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学術情報メディアセンター > イベント情報 > 【臨時開催】学術情報メディアセンターセミナー 「因果関係ネットワークの解明」

【臨時開催】学術情報メディアセンターセミナー 「因果関係ネットワークの解明」

Post date:2017/10/16

京都大学学術情報メディアセンターでは、各分野でご活躍の講師をお招きし、それぞれの研究開発活動の内容や現在抱えている課題についてご紹介いただき、参加者を含めて広く議論を行う機会として、月例セミナーを開催しています。
11月9日の学術情報メディアセンターセミナーでは、UC San Diego の George Sugihara 教授をお招きし、ご講演いただきます。学内外を問わず多数の方のご参加をお待ちしています。

日時 2017/11/09(木)16時30分〜18時00分
会場 京都大学 学術情報メディアセンター北館 4階 404大会議室
http://www.kyoto-u.ac.jp/ja/access/campus/yoshida/map6r_y/
(上記URLのマップ中、42番の建物です)
定員
参加費用 無料
参加申込み 不要
主催 京都大学 学術情報メディアセンター
お問い合わせ 京都大学 学術情報メディアセンター  夏川 浩明
電話番号:075-753-7473
メール:natsukawa * viz.media.kyoto-u.ac.jp (*を@に変えてください)
プログラム ◆16時30分~18時00分 【使用言語:英語、同時通訳なし】
講演者: George Sugihara (UC San Diego, Physical Oceanography Research Division, Scripps Institution of Oceanography ・ Professor)

講演題目: Mathematical Biology Without Equations: Uncovering Invisible Causal Networks

講演概要: Since before the time of Aristotle and the natural philosophers, reductionism has played a foundational role in western scientific thought. The premise of reductionism is that systems can be broken down into constituent pieces and studied independently, then reassembled to understand the behavior of the system as a whole. It embodies the classical linear perspective. This approach has been successful in developing basic physical laws and especially in engineering where linear analysis dominates and systems are purposefully designed that way. However, reductionism is not universally applicable for natural complex systems found in biology and elsewhere where behavior is driven, not by a few factors acting independently, but by complex interactions between many components acting together in time –nonlinear dynamic systems.
Nonlinearity in living systems means that its parts are interdependent –variables do not act in a mutually independent manner; rather they interact, and as a consequence associations (correlations) between them will change as the overall system context (state) changes. This problem is highlighted when extrapolating the results of single-factor experiments to nature, and surely contributes to the frustrating disconnect between experimental findings and clinical outcomes in drug trials. Indeed, while everyone knows Berkeley’s 1710 dictum “correlation does not imply causation” few realize that for nonlinear systems the converse “causation does not imply correlation” is also true. This conundrum runs counter to deeply ingrained heuristic thinking that is at the basis of modern science. Biological systems (esp. ecosystems) are particularly perverse on this issue by exhibiting mirage correlations that can continually cause us to rethink relationships we thought we understood.
Here we examine a minimalist paradigm, empirical dynamics, for studying non-linear systems and a method that can distinguish causality from correlation. It is a data-driven approach that uses time series information to study a system holistically by reconstructing its attractor – a geometric object that embodies the rules of a full set of equations for the system. The ideas are intuitive and will be illustrated with examples from ecology, epidemiology and genetics.
備考

【情報交換会のご案内】 セミナー終了後、情報交換会を開催いたします。参加希望者は、上記問い合わせ先までご連絡ください(場所は未定)。

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