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1、基因调控网络：数学模型与仿真,马宏宾系统所,纲要,必要的说明问题与背景模型与仿真总结与展望参考文献,有向图Bayesian网络Boolean网络及推广常微分方程“定性”微分方程偏微分方程随机模型基于规则的形式方法,必要的说明,我完全不懂生物学；我为什么要讲这个？我讲的侧重点在哪？,内容完全基于：童维上传Modeling and Simulation of Genetic Regulatory Systems:A Literature Review,问题与背景,什么是基因调控网络？细胞、DNA、蛋白质、基因、基因网络为什么要研究基因调控网络？从分子水平认识细胞组织的功能。基因调控网络与复杂性了解
2、基因调控网络，对我们有什么启发？,问题与背景,基因和蛋白质Genes code for proteins that are essential for development and functioning of organism:gene expression,问题与背景,基因表达的调控：不同层次Gene expression controlled by proteins produced by other genes:regulatory interactions,问题与背景,基因调控网络：Genetic regulatory network consists of set of gene
3、s,proteins,small molecules,and their mutual regulatory interactions。Development and functioning of organisms cell emerges from interactions in genetic regulatory networks。,问题与背景,例子：,Choice between alternative developmental pathways controlled by network of genes,proteins,and mutual regulatory intera
4、ctions。,基因调控网络的复杂性Large networksComplex cells has many components that can interact in complex ways.Dynamics processes are hard to understand by intuitive approaches alone.Genetic regulatory networks have complicated interactions far beyond correlation of gene expression patterns.Clustering cannot r
5、eveal causal connections between genes.为什么需要数学建模与仿真？precise and unambiguous description of network of interactionssystematical derivation of behavioral predictions,问题与背景,问题与背景,目标我们想知道：Which genes are expressed?When and where in the organisms?To which extent?Are there any universal laws?Can we predic
6、t the evolution of the network?How to predict the evolution of the network?,问题与背景,途径实验、建模、仿真：,模型：有向图,模型：有向图,模型：Baysian network,模型：Baysian network,模型：Boolean network,模型：Boolean network,模型：Boolean network,Truth tables State-transition diagram,模型：Generalized logical network,模型：Nonlinear ODE,Negative fe
7、edbackGene encodes a protein inhibiting its own expressionimportant for homeostasis,maintenance of system near a desired stateSteady state analysisTransient behavior simulation,模型：Nonlinear ODE,模型：Nonlinear ODE,Positive feedbackGene encodes a protein activating its own expression.important for diffe
8、rentiation,evolution towards one of two alternative states of systemSteady statesTransient behaviors,模型：Nonlinear ODE,Applications:,模型：Piecewise-linear ODE,模型：Qualitative Differential Equation,QDE:Abstraction of the formQualitative value x:Qualitative function fi:QSIM algorithmQualitative behaviorsQ
9、ualitative simulation,模型：Spatially Distributed Model,Configuration：Discrete model:Continuous model:boundary conditions:,模型：Stochastic Model,模型：Stochastic Model,Time evolution of p(X,t)：master equation:Stochastic simulation:use r.v.and,模型：Stochastic Model,Simulations:Applications:,模型：Rule-based forma
10、lism,Knowledge base Expert system?Facts：Rules：,总结与展望,总结与展望,Computer tools for modeling and simulation will be necessary to understand genetic regulatory processesVariety of approaches available,representing genetic regulatory systems on different levels of abstractionChoice of approach depends on ai
11、m of analysis and on available information:knowledge on reaction mechanismsquantitative data on model parameters and gene expression levelsSerious applications are beginning to emerge,参考文献,Hidde De Jong,Modeling and Simulation of Genetic Regulatory Systems:A Literature Review,Journal Of Computationa
12、l Biology,9(1),2002.Harley H.McAdams,Adam Arkin,Simulation Of Prokaryotic Genetic Circuits,Annu.Rev.Biophys.Biomol.Struct.1998.27:199224.Paul Smolen,Douglas A.Baxter And John H.Byrne,Modeling Transcriptional Control in Gene NetworksMethods,Recent Results,and Future Directions,Bulletin of Mathematica
13、l Biology(2000)62,247292.Christophe Roos,Facing Biological Complexity From One Cell to a Multicellular Organism,Technology BIOINFORMATICS.Eric Alm and Adam P Arkin,Biological networks,Current Opinion in Structural Biology,2003,13:193202.Olivier Cinquin,Jacques Demongeot,Positive and negative feedback:striking a balance between necessary antagonists,Journal of Theoretical Biology,216(2),pp229-241(2002),谢谢大家！,
