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下記のとおり、伊藤公人准教授（北海道大学人獣共通感染症リサーチセンター）
を囲んで、第4回数学連携サロンを開催致しますので、ご案内申し上げます。
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　　　　　　　　　　記

日　時： 2008年10月14日(火)　10時〜
会　場： 電子科学研究所1階会議室（札幌市北区北20条西10丁目）
　　　　　http://www.math.sci.hokudai.ac.jp/sympo/hokudai_ries.html
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　　　　　創成科学研究棟2Fと渡り廊下で接続されております。

講演者： 伊藤公人准教授（北海道大学人獣共通感染症リサーチセンター）

タイトル：
Patterns of amino acid substitutions on the hemagglutinin molecules of
antigenic variants of H3N2 influenza A viruses.

アブストラクト：
The rapid development of molecular biology during the last two decades
has accelerated the accumulation of results from genetic and
experimental studies on zoonotic pathogens. Massive biological data sets
enhance the chance to find important factors that are essential for
zoonosis control and have not been addressed so far. At the same time,
however, the dramatic increase in data volume causes difficulty in
analysis by hand, or even by existing computer programs. In this regard,
the larger the data sets on individual zoonotic pathogens that are
accumulated in the databases, the more important role bioinformatics may
well play in comprehensive studies to develop effective strategies for
control of zoonoses.
Here we present bioinformatics technologies developed for influenza
control. Influenza A viruses are zoonotic pathogens that have been
isolated from various animals, including humans. All subtypes of
influenza A viruses are maintained in aquatic birds and they are known
to be the source of these viruses. Hemagglutinin (HA) is the major
target of antibodies that neutralize viral infectivity. HA undergoes
antigenic changes with the accumulation of amino acid substitutions. The
structural changes in antigenic sites of HA are responsible for the
viral escape from neutralizing antibodies induced by previous infection
or vaccination. Thus influenza virus strains that acquire novel
antigenic structures cause annual epidemics worldwide, and it is
believed that eradication of influenza is difficult to achieve.
Moreover, the high rate of mutation in the HA gene causes substantial
difficulties to select an effective vaccine strain prior to each
influenza season.
To predict future antigenic changes, it is important to understand the
evolution of the virus associated with antigenic changes caused by amino
acid substitutions in the past. We introduce bioinformatics technologies
developed at the author’s laboratory, aiming to predict the future
evolution of influenza viruses. The techniques include sequence data
analysis employing information theory to find patterns of evolution of
viruses, and molecular modeling using homology modeling and molecular
dynamics simulation of viral proteins. Through these technologies, we
investigate the past, current and future evolution of influenza viruses.

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