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Please use this identifier to cite or link to this item: http://hdl.handle.net/10119/13669

Title: 機械学習を用いた水溶液にひそむ動的秩序の抽出
Other Titles: Extraction of dynamical hidden order of water by mining simulation data
Authors: Dam, Hieu Chi
Keywords: データマイニング
Issue Date: 15-Jun-2016
Abstract: ミクロなスケールでみた水分子の振る舞いには,ランダムに見えて幅広い多様性がある.それは水が,小さな分子量(M=18)に対して,比較的大きな静電気双極子モーメントを持ち,お互いに“粘りつく”ように緊密な相互作用をして存在しているからである.また複雑なエネルギーランドスケープを持ち,様々な局所構造をとる.周りとの相互作用が大きい水分子の動きは,その相互作用を通じて周りの環境に関する情報を取り入れている.この“振る舞い”を,データマイニングするにあたり,自然言語処理的な“文脈”の解釈を行う可能性を念頭に置いて,解析系を構築した. : Water molecules with their electrostatic dipole moments and characteristic hydrogen bond network have tight interaction to each other as well as to proteins in solutions. The water molecules are moving under the interactions with the surrounding water molecules and information about the local chemical environment is implicitly included in their dynamical behaviors. By applying data mining techniques to the simulation data of protein solution, we have constructed an analysis system for analyzing the dynamical behavior of water molecules for extracting the hidden dynamical structure of protein solution.
Description: 若手研究(B)
Language: jpn
URI: http://hdl.handle.net/10119/13669
Appears in Collections:2015年度 (FY 2015)

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