Difference between revisions of "Applied/ACMS/absF11"
(→Anne Shiu, U of Chicago) 
(→Carsten Conradi, MPIMagdeburg) 

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{ style="color:black; fontsize:100%" table border="2" cellpadding="10" width="700" cellspacing="20"  { style="color:black; fontsize:100%" table border="2" cellpadding="10" width="700" cellspacing="20"  
    
−   bgcolor="#DDDDDD" align="center" '''  +   bgcolor="#DDDDDD" align="center" '''Multistationarity and switching in mass action networks 
'''  '''  
    
 bgcolor="#DDDDDD"   bgcolor="#DDDDDD"  
−  +  Many biochemical processes can successfully be described by  
+  dynamical systems allowing some form of switching when, depending on their  
+  initial conditions, solutions of the dynamical system end up in different  
+  regions of state space (associated with different biochemical functions):  
+  switching is, for example, the basis of intracellular processes like  
+  cellular signal transduction, information processing and cell cycle control.  
+  Due to predominant parameter uncertainty numerical methods are generally  
+  difficult to apply to realistic models originating in Systems Biology. Hence  
+  analytical tools that allow the direct computation of states and parameters  
+  where switching occurs are desirable. Here conditions for mass action  
+  networks are presented that take the form of linear inequality systems.  
}  }  
</center>  </center> 
Revision as of 17:36, 4 November 2011
Contents
 1 Sigurd Angenent, UWMadison
 2 John Finn, Los Alamos
 3 Jay Bardhan, Rush Univ
 4 Omar Morandi, TU Graz
 5 Guowei Wei, Michigan State
 6 George Hagedorn, Virginia Tech
 7 Frederic Coquel, Ecole Polytechnique Paris
 8 Qiang Deng, UWMadison
 9 Ray Pierrehumbert, U of Chicago
 10 Jianfeng Lu, Courant Institute
 11 Bokai Yan, UWMadison
 12 Henri Berestycki, EHESS
 13 David Anderson, UWMadison
 14 Carsten Conradi, MPIMagdeburg
 15 Anne Shiu, U of Chicago
 16 Organizer contact information
 17 Archived semesters
Sigurd Angenent, UWMadison
Deterministic and random models for polarization in yeast cells 
I'll present one of the existing models for "polarization in yeast cells." The heuristic description of the model allows at least two mathematical formulations, one using pdes (a reaction diffusion equation) and one using stochastic particle processes, which give different predictions for what will happen. The model is simple enough to understand and explain why this is so. 
John Finn, Los Alamos
Symplectic integrators with adaptive time steps 
TBA 
Jay Bardhan, Rush Univ
Understanding Protein Electrostatics using BoundaryIntegral Equations 
The electrostatic interactions between biological molecules play important roles determining their structure and function, but are challenging to model because they depend on the collective response of thousands of surrounding water molecules. Continuum electrostatic theory  e.g., the Poisson equation  offers a successful and simple theory for biomolecule science and engineering, and boundaryintegral equation formulations of the problem offer several theoretical and computational advantages. In this talk, I will highlight some recent modeling advances derived from the boundaryintegral perspective, which have important applications in biophysics and whose mathematical foundations may be useful in other domains as well. First, one may derive a fast electrostatic model that resembles Generalized Born theory, but is based on a rigorous operator approximation for rapid, accurate estimation of a Green's function. In addition, we have been exploring a boundaryintegral approach to nonlocal continuum theory as a means to model the influence of water structure, an important piece of molecular physics left out of the standard continuum theory. 
Omar Morandi, TU Graz
Modeling quantum transport with the phasespace formalism 
Quantum modeling is becoming a crucial aspect in nanoelectronics research in perspective of analog and digital applications. Devices like interband tunneling diodes or graphene sheets are examples of solid state structures that are receiving a great importance in the modern nanotechnology for highspeed and miniaturized systems. Differing from the usual transport where the electronic current flows within a single band, the remarkable feature of such solid state structures is the possibility to achieve a sharp coupling among states belonging to different bands. As a consequence, the single band transport or the classical phasespace description of the charge motion based on the Boltzmann equation are not longer accurate. Moreover, in a crystal where the effective Hamiltonian is expressed by a partially diagonalized basis (e. g. in graphene or in semiconductors), the usual definitions of the macroscopic quantities, as for example the mean velocity or the particle density, no longer apply. The theory of Berry phases offers an elegant explanation of this effect in terms of the intrinsic curvature of the perturbed band. Different approaches have been proposed to achieve a full quantum description of electron transport where the interaction among the different bands can be included. Among them, the phasespace formulation of quantum mechanics based on the concept of “WignerWeyl quantization”, offers a framework in which the quantum phenomena can be described with a classical language and the question of the quantumclassical correspondence can be directly investigated. In this contribution, an extension of the original WignerWeyl theory based on a suitable projection procedure, is presented. The applications of this formalism span among different subjects: the multiband transport and applications to nanodevices, the infinite order approximations of the motion and the characterization of a system in terms of Berry phases or, more generally, the representation of a quantum system as a Riemann manifold with a suitable connection. Furthermore, some asymptotic procedures devised for the approx imation of the quantum WignerWeyl solution have shown a very attractive connection with the DysonFeynmann theory of the particle interaction, which allows us to describe quantum transition by means of an effective Boltzmann process. 
Guowei Wei, Michigan State
Variational multiscale models for biomolecular systems

A major feature of biological science in the 21st Century will be its transition from a phenomenological and descriptive discipline to a quantitative and predictive one. Revolutionary opportunities have emerged for mathematically driven advances in biological research. However, the emergence of complexity in selforganizing biological systems poses fabulous challenges to their quantitative description because of the excessively high dimensionality. A crucial question is how to reduce the number of degrees of freedom, while returning the fundamental physics in complex biological systems. This talk focuses on a new variational multiscale paradigm for biomolecular systems. Under the physiological condition, most biological processes, such as protein folding, ion channel transport and signal transduction, occur in water, which consists of 6590 percent of human cell mass. Therefore, it is desirable to describe membrane protein by discrete atomic and/or quantum mechanical variables; while treating the aqueous environment as a dielectric or hydrodynamic continuum. I will discuss the use of differential geometry theory of surfaces for coupling microscopic and macroscopic scales on an equal footing. Based on the variational principle, we derive the coupled Poisson Boltzmann, NernstPlanck (or KohnSham), LaplaceBeltrami and NavierStokes equations for the structure, dynamics and transport of ionchannel systems. As a consistency check, our models reproduce appropriate solvation models at equilibrium. Moreover, our model predictions are intensively validated by experimental measurements. Mathematical challenges include the wellposedness and numerical analysis of coupled partial differential equations (PDEs) under physical and biological constraints, lack of maximumminimum principle, effectiveness of the multiscale approximation, and the modeling of more complex biomolecular phenomena. References GuoWei Wei, Differential geometry based multiscale models, Bulletin of Mathematical Biology, 72, 15621622, (2010). http://www.springerlink.com/content/8303641145x84470/fulltext.pdf Zhan Chen, Nathan Baker and GuoWei Wei, Differential geometry based solvation model I: Eulerian formulation, Journal of Computational Physics, 229, 82318258 (2010). http://math.msu.edu/~wei/paper/p141.pdf Qiong Zheng and GuoWei Wei, PoissonBoltzmannNernstPlanck model. Journal of Chemical Physics, 134 (19), 194101, (2011). http://jcp.aip.org/resource/1/jcpsa6/v134/i19/p194101_s1 
George Hagedorn, Virginia Tech
Time Dependent Semiclassical Quantum Dynamics: Analysis and Numerical Algorithms

We begin with some elementary comments about timedependent quantum mechanics and the role of Planck's constant. We then describe several mathematical results about approximate solutions to the Schr\"odinger equation for small values of the Planck constant. Finally, we discuss numerical difficulties of semiclassical quantum dynamics and algorithms that have recently been developed, including some work in progress. 
Frederic Coquel, Ecole Polytechnique Paris
Coupling of Hyperbolic PDEs: thin versus thick coupling interfaces

The talk will give an overview of some results obtained with several coworkers on the mathematical coupling of nonlinear hyperbolic PDEs. The (wellseparated) multiscale phenomena taking place in various technological setups indeed requires to address Cauchy problems built from a hierarchy of hyperbolic models with relaxation that are formulated on a partition of the physical domain into subregions. At the interface of two subregions, discontinuities in the modeling arise and transient exchange conditions, the socalled coupling conditions, have to be prescribed. I will present a mathematical formalism which models the coupling interfaces in terms of standing waves for an augmented PDE model which is set over the whole physical domain. The augmented equations which may be seen as a first order system with discontinuous coefficients can in turn support various regularization mechanisms. We first adopt the viscous regularization {\it \`a la} Dafermos and prove existence of selfsimilar weak solutions for the coupling of two hyperbolic systems in a single space dimension under fairly general conditions. However, failure of uniqueness is observed in the limit of a vanishing viscosity, as a consequence of a resonance phenomena. To recover uniqueness, we will promote another regularization mechanism based on thickened coupling interfaces. The proposed framework naturally allows for the definition of multidimensional and multicomponent couplings with possible covering. Numerical illustrations will be given all along the lecture. 
Qiang Deng, UWMadison
Tropical cyclogenesis in a 3D Boussinesq model with simple cloud physics

TBA 
Ray Pierrehumbert, U of Chicago
Bifurcation and climate sensitivity

The concept of climate sensitivity lays at the heart of assessment of the magnitude of the imprint of human activities on the Earth's climate. Most commonly, the "climate" is represented by a simple projection such as a global mean temperature, and we wish to know how this changes in response to changes in a single control parameter  usually atmospheric CO2 concentration. This problem is an instance of a broad class of related problems in parameter dependence of dynamical systems. I will discuss the shortcomings of the traditional linear approach to this problem, particularly in light of the spurious "runaway" states produced when feedback becomes large. The extension to include nonlinear effects relates in a straightforward way to bifurcation theory. I will discuss explicit examples arising from icealbedo, water vapor, and cloud feedbacks. Finally, drawing on the logistic map as an example, I will discuss the problem of defining climate sensitivity for problems exhibiting structural instability. 
Jianfeng Lu, Courant Institute
TBA

TBA 
Bokai Yan, UWMadison
Asymptoticpreserving schemes for kineticfluid coupling model

We consider a system coupling the incompressible NavierStokes equations to the VlasovFokkerPlanck equation. Such a problem arises in the description of particulate flows. We design a numerical scheme to simulate the behavior of the system. This scheme is asymptoticpreserving, thus efficient in both the kinetic and hydrodynamic regimes. It has a numerical stability condition controlled by the nonstiff convection operator, with an implicit treatment of the stiff drag term and the FokkerPlanck operator. Yet, consistent to a standard asymptoticpreserving FokkerPlanck solver or an incompressible NavierStokes solver, only the conjugategradient method and fast Poisson and Helmholtz solvers are needed. Numerical experiments are presented to demonstrate the accuracy and asymptotic behavior of the schemes, with several interesting applications. 
Henri Berestycki, EHESS
TBA

TBA 
David Anderson, UWMadison
Computational methods for stochastic models in biology

I will focus on computational methods for continuous time Markov chains, which includes the large class of stochastically modeled biochemical reaction networks and population processes. I will show how different computational methods can be understood and analyzed by using different representations for the processes. Topics discussed will be a subset of: approximation techniques, variance reduction methods, parameter sensitivities. 
Carsten Conradi, MPIMagdeburg
Multistationarity and switching in mass action networks

Many biochemical processes can successfully be described by dynamical systems allowing some form of switching when, depending on their initial conditions, solutions of the dynamical system end up in different regions of state space (associated with different biochemical functions): switching is, for example, the basis of intracellular processes like cellular signal transduction, information processing and cell cycle control. Due to predominant parameter uncertainty numerical methods are generally difficult to apply to realistic models originating in Systems Biology. Hence analytical tools that allow the direct computation of states and parameters where switching occurs are desirable. Here conditions for mass action networks are presented that take the form of linear inequality systems. 
Anne Shiu, U of Chicago
Chemical reaction systems with toric steady states

Chemical reaction networks taken with massaction kinetics are dynamical systems governed by polynomial differential equations that arise in chemical engineering and systems biology. In general, establishing the existence of (multiple) steady states is challenging, as it requires the solution of a large system of polynomials with unknown coefficients. If, however, the steady state ideal of the system is a binomial ideal, then we show that these questions can be answered easily. This talk focuses on systems with this property, and we say that such systems have toric steady states. Our main result gives sufficient conditions for a chemical reaction system to admit toric steady states. Furthermore, we analyze the capacity of such a system to exhibit multiple steady states. An important application concerns the biochemical reaction networks networks that describe the multisite phosphorylation of a protein by a kinase/phosphatase pair in a sequential and distributive mechanism. No prior knowledge of chemical reaction network theory or binomial ideals will be assumed. This is joint work with Carsten Conradi, Mercedes Pérez Millán, and Alicia Dickenstein. 
Organizer contact information
Archived semesters
 Spring 2011
 Fall 2010
 Spring 2010
 Fall 2009
 Spring 2009
 Fall 2008
 Spring 2008
 Fall 2007
 Spring 2007
 Fall 2006
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