1, Code Structure, Sequence Prediction.

Related Ontology Subjects/Areas/Topics: Bioinformatics ; Biomedical Engineering ; Sequence Analysis

Abstract: The changes in the receptor binding domain of influenza A virus hemagglutinin lead to the appearance of new viral strains that evade the immune system. To prepare the future emergence of potentially dangerous outbreaks caused by divergent influenza strains including human-adapted H5N1 strains, it is imperative that we understand the rule stored in the sequence of the receptor binding domain. Information of life is stored as a sequence of nucleotides, and the sequence composed of four nucleotides seems to be a code. It is important to determine the code structure of the sequences. Once we know the code structure, we can make use of mathematical results concerning coding theory for research in life science. In this study, we applied various codes in coding theory to sequence analysis of the 220 loop in the receptor binding domain of H1, H3, H5 and H7 subtype viruses isolated from humans. Sequence diversity in the 220 loop has been observed even within the same hemagglutinin subtype. How ever, we found that the code structure of the 220 loop from the same subtype remains unchanged. Our results indicate that the sequences at the 220 loop have the structure of subtype-specific codes. In addition, in view of these finding, we predicted possible amino acid changes in the 220 loop of H5N1 strains that will emerge in the future. Our method will facilitate understanding of the evolutionary patterns of influenza A viruses, and further help the development of new antiviral drugs and vaccines. (More)

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Paper citation in several formats:
Sato, K.; Hara, T. and Ohya, M. (2016). A Coding Theoretical Approach to Predict Sequence Changes in H5N1 Influenza A Virus Hemagglutinin.In Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 3: BIOINFORMATICS, (BIOSTEC 2016) ISBN 978-989-758-170-0, pages 159-167. DOI: 10.5220/0005659701590167

@conference{bioinformatics16,
author={Keiko Sato. and Toshihide Hara. and Masanori Ohya.},
title={A Coding Theoretical Approach to Predict Sequence Changes in H5N1 Influenza A Virus Hemagglutinin},
booktitle={Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 3: BIOINFORMATICS, (BIOSTEC 2016)},
year={2016},
pages={159-167},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005659701590167},
isbn={978-989-758-170-0},
}

TY - CONF

JO - Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 3: BIOINFORMATICS, (BIOSTEC 2016)
TI - A Coding Theoretical Approach to Predict Sequence Changes in H5N1 Influenza A Virus Hemagglutinin
SN - 978-989-758-170-0
AU - Sato, K.
AU - Hara, T.
AU - Ohya, M.
PY - 2016
SP - 159
EP - 167
DO - 10.5220/0005659701590167

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