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学术报告六十七:Modelling and analysis of non-Markovian biochemical reaction networks

时间:2021-07-20 11:07

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报告题目:  Modelling and analysis of non-Markovian biochemical reaction networks

报告人:张家军  教授(中山大学

报告时间:20210721日(1000-11:30 am

报告地点: 腾讯会议270695245  

报告内容:Modeling intracellular processes has long relied on the Markovian assumption. However, as soon as a reactant interacts with its environment, molecular memory definitely exists and its effects cannot be neglected. Since the Markov theory cannot translate directly to modeling and analysis of non-Markovian processes, this leads to many significant challenges. We develop a formulation, namely the stationary generalized chemical-master equation, to model intracellular processes with molecular memory. This formulation converts a non-Markovian question to a Markovian one while keeping the stationary probabilistic behavior unchanged. Both a stationary generalized Fokker–Planck equation and a generalized linear noise approximation are further developed for the fast evaluation of fluctuations. These formulations can have broad applications and may help us discover new biological knowledge.

报告人简历:张家军,中山大学数学学院教授,博士研究生导师。主要从事计算系统生物学和生物信息学研究,在国际重要学术期刊如PNASPhysical Review LettersPLoS Computational BiologyBiophysical JournalSIAM Journal on Applied Mathematics等发表多篇研究论文。主持国家自然科学基金面上项目、国家自然科学青年科学基金项目、广州市珠江科技新星专项等多项科研项目,并作为主要参与人(前三)参与2项国家自然科学重点项目等科研项目。现任中国工业与应用数学学会数学生命科学专业委员会副秘书长、广东省计算数学学会副理事长、中国细胞生物学学会功能基因组信息学与系统生物学分会理事、广东省工业与应用数学学会理事、广东省高性能计算学会理事。获2020世界华人数学家联盟最佳论文奖(若琳奖)。

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