Nonlinear Dynamics in Mesoscopic Chemical Systems Zhonghuai Hou ( 侯中怀 ) Department of Chemical Physics Hefei National Lab of Physical Science at Microscale.

Slides:



Advertisements
Similar presentations
Non-Markovian dynamics of small genetic circuits Lev Tsimring Institute for Nonlinear Science University of California, San Diego Le Houches, 9-20 April,
Advertisements

Theory. Modeling of Biochemical Reaction Systems 2 Assumptions: The reaction systems are spatially homogeneous at every moment of time evolution. The.
A model of one biological 2-cells complex Akinshin A.A., Golubyatnikov V.P. Sobolev Institute of Mathematics SB RAS, Bukharina T.A., Furman D.P. Institute.
Molecular mechanisms of long-term memory
Multiscale Stochastic Simulation Algorithm with Stochastic Partial Equilibrium Assumption for Chemically Reacting Systems Linda Petzold and Yang Cao University.
Collaboration with Federico Vázquez - Mallorca - Spain The continuum description of individual-based models Cristóbal López.
Optical Tweezers F scatt F grad 1. Velocity autocorrelation function from the Langevin model kinetic property property of equilibrium fluctuations For.
Signal Processing in Single Cells Tony 03/30/2005.
Stochasticity in molecular systems biology
Deterministic and Stochastic Analysis of Simple Genetic Networks Adiel Loinger MS.c Thesis of under the supervision of Ofer Biham.
Deterministic and Stochastic Analysis of Simple Genetic Networks Adiel Loinger Ofer Biham Azi Lipshtat Nathalie Q. Balaban.
Two Approaches to Multiphysics Modeling Sun, Yongqi FAU Erlangen-Nürnberg.
The Dynamics of Intracellular Ca2+ Signals
Adiel Loinger Ofer Biham Nathalie Q. Balaban Azi Lipshtat
Photo-transduction and related mathematical problems D. Holcman, Weizmann Institute of Science.
Nonlinear Physics Textbook: –R.C.Hilborn, “Chaos & Nonlinear Dynamics”, 2 nd ed., Oxford Univ Press (94,00) References: –R.H.Enns, G.C.McGuire, “Nonlinear.
Seth Weinberg Acknowledgements: Xiao Wang, Yan Hao, Gregory Smith
Gating Modeling of Ion Channels Chu-Pin Lo ( 羅主斌 ) Department of Applied Mathematics Providence University 2010/01/12 (Workshop on Dynamics for Coupled.
Absorbing Phase Transitions
Cristóbal López IMEDEA, Palma de Mallorca, Spain From microscopic dynamics to macroscopic evolution.
Temperature Oscillations in a Compartmetalized Bidisperse Granular Gas C. K. Chan 陳志強 Institute of Physics, Academia Sinica, Dept of Physics,National Central.
Dynamics of Coupled Oscillators-Theory and Applications
Biological Modeling of Neural Networks Week 8 – Noisy input models: Barrage of spike arrivals Wulfram Gerstner EPFL, Lausanne, Switzerland 8.1 Variation.
Dynamical network motifs: building blocks of complex dynamics in biological networks Valentin Zhigulin Department of Physics, Caltech, and Institute for.
Novel size effect in mesoscopic chemical oscillation systems Zhonghuai Hou ( 侯中怀 ) Sep. 2008, Hefei Department of Chemical Physics Hefei National Lab for.
AMATH 382: Computational Modeling of Cellular Systems Dynamic modelling of biochemical, genetic, and neural networks Introductory Lecture, Jan. 6, 2014.
Stochastic modeling of molecular reaction networks Daniel Forger University of Michigan.
Correlation-Induced Oscillations in Spatio-Temporal Excitable Systems Andre Longtin Physics Department, University of Ottawa Ottawa, Canada.
Introduction to Self-Organization
Spatiotemporal dynamics of coupled nonlinear oscillators on complex networks Zhonghuai Hou( 侯中怀 ) Beijing Department of Chemical Physics Hefei.
The chemotaxis network is able to extract once the input signal varies slower relative to the response time of the chemotaxis network. Under an input signal.
Stochastic Thermodynamics in Mesoscopic Chemical Oscillation Systems
Biological Modeling of Neural Networks Week 8 – Noisy output models: Escape rate and soft threshold Wulfram Gerstner EPFL, Lausanne, Switzerland 8.1 Variation.
Dynamics of ITG driven turbulence in the presence of a large spatial scale vortex flow Zheng-Xiong Wang, 1 J. Q. Li, 1 J. Q. Dong, 2 and Y. Kishimoto 1.
By Rosalind Allen Regulatory networks Biochemical noise.
1 Stochasticity and robustness Steve Andrews Brent lab, Basic Sciences Division, FHCRC Lecture 5 of Introduction to Biological Modeling Oct. 20, 2010.
Study on synchronization of coupled oscillators using the Fokker-Planck equation H.Sakaguchi Kyushu University, Japan Fokker-Planck equation: important.
Some figures adapted from a 2004 Lecture by Larry Liebovitch, Ph.D. Chaos BIOL/CMSC 361: Emergence 1/29/08.
Introduction: Brain Dynamics Jaeseung Jeong, Ph.D Department of Bio and Brain Engineering, KAIST.
Janine Bolliger 1, Julien C. Sprott 2, David J. Mladenoff 1 1 Department of Forest Ecology & Management, University of Wisconsin-Madison 2 Department of.
Stability and Dynamics in Fabry-Perot cavities due to combined photothermal and radiation-pressure effects Francesco Marino 1, Maurizio De Rosa 2, Francesco.
Circadian Rhythms 안용열 ( 물리학과 ). Index Intro - What is the circadian rhythm? Mechanism in reality How can we understand it?  Nonlinear dynamics –Limit.
Double RF system at IUCF Shaoheng Wang 06/15/04. Contents 1.Introduction of Double RF System 2.Phase modulation  Single cavity case  Double cavity case.
Engineered Gene Circuits Jeff Hasty. How do we predict cellular behavior from the genome? Sequence data gives us the components, now how do we understand.
Optimal Strategy in E. coli Chemotaxis: An Information Theoretic Approach Lin Wang and Sima Setayeshgar Department of Physics, Indiana University, Bloomington,
Content: 1) Dynamics of beta-cells. Polynomial model and gate noise. 2) The influence of noise. Phenomenological. 3) The Gaussian method. 4) Wave block.
Biochemical Reactions: how types of molecules combine. Playing by the Rules + + 2a2a b c.
1 Low Dimensional Behavior in Large Systems of Coupled Oscillators Edward Ott University of Maryland.
Optimal Strategy in E. coli Chemotaxis: An Information Theoretic Approach Lin Wang and Sima Setayeshgar Department of Physics, Indiana University, Bloomington,
Control and Synchronization of Chaos Li-Qun Chen Department of Mechanics, Shanghai University Shanghai Institute of Applied Mathematics and Mechanics Shanghai.
Computational Mechanics of ECAs, and Machine Metrics.
Neural Synchronization via Potassium Signaling. Neurons Interactions Neurons can communicate with each other via chemical or electrical synapses. Chemical.
Nonlinear Dynamics and Non- equilibrium Thermodynamics in Mesoscopic Chemical Systems Zhonghuai Hou ( 侯中怀 ) Shanghai , TACC2008
ECE-7000: Nonlinear Dynamical Systems 2. Linear tools and general considerations 2.1 Stationarity and sampling - In principle, the more a scientific measurement.
Transition to Burst Synchronization on Complex Neuron Networks Zhonghuai Hou( 侯中怀 ) Nanjing Department of Chemical Physics Hefei National Lab of.
Arthur Straube PATTERNS IN CHAOTICALLY MIXING FLUID FLOWS Department of Physics, University of Potsdam, Germany COLLABORATION: A. Pikovsky, M. Abel URL:
Dynamics theory and experiment 1. Atomic motion and energy flow in the reacting molecules. 2. Atomic motion and energy flow in the reacting surface/substrate.
Dynamic of Networks at the Edge of Chaos
Interaction between vortex flow and microturbulence Zheng-Xiong Wang (王正汹) Dalian University of Technology, Dalian, China West Lake International Symposium.
The chemotaxis network is able to extract as much as information possible once the input signal varies slower relative to the response time of the chemotaxis.
Novel size effect in mesoscopic chemical oscillation systems
                                                                                                                                                                                                  
Jingkui Wang, Marc Lefranc, Quentin Thommen  Biophysical Journal 
Optimization Based Design of Robust Synthetic
AMATH 882: Computational Modeling of Cellular Systems
Stability and Dynamics in Fabry-Perot cavities due to combined photothermal and radiation-pressure effects Francesco Marino1,4, Maurizio De Rosa2, Francesco.
Biointelligence Laboratory, Seoul National University
Time-dependent picture for trapping of an anomalous massive system
Volume 6, Issue 4, Pages e3 (April 2018)
Ankit Gupta, Benjamin Hepp, Mustafa Khammash  Cell Systems 
Presentation transcript:

Nonlinear Dynamics in Mesoscopic Chemical Systems Zhonghuai Hou ( 侯中怀 ) Department of Chemical Physics Hefei National Lab of Physical Science at Microscale University of Science & Technology of China

Genetic Toggle Switch In E. Coli Nature 2000 Two or more stable states under same external constraints Reactive/Inactive bistabe CO+O2 on Pt filed tip PRL1999 Travelling/Target/Spiral/Soliton … waves PEEM Image CO Oxidation on Pt PRL 1995 Calcium Spiral Wave in Cardiac Tissues Nature 1998 Temporally Periodic Variations of Concentrations Rate Oscillation CO+O2 Nano- particle Catal.Today 2003 Synthetic transcriptional oscillator (Repressilator) Nature 2002 Stationary spatial structures in reaction-diffusion systems Cellular Pattern CO Oxidation on Pt PRL 2001 Turing Pattern BZ Reaction System PNAS 2003  Oscillation  Multistability  Patterns  Waves  Chaos Nonlinear Chemical Dynamics  far-from equilibrium, self-organized, complex, spatio-temporal structures Aperiodic/Initial condition sensitivity/strange attractor … Strange Attractor The Lorenz System Chemical turbulence CO+O2 on Pt Surface Science 2001 Collective behavior involving many molecular units

Sub-cellular reactions - gene expression - ion-channel gating - calcium signaling … Heterogeneous catalysis - field emitter tips - nanostructured composite surface - small metal particles Mesoscopic Reaction Systems N, V (Small) Molecular Fluctuation Nonlinear Chemical Dynamics ?

Noise Induced Pattern Transition Z.Hou, et al., PRL 81, 2854 (1998) Disorder sustained spiral waves Z.Hou, et al., PRL 89, (2002) Noise/Disorder  Noise and disorder play constructive roles in nonlinear dynamical systems Taming Chaos by Topological Disorder F. Qi, Z.Hou, H. Xin, PRL 91, (2003)

Stochastic Chemical Kinetics  chemical reactions are essentially stochastic, discrete processes Discrete Brownian Motion of X : Prob. Evolution: Master equation Sample Trajectory: Langevin equation stochastic state variable probability distribution

Chemical Langevin equation (CLE) N Species, M reaction channels, well-stirred in V Reaction j: Rate:  Molecular fluctuation (Internal noise)  Deterministic kinetics for  Each channel contributes independently to internal noise:  Fast numerical simulation

The Brusselator  Deterministic bifurcation Fixed Point: Hopf bifurcation:

Noise Induced Oscillation  Stochastic dynamics FFT

Optimal System Size Optimal System size for mesoscopic chemical oscillation Z. Hou, H. Xin. ChemPhysChem 5, 407(2004)

Seems to be common …  Internal Noise Stochastic Resonance in a Circadian Clock System J.Chem.Phys. 119, 11508(2003)  Optimal Particle Size for Rate Oscillation in CO Oxidation on Nanometer-Sized Palladium(Pd) Particles J.Phys.Chem.B 108, 17796(2004)  Internal Noise Stochastic Resonance of synthetic gene network Chem.Phys.Lett. 401,307(2005)  Effects of Internal Noise for rate oscillations during CO oxidation on platinum(Pt) surfaces J.Chem.Phys. 122, (2005)  System size bi-resonance for intracellular calcium signaling ChemPhysChem 5, 1041(2004)  Double-System-Size resonance for spiking activity of coupled HH neurons ChemPhysChem 5, 1602(2004)

Analytical study  Stochastic Normal Form

Analytical study  Stochastic Averaging

Analytical study  Probability distribution of r Fokker- Planck equation Stationary distribution Most probable radius Noise induced oscillation

Analytical study  Auto-correlation function

Analytical study  Power spectrum and SNR Optimal system size:

Analytical study Universal near HB System Dependent Internal Noise Coherent Resonance for Mesoscopic Chemical oscillations: a Fundamental Study. Z. Hou, … ChemPhysChem 7, 1520(2006)

Summary  In mesoscopic chemical systems, molecular fluctuations can induce oscillation even outside the deterministic oscillatory region  Optimal system size exists, where the noise- induced oscillation shows the best performance, characterized by a maximal SNR, a trade off between strength and regularity  Based on stochastic normal form, analytical studies show rather good agreements with the simulation results, uncovering the mechanism of NIO and OSS

Further questions

Acknowledgements Supported by: National science foundation (NSF) Fok Yin Dong education foundation Thank you