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IMA Newsletter #378

April 2008

2007-2008 Program

Mathematics of Molecular and Cellular Biology

See http://www.ima.umn.edu/2007-2008 for a full description of the 2007-2008 program on Mathematics of Molecular and Cellular Biology.

News and Notes
The 2008 IMA Summer Program Geometrical Singularities and Singular Geometries, July 14-25, 2008, will focus on the interplay between geometry and physics in the material world through the study of singular stuctures.

This two week workshop at the IMA, organized by L. Mahadevan, Engineering and Applied Sciences, Harvard University, Edward A. Spiegel, Astronomy, Columbia University, Thomas A. Witten, Physics, University of Chicago, and Wendy Zhang, Physics, University of Chicago, will focus on what we know and what we would like to know about these types of singular structures; with the first week focusing on fluid singularities, and the second on elastic singularities. We also expect to have an intense mid-week mini-tutorial on singularities in geometric field theories: examples from gravitation to condensed matter.

PI Summer Program for Graduate Students Linear Algebra and Applications will be held at Iowa State University, June 30-July 25, 2008. This program is is primarily for graduate students of IMA Participating Institutions. In order to participate, students need to fill out the application form and provide a brief note of nomination by April 15, 2008. The program will run for four weeks and cover linear algebra, numerical linear algebra, and applications.

Mathematical Modeling in Industry Mathematical Modeling in Industry XII - A Workshop for Graduate Students, August 6-15, 2008 offers graduate students and qualified advanced undergraduates first hand experience in industrial research. Teams of up to six students will work under the guidance of a mentor from industry, who will guide the students in the modeling and analysis of real-world industrial problems. This year's mentors are Christopher Bemis, Whitebox Advisors, Olus Boratav Corning Inc., J. Michael Gray and Robert Shimpa, Medtronic, Thomas A. Grandine, Boeing, Anthony José Kearsley, National Institute of Standards and Technology Chai Wah Wu, IBM Research. The application deadline is April 15.

Complex Fluids and Complex Flows: The preliminary program for the IMA Thematic year 2009-2010 on Complex Fluids and Complex Flows is now available on line.

IMA Events

IMA Tutorial

Network Dynamics and Cell Physiology

April 17-18, 2008

Organizers: Daniel Forger (University of Michigan), John J. Tyson (Virginia Polytechnic Institute and State University)

IMA Annual Program Year Workshop

Design Principles in Biological Systems

April 21-25, 2008

Organizers: Bud Mishra (New York University), Partha P. Mitra (Cold Spring Harbor Laboratory)
Schedule

Tuesday, April 1

11:15a-12:15pDiscovering biological networks by integrating diverse genomic dataChad L. Myers (University of Minnesota)Lind Hall 409 PS

Wednesday, April 2

11:15a-12:15pFrom neurons to neural networksJeff Knisley (East Tennessee State University)Lind Hall 409 MMCB

Thursday, April 3

2:00p-3:00pInformal working seminar on stochastic techniques in microbiologyPeter R. Kramer (Rensselaer Polytechnic Institute)Lind Hall 409 WS-STM

Friday, April 4

1:25p-2:25pInteraction of lipid bilayers with inorganic surfaces: experiments to modelingAravind R. Rammohan (Corning)Vincent Hall 570 IPS

Tuesday, April 8

11:15a-12:15pDynamical approaches to understanding epilepsyTheoden Netoff (University of Minnesota)Lind Hall 409 PS

Wednesday, April 9

11:15a-12:15pRecent advances and challenges in deterministic global optimizationChristodoulos A. Floudas (Princeton University)Lind Hall 409 MMCB

Friday, April 11

1:25p-2:25pChallenges for numerical analysis in medical device industriesMichael Schendel (Medtronic)Vincent Hall 570 IPS

Tuesday, April 15

11:15a-12:15pParameterization for mesoscale ocean transport through random flow modelsBanu Baydil (Rensselaer Polytechnic Institute)Lind Hall 409 PS

Wednesday, April 16

11:45a-12:45pSize and shape of polymersEric J. Rawdon (University of St. Thomas)Lind Hall 409 MMCB

Thursday, April 17

8:15a-8:50aRegistration and CoffeeEE/CS 3-176 T4.17-18.08
8:50a-9:00aWelcome to the IMA Douglas N. Arnold (University of Minnesota)EE/CS 3-180 T4.17-18.08
9:00a-10:00aLecture 1: Cell physiology, molecular biology and mathematical modelingJohn J. Tyson (Virginia Polytechnic Institute and State University)EE/CS 3-180 T4.17-18.08
10:00a-10:30aCoffeeEE/CS 3-176 T4.17-18.08
10:30a-11:30aLecture 2: Network motifs: sniffers, buzzers, toggles and blinkersJohn J. Tyson (Virginia Polytechnic Institute and State University)EE/CS 3-180 T4.17-18.08
11:30a-1:30pLunch T4.17-18.08
1:15p-2:30pComputer Lab 1: Phase planes, vector fields, nullclines, bifurcationsDaniel Forger (University of Michigan)
John J. Tyson (Virginia Polytechnic Institute and State University)
Lind Hall 409 T4.17-18.08
2:30p-3:00pCoffeeEE/CS 3-176 T4.17-18.08
3:00p-4:00pLecture 3: Cell cycle regulationJohn J. Tyson (Virginia Polytechnic Institute and State University)EE/CS 3-180 T4.17-18.08
4:00p-5:00pComputer Lab 2: Modeling exercisesDaniel Forger (University of Michigan)
John J. Tyson (Virginia Polytechnic Institute and State University)
Lind Hall 409 T4.17-18.08

Friday, April 18

8:30a-9:00aCoffeeEE/CS 3-176 T4.17-18.08
9:00a-9:00aLecture 4: Stochastic modeling of molecular regulatory networksDaniel Forger (University of Michigan)EE/CS 3-180 T4.17-18.08
10:00a-10:30aBreakEE/CS 3-176 T4.17-18.08
10:30a-11:30aLecture 5: Models of circadian rhythms Daniel Forger (University of Michigan)EE/CS 3-180 T4.17-18.08
11:30a-12:30pLunch T4.17-18.08
1:15p-2:30pComputer Lab 3: Stochastic Simulation Daniel Forger (University of Michigan)
John J. Tyson (Virginia Polytechnic Institute and State University)
Lind Hall 409 T4.17-18.08
2:30p-3:00pBreakEE/CS 3-176 T4.17-18.08
3:00p-4:00pLecture 6: Synchronization and phase resettingDaniel Forger (University of Michigan)EE/CS 3-180 T4.17-18.08

Monday, April 21

8:45a-9:30aRegistration and coffeeEE/CS 3-176 W4.21-25.08
9:30a-9:40aWelcome to the IMADouglas N. Arnold (University of Minnesota)EE/CS 3-180 W4.21-25.08
9:40a-10:00aIntroduction to the workshopBud Mishra (New York University)
Partha P. Mitra (Cold Spring Harbor Laboratory)
EE/CS 3-180 W4.21-25.08
10:00a-10:50aTutorial on feedback control theoryRichard M. Murray (California Institute of Technology)EE/CS 3-180 W4.21-25.08
10:50a-11:20aCoffeeEE/CS 3-176 W4.21-25.08
11:20a-12:00pArchitecture: Human engineered systemsRichard M. Murray (California Institute of Technology)EE/CS 3-180 W4.21-25.08
12:00p-2:00pLunch W4.21-25.08
2:00p-2:40pArchitecture: BacteriaJohn C. Doyle (California Institute of Technology)EE/CS 3-180 W4.21-25.08
2:50p-3:30pArchitecture: BrainsPartha P. Mitra (Cold Spring Harbor Laboratory)EE/CS 3-180 W4.21-25.08
3:30p-3:50pCoffee EE/CS 3-176 W4.21-25.08
3:50p-4:20pResponse tuning through specific feedback architecturesHana El-Samad (University of California)EE/CS 3-180 W4.21-25.08
4:30p-5:00pCircuitry, psychophysics, and electrophysiology of touch in the rat vibrissa systemDavid Kleinfeld (University of California, San Diego)EE/CS 3-180 W4.21-25.08
5:00p-6:30pReception and Poster SessionLind Hall 400 W4.21-25.08
Quantitative systems analysis of multicellular morphodynamicsAnand R. Asthagiri (California Institute of Technology)
A design principle in biochemical reaction networks based on realization theoryBassam Bamieh (University of California)
A transcriptional regulatory switch underlying B-cell terminal differentiation and its disruption by dioxin Sudin Bhattacharya (The Hamner Institutes for Health Sciences)
Recurrent and robust patterns underlying human relative preference, and associations with brain circuitry plus genetics Hans C. Breiter MD (Massachusetts General Hospital)
Computational hemodynamics analysis in large blood vessels: Effects of hematocrit variation on flow stabilityOluwole Daniel Makinde (University of Limpopo)
The advantage of two step transport problemEzio Marchi (Instituto de Matemática Aplicada)
Biological project: The construction of the cycle in Lotka-Volterra of n-speciesEzio Marchi (Instituto de Matemática Aplicada)
Trajectory measures describing the locomotor behavior of Drosophila melanogaster in a circular arenaDan Valente (Cold Spring Harbor Laboratory)
Evolution of song culture in the zebra finchHaibin Wang (Cold Spring Harbor Laboratory)

Tuesday, April 22

9:00a-9:30aCoffeeEE/CS 3-176 W4.21-25.08
9:30a-10:10aGeneric approach to construction of system design spaceMichael A. Savageau (University of California)EE/CS 3-180 W4.21-25.08
10:20a-11:00aTransient stochastic analysis of gene networksMustafa H. Khammash (University of California)EE/CS 3-180 W4.21-25.08
11:00a-11:20aCoffeeEE/CS 3-176 W4.21-25.08
11:20a-12:00pModeling epigenetic silencingAnirvan Sengupta (Rutgers University)EE/CS 3-180 W4.21-25.08
12:00p-2:00pLunch W4.21-25.08
2:00p-2:40pTBAEE/CS 3-180
2:50p-3:30p Monotone input/output systems as a technique for modular analysis of biomolecular network dynamics Eduardo D. Sontag (Rutgers University)EE/CS 3-180 W4.21-25.08
3:30p-4:00pCoffeeEE/CS 3-176 W4.21-25.08
4:00p-4:30pSecond chancesEE/CS 3-180 W4.21-25.08
4:45p-5:00pWorkshop photo W4.21-25.08

Wednesday, April 23

9:00a-9:30aCoffeeEE/CS 3-176 W4.21-25.08
9:30a-10:10a Design principles in the evolution of animal communicationW. Tecumseh Fitch (University of St. Andrews)EE/CS 3-180 W4.21-25.08
10:20a-11:00aEvolvabilityChristine Queitsch (Harvard University)EE/CS 3-180 W4.21-25.08
11:00a-11:20aCoffeeEE/CS 3-176 W4.21-25.08
11:20a-12:00pReverse engineering the lordosis behavior neuronal circuitDonald Pfaff (Rockefeller University)EE/CS 3-180 W4.21-25.08
12:00p-2:00pLunch W4.21-25.08
2:00p-2:40pPhilosophy of biology: Function/design: IRobert Cummins (University of Illinois at Urbana-Champaign)EE/CS 3-180 W4.21-25.08
2:50p-3:30pPluralism about functionPeter H. Schwartz (Indiana University Center for Bioethics and Indiana University School of Medicine)EE/CS 3-180 W4.21-25.08
3:30p-4:00pCoffeeEE/CS 3-176 W4.21-25.08
4:00p-4:30pSecond chancesEE/CS 3-180 W4.21-25.08
6:30p-8:30pWorkshop DinnerCaspian Bistro
2418 University Ave SE
Minneapolis, MN 55414
612-623-1133
W4.21-25.08

Thursday, April 24

9:00a-9:30aCoffeeEE/CS 3-176 W4.21-25.08
9:30a-10:10a Engineering theory of neuronal shapeDmitri Chklovskii (Cold Spring Harbor Laboratory)EE/CS 3-180 W4.21-25.08
10:20a-11:00aCellular information processing in the face of promiscuity and sloppinessChristopher R. Myers (Cornell University)EE/CS 3-180 W4.21-25.08
11:00a-11:20aCoffeeEE/CS 3-176 W4.21-25.08
11:15a-12:15pAnalysis of physical fidelity of stochastic simulation method for microbiological systemPeter R. Kramer (Rensselaer Polytechnic Institute)Vincent Hall 570 AMS
11:20a-12:00pDesign principles in synthetic biologyChris J. Myers (University of Utah)EE/CS 3-180 W4.21-25.08
12:00p-2:00pLunch W4.21-25.08
2:00p-2:40pFundamental limitations on noise reduction in the cellGlenn Vinnicombe (University of Cambridge)EE/CS 3-180 W4.21-25.08
2:50p-3:30pTBAC.P. Hunter (Harvard University)EE/CS 3-180 W4.21-25.08
3:30p-4:00pCoffeeEE/CS 3-176 W4.21-25.08
4:00p-4:40pTBD (possibly: 5 minute spontaneous participant talks)EE/CS 3-180 W4.21-25.08
4:40p-5:10pSecond chancesEE/CS 3-180 W4.21-25.08

Friday, April 25

9:00a-9:30aCoffeeEE/CS 3-176 W4.21-25.08
9:30a-10:10aPredicting quantitative diversification of multicellular phenotypeAnand R. Asthagiri (California Institute of Technology)EE/CS 3-180 W4.21-25.08
10:20a-11:00aEvo-devo and the syntactic and semantic 'design features' of human language Robert C. Berwick (Massachusetts Institute of Technology)EE/CS 3-180 W4.21-25.08
11:00a-11:20aCoffeeEE/CS 3-176 W4.21-25.08
11:20a-12:00pWrap-up discussionEE/CS 3-180 W4.21-25.08

Tuesday, April 29

All DayNSF site visit
11:15a-12:15pA user's guide to PDE models for chemotaxisThomas Hillen (University of Alberta)EE/CS 3-180 PS

Wednesday, April 30

All DayNSF site visit
Abstracts
Anand R. Asthagiri (California Institute of Technology) Predicting quantitative diversification of multicellular phenotype
Abstract: Networks of biological signals guide cells to form multicellular patterns and structures. Understanding the design and function of these complex networks is a fundamental challenge in developmental biology and has clear implications for biomedical applications, such as tissue engineering and regenerative medicine. Signaling networks are composed of highly interconnected pathways involving numerous molecular components. Precisely to what extent multicellular structures are susceptible to quantitative variations in underlying signals and to what extent Nature has utilized this mechanism of "quantitative diversification" during evolution are unclear. I will describe a computational framework that we have developed to explore and to quantify the multicellular diversity that emerges from signaling perturbations. We have applied this method to study vulval development in C. elegans. The approach is not only effective in predicting the molecular genetics of multicellular patterning, but also gauges the capacity of this signaling network for creating phenotypic diversity. In fact, model predictions strongly correlate to multicellular phenotypes observed across ten species related to C. elegans. These results suggest that systems-level modeling can shed insight into the evolutionary trajectories of regulatory networks that gave rise to divergent multicellular phenotypes.
Anand R. Asthagiri (California Institute of Technology) Quantitative systems analysis of multicellular morphodynamics
Abstract: The goal of my research program is to better understand how biological circuits program multicellular phenotypes. While a major focus of the group involves phenotypes associated with human epithelial systems, we have also drawn upon more tractable model systems, such as C. elegans and yeast, to glean deeper fundamental insights. Each of these three biological systems provides unique advantages that my lab has sought to exploit using a combination of computational and quantitative experimental approaches.
Bassam Bamieh (University of California) A design principle in biochemical reaction networks based on realization theory
Abstract: We attempt to address the question of why there are so many intermediate species in biochemical reaction networks using an idea from realization theory. We describe how prescribed biological function can be designed with very low dimensional models, which are however not implementable with the physically allowable biochemical reaction mechanisms. It then becomes apparent that the introduction of a large number of intermediate species can be interpreted as a realization technique to enable the implementation of prescribed function with the available dynamical building blocks. By reversing this realization scheme, we propose a model reduction paradigm for biochemical reaction networks.
Banu Baydil (Rensselaer Polytechnic Institute) Parameterization for mesoscale ocean transport through random flow models
Abstract: We describe a mathematical approach based on homogenization theory toward representing the effects of mesoscale coherent structures, waves, and turbulence on large-scale transport in the ocean. We are developing a systematic parameterization strategy by building up deterministic and random subgrid-scale flow models in an increasing hierarchy of complexity, coupling the results from numerical simulations of cell problems with asymptotic analysis with respect to key nondimensional physical parameters such as Pecl'{e}t and Strouhal numbers.
Robert C. Berwick (Massachusetts Institute of Technology) Evo-devo and the syntactic and semantic 'design features' of human language
Abstract: Human language has long captured the imagination of biological researchers, but the gulf separating 'computation,' 'biology', and 'language' has been equally long-standing: the classical biological problem of how to bridge between a genotype and a phenotype, in this case, perhaps the most complex behavioral phenotype we know of. The aim of this talk is to show how recent developments in linguistic theory bridge this 'abstraction gap' by illuminating some of the modular design properties of human language, illustrating that despite its apparent surface complexity, human language's core seems to be far simpler than has been previously supposed, potentially reducible to a single, simple, basic operation that derives all the seemingly special properties of human language. Further, by positing this modular approach, we can shed light on the computational interfaces of human language to the systems of speech/motor production and parsing, as well as internal systems of inference; here there seems to be a natural, and expected kind of 'impedance matching,' with the design seemingly forced to follow constraints imposed by considerations of semantic interpretation, rather than considerations of computational complexity in parsing or production. Finally, this new modular view leads naturally to evolutionary considerations as to how these components arose in the course of evolution, in this case, a more 'saltational' view than is generally supposed.
Sudin Bhattacharya (The Hamner Institutes for Health Sciences) A transcriptional regulatory switch underlying B-cell terminal differentiation and its disruption by dioxin
Abstract: Joint work with Qiang Zhang(1), Melvin E. Andersen(1) and Rory B. Conolly(2). The terminal differentiation of B cells in lymphoid organs into antibody-secreting plasma cells upon antigen stimulation is a crucial step in the humoral immune response. The architecture of the B-cell transcriptional regulatory network consists of coupled mutually-repressive feedback loops involving the three transcription factors Bcl6, Blimp1 and Pax5. This structure forms the basis of an irreversible bistable switch directing the B-cell to plasma cell differentiation process - i.e., the switch remains on even after the activating stimulus (antigen) is removed. The environmental contaminant 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) is known to suppress the humoral immune response by interfering with this differentiation program. We have developed a computational model of the biochemical pathways that regulate B-cell differentiation, and the molecular mechanism by which TCDD impairs this process through the action of the aryl hydrocarbon receptor (AhR). Using a kinetic model and bifurcation analysis, we propose that TCDD regulates the proportion of B-cells that differentiate into plasma cells by raising the threshold dose of antigen lipopolysaccharide (LPS) required to trigger the differentiation switch. We also show that stochastic modeling of gene expression, which allows cell-to-cell differences in content of signaling proteins, introduces distributional characteristics to the timing and probability of differentiation among a population of B-cells. This cell-to-cell variability is likely to be a key determinant of dose-response and sensitivity of individual cells to differentiation. (1) Division of Computational Biology, The Hamner Institutes for Health Sciences, Research Triangle Park, NC 27709, USA (2) National Center for Computational Toxicology, U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, USA
Hans C. Breiter MD (Massachusetts General Hospital) Recurrent and robust patterns underlying human relative preference, and associations with brain circuitry plus genetics
Abstract: Joint work with BW Kim. The Phenotype Genotype Project on Addiction and Depression (PGP), with support from the Departments of Neurology, Psychiatry, and Radiology, and Center for Human Genetic Research; Massachusetts General Hospital and Harvard Medical School; Boston, MA, USA Positive and negative preferences can be assessed by keypress procedures that quantify (i) decision-making regarding approach, avoidance, indifference, and ambivalence responses, and (ii) judgments that determine the magnitude of approach and avoidance. Most prior studies of relative preference have not used keypress procedures, but have used ratings of personal utility, as a composite index of approach and avoidance. Such composite ratings can be calibrated against an absolute framework such as the macroeconomic pricing of commodities, as is done with Prospect Theory. It leaves open questions of whether or not splitting composite ratings of utility into approach and avoidance measures reveals any patterns in behavior, as observed for Prospect Theory. Such patterns might include a trade-off relationship between approach and avoidance, or a value function that might not need an absolute macroeconomic framework. We assessed these questions across multiple sets of healthy control sub jects with a keypress procedure, and found a set of patterns for approach and avoidance are (i) recurrent across many stimulus types, and (ii) robust to the injection of noise. These patterns include: (a) a preference trade-off plot that counterbalances approach and avoidance responses and represents biases in preference and consistency/uncertainty of preference, (b) a value function linking preference intensity to uncertainty about preference, and (c) a preference saturation plot that represents how avoidance actions are over-determined relative to approach actions. One can consider this set of patterns to be a form of relative preference theory (RPT), since they meet the same requirements for recurrency and robustness to noise as the Weber-Fechner-Stevens Law. As with the value function for Prospect Theory, the value function in RPT has a steeper slope for negative relative to positive preferences (i.e., loss aversion), and can be described as a power law, or a logarithmic functi on. All of these patterns show symmetry between group and individual data in that they have similar mathematical formulations as manifolds or boundary asymptotes for group data, or as fitted functions for individual data across multiple variables. These patterns verify known biases between females and males regarding viewing beautiful and average faces. When used to evaluate cocaine dependent subjects versus healthy controls, these patterns quantify the phenotype of the restricted behavioral repertoire observed in addiction. When used as regressors in the analysis of fMRI data, RPT measures are associated with significant BOLD signal change across a set of reward/aversion brain regions. Both keypress behavior and fMRI BOLD signal can be further associated with polymorphisms is genes such as CREB1 and BDNF. Given RPT scaling between groups of subjects and individuals, further work is warranted to assess if scaling can be achieved to brain circuitry and genetics.
Dmitri Chklovskii (Cold Spring Harbor Laboratory) Engineering theory of neuronal shape
Abstract: The human brain is a network containing a hundred billion neurons, each communicating with several thousand others. As the wiring for neuronal communication draws on limited space and energy resources, evolution had to optimize their use. This principle of minimizing wiring costs explains many features of brain architecture, including placement and shape of many neurons. However, the shape of some neurons and their synaptic properties remained unexplained. This led us to the principle of maximization of brain’s ability to store information, which can be expressed as maximization of entropy. Combination of the two principles, analogous to the minimization of free energy in statistical physics, provides a systematic view of brain architecture, necessary to explain brain function.
Robert Cummins (University of Illinois at Urbana-Champaign) Philosophy of biology: Function/design: I
Abstract: The concept of function has a tainted history in science and philosophy, having been mated to teleology and harnessed to pull various discredited theories. This presentation begins with a short history designed to give a sense of what made the concept of function problematic. Current philosophical attention to the problem revolves ellipse-like around two foci: systematic or system relative accounts, and selectionist accounts. These are briefly described, and the systematic account is defended on the grounds that it captures a ubiquitous explanatory strategy in science and engineering, and that selectionist accounts are, in contrast, limited to evolutionary biology (and, perhaps, designed artifacts), and make it difficult to articulate various important issues in evolutionary biology itself.
Hana El-Samad (University of California) Response tuning through specific feedback architectures
Abstract: Determining proper sensitivity to incoming signals is important to all regulated biological systems, but is especially crucial for responses that involve an irreversible decision. Using Xenopus oocytes maturation as an example, we illustrate how entangled feedback architectures can be used to integrate the multiple signals needed to make the switchlike, irreversible transition from interphase to meiosis. We also discuss how the specific topologies of these feedback loops modulate the switching threshold as a function of the progesterone input.
W. Tecumseh Fitch (University of St. Andrews) Design principles in the evolution of animal communication
Abstract: The evolution of communication provides one of the few examples in evolutionary biology where principles of physical acoustics, interacting with developmental constraints on physiology and motor control, have clear and predictable effects on evolutionary outcomes. I will provide two clear example of this, relating to basic physiological constraints on fundamental and formant frequencies, and various morphological "tricks" that vertebrates have evolved to evade such constraints. Then I will explore a more speculative hypothesis concerning the neural control of vocalization: that the production of complex learned vocalizations requires particular neural correlates (direct fronto-bulbar connections) and behaviours ("babbling" or subsong), and furthermore that constraints on development may mean that there are only a few ways to achieve such vocal capabilities, raising the interesting possibility of "deep homology" in the evolution of communication. This hypothesis, though speculative, is testable and is consistent with the most recent information on genes involved in vocal learning.
Christodoulos A. Floudas (Princeton University) Recent advances and challenges in deterministic global optimization
Abstract: In this presentation, we will provide an overview of the research progress in global optimization. The focus will be on important contributions during the last five years, and will provide a perspective for future research opportunities. The overview will cover the areas of (a) twice continuously differentiable constrained nonlinear optimization, and (b) mixed-integer nonlinear optimization models. Subsequently, we will present our recent fundamental advances in (i) convex envelope results for multi-linear functions, (ii) a piecewise quadratic convex underestimator for twice continuously differentiable functions, (iii) the generalized alpha-BB framework, (iv) our recently improved convex underestimation techniques for univariate and multivariate functions, and (v) generalized pooling problems. Computational studies will illustrate the potential of these advances.
Daniel Forger (University of Michigan), John J. Tyson (Virginia Polytechnic Institute and State University) Computer Lab 1: Phase planes, vector fields, nullclines, bifurcations
Abstract: How to use WinPP and XPP. Models of bistability and oscillations. Drawing phase plane portraits. How portraits depend on parameter values. One-parameter bifurcation diagrams.
Daniel Forger (University of Michigan), John J. Tyson (Virginia Polytechnic Institute and State University) Computer Lab 2: Modeling exercises
Abstract: Building simple models of cell cycle, circadian rhythm, programmed cell death, glycolysis, Ca2+ oscillations, etc.
Daniel Forger (University of Michigan) Lecture 4: Stochastic modeling of molecular regulatory networks
Abstract: Relation between stochastic and deterministic formalisms. Two discrete simulation methods proposed by Gillespie. 1/N relationship. Noise induced oscillations. Chemical Langevin equations and hybrid methods. Introduction to simulation packages.
Daniel Forger (University of Michigan) Lecture 5: Models of circadian rhythms
Abstract: Basic properties of circadian clocks. Goodwin and early models. More realistic models. Model predictions and their experimental validation. Temperature Compensation. Unanswered questions.
Daniel Forger (University of Michigan), John J. Tyson (Virginia Polytechnic Institute and State University) Computer Lab 3: Stochastic Simulation
Abstract: Simulations of simple models of genetic networks using the Gillespie Method. Comparison of behavior for small and large number of chemical events.
Daniel Forger (University of Michigan) Lecture 6: Synchronization and phase resetting
Abstract: Phase Response Curves, Phase Transition Curves and Winfree’s Type 0 vs. Type 1 distinction. Global vs. local coupling. Pulse vs. sustained coupling. Coupling induced rhythmicity. Relationship between phase resetting and coupling.
Thomas Hillen (University of Alberta) A user's guide to PDE models for chemotaxis
Abstract: The mathematical analysis of chemotaxis (the movement of biological cells or organisms in response to chemical gradients) has developed into a large and diverse discipline. A simplified version of the original Keller-Segel model (called "minimal model") displays already self-aggregation properties, which are expressed, in higher dimensions, through finite time blow-up solutions. Based on this "minimal" model we study modifications and variations of chemotaxis models. These variations are partly motivated through biological realism and partly through mathematical convenience. We will present results on global existence and blow-up for the modified models and discuss spatial pattern formation for those models with global solutions. Typical patterns show an interesting merging and emerging dynamics. (joint work with Kevin Painter, Heriot Watt, Edinburgh)
Mustafa H. Khammash (University of California) Transient stochastic analysis of gene networks
Abstract: Many gene regulatory networks are modeled at the mesoscopic scale, where chemical populations change according to a discrete state (jump) Markov process. The chemical master equation for such a process is typically infinite dimensional and unlikely to be computationally tractable without reduction. The recently proposed Finite State Projection technique allows for a bulk reduction of the CME while explicitly keeping track of its own approximation error. We show how a projection approach can be used to directly determine the statistical distributions for stochastic gene switch rates, escape times, trajectory periods, and trajectory bifurcations, and to evaluate how likely it is that a network will exhibit certain behaviors during certain intervals of time. We illustrate these ideas through the analysis of the switching behavior of a stochastic model of Gardner's genetic toggle switch.
David Kleinfeld (University of California, San Diego) Circuitry, psychophysics, and electrophysiology of touch in the rat vibrissa system
Abstract: I will review the control of localization by rat vibrissa system.
Jeff Knisley (East Tennessee State University) From neurons to neural networks
Abstract: Artificial Neural Networks (ANN's) are machine-learning algorithms that are often used as classifiers in molecular and computational biology. Originally, ANN's were inspired by in vivo models of axonal and dendritic neuro-electric activity, especially the classical models of Hodkgin, Huxley, and others. Much of the successive development of ANN's, as well as the parallel development of other approaches such as Support Vector Machines, has been as a means of addressing issues such as overfitting and hard margins which arise in machine learning applications. To address these issues, ANN's have borrowed from a variety of sources in computer science, physics, and cognitive psychology, but not so much from the ever-improving neuronal models which provided their initial inspiration. We will revisit much of the historical and algorithmic development of ANN's, with the goal being that of suggesting the types of ANN's that might be inspired by more recent developments in dendritic electrotonic models.
Peter R. Kramer (Rensselaer Polytechnic Institute) Informal working seminar on stochastic techniques in microbiology
Abstract: Based on the response I received, I propose to do the following: I'll begin by briefly advertising the various projects in which I am actively interested since several new people have arrived since I did this before. For most of the hour, I will again discuss the stochastic immersed boundary method for simulating microbiological systems, but the emphasis will not be so much on the method itself, but on more general issues raised in the design and analysis of the method. Possible topics for discussion include: 1) How do you add noise in a "correct" way to a physical system? 2) How can you check that a stochastic numerical method is simulating the correct statisical physics? 3) How can you use the method of stochastic mode reduction to analyze the effective coarse-grained behavior of a complex stochastic systems when a separation of time scales can be exploited. If desired, I can illustrate the stochastic mode reduction approach on the simple equation I described last week (showing that, on long-time scales, thermally driven Newton's law for particle motion (second order stochastic differential equation) can be approximated by a first order drift-diffusion model). I'll direct the discussion as best I can toward the interests of those who choose to attend, and pitch the technical level accordingly.
Peter R. Kramer (Rensselaer Polytechnic Institute) Analysis of physical fidelity of stochastic simulation method for microbiological system
Abstract: One approach to accelerating biomolecular simulations is to simulate explicitly only certain slow degrees of freedom of interest, incorporating the effects of the remaining “fast” variables through effective stochastic models. We illustrate a systematic multi-scale stochastic mode reduction procedure on a simple model problem with metastability – a high potential energy barrier separating different conformational states. Metastability is a prevalent feature in biomolecular systems. We show in particular how the metastability can lead to various effective stochastic equations for the slow degrees of freedom depending on the relations between the physical parameters and properties of the potential energy landscape. This work is in collaboration with Jessika Walter at Ecole Polytechnique Federale de Lausanne and Christof Schuette at the Free University of Berlin. Time permitting, I will also discuss some general observations concerning the application of multiple scale asymptotics to problems with three (or more) active time scales (joint work with Adnan Khan (Lahore) and Robert E. Lee DeVille (University of Illinois)).
Oluwole Daniel Makinde (University of Limpopo) Computational hemodynamics analysis in large blood vessels: Effects of hematocrit variation on flow stability
Abstract: Understanding the effects of blood viscosity variation plays a very crucial role in hemodynamics, thrombosis and inflammation and could provide useful information for diagnostics and therapy of (cardio) vascular disease. Blood viscosity, which arises from frictional interactions between all major blood constituents, i.e. plasma, plasma proteins and red blood cells, constitutes blood inherent resistance to flow in the blood vessel. Because red blood cells (RBCs) are the main constituent of the cellular phase of blood, white blood cells and platelets normally do not have a great influence on whole blood viscosity. When blood flows through a vessel, it tends to separate in two different phases. In direct contact with the wall a low viscosity phase exists, which is deficient in cells and rich in plasma and acts as a lubricant for the blood transport. In the central core region of the vessel a high viscosity phase exists, which depends on the hematocrit. In this paper, the nature and stability of blood flow in a large artery is investigated numerically using a spectral collocation technique with expansions in Chebyshev polynomials. The study reveals that a rise in hematocrit concentration in the central core region of a large artery has a stabilizing effect on the flow. Keywords: Arterial blood flow; Hematocrit; Variable viscosity; Temporal stability; Chebyshev spectral collocation technique References: 1.) Pedley T. J.: The Fluid Mechanics of Large Blood Vessels. Cambridge University Press, London, 1980. 2.) Makinde O. D.: Magneto-Hydromagnetic Stability of plane- Poiseuille flow using Multi-Deck asymptotic technique. Mathematical & Computer Modelling Vol. 37, No. 3-4, 251-259, 2003. 3.) Makinde O. D. and Mhone P. Y.: Temporal stability of small disturbances in MHD Jeffery-Hamel flows. Computers and Mathematics with Applications, Vol. 53, 128–136, 2007. 4.) Makinde O. D.: Entropy-generation analysis for variable-viscosity channel flow with non-uniform wall temperature. Applied Energy, Vol. 85, 384-393, 2008.
Ezio Marchi (Instituto de Matemática Aplicada) The advantage of two step transport problem
Abstract: Here, we present a transport model which indroduce a variant in the transport theory. Here the mass or merchandize in order to go from a port to a destination must pass through a deposit, without accumulation. It is possible to consider deposit constraint. We obtain the corresponding linear program associated to it, as well as the dual. The application of this model to biological sciences, specially in human body, lungs, blood and biological systems seems promising. We obtain the dual, which appear in a natural way from the incidence matrix, which has many interesting properties. The rank is the number of the ports, deposits plus the destination minus on. We study and characterize all the extremals extending the ideas of Jurkar-Ryser, and von Neumann in the case of the classical transpot model. A relation with the material in the papers by E. Marchi:Z.Wahrscheinlichtheorie verww. geb,12,220-230 (1969) and 23,7-17, (1972), is underway. We were succesful to extend this theory to mixed model considering that in a deposit, there exists the possibility to stay or passing. This rich study permits more potentiality to the tools. An extension to several steps has been performed and its potentiality for applications is vast.
Ezio Marchi (Instituto de Matemática Aplicada) Biological project: The construction of the cycle in Lotka-Volterra of n-species
Abstract: Lotka-Volterra equations are very famous by two biological spices. Generally the most common presentations are in ecology science. We study this models without considering the antisymmetric condition among the parameters.(see Marchi and Velasco Revista Mexicana de Fisica,36,No4(1990)665-679).We obtain a movement constant for the systems which satisfies the Hamilton equation. For more than two interacting species the result the Volterra result are biologically improper. This is due to the antisymetric conditions. Following Volterra original methods combined with the variation of Montroll et. all, who applied such equation to maser and laser, we obtain some powerful personal procedure that we applied to the three and four species obtaining and general condition and build the cycle. Moreover this can be extended for an arbitrary number of biological species obtaining constructively the cycle. The background idea is to delete one variable at that time using partial differentials equations of second power of the first order. Furthermore we consider the conservation of the density of point in the fase space (LIoville theorem) an we postulate that the same distributions following the Gibbs Canonical Law. By the way Prigogyne at all applied Lotka-Volterra system in non-equilibrium thermodynamics. Moreover, there are several applications of Lotka-Volterra to the theory of membrane. We can show you some of them. Finally, we point out that there are about four hundred papers in the subject in the last ten years, and non of them apply our methods. The potentiality for real application is very important even if the system of Lotka-Volterra is asymptotically unstable.
Richard M. Murray (California Institute of Technology) Tutorial on feedback control theory
Abstract: This talk will present an introduction to some of the key principles and tools from feedback control theory. The two main design principles that will be explored is the role of feedback as a tool for managing uncertainty, and the use of feedback to design the dynamics of a system. Examples from engineering and nature will be used to illustrate some of the key concepts and techniques.
Richard M. Murray (California Institute of Technology) Architecture: Human engineered systems
Abstract: This talk will present an engineering perspective on "architecture" in complex engineered systems. The role of protocols and interfaces will be emphasized, along with other architectural concepts such as modularity, evolvability and reusability. Examples of architecture as applied to autonomous vehicles will be used to illustrate modern engineering design tools.
Chad L. Myers (University of Minnesota) Discovering biological networks by integrating diverse genomic data
Abstract: Understanding protein function and modeling biological networks is a key challenge in modern systems biology. Recent developments in biotechnology have enabled high-throughput measurement of several cellular phenomena including gene expression, protein-protein interactions, protein localization and sequence. The wealth of data generated by such technology promises to support computational prediction of network models, but so far, successful approaches that translate these data into accurate, experimentally testable hypotheses have been limited. I will discuss key insights into why we face this imbalance between genomic data and established knowledge and present computational approaches for addressing these challenges. Specifically, I will present a Bayesian framework for integrating diverse genomic data to predict biological networks. I will describe the machine learning methods as well as important data visualization features that support a public, web-based system for user-driven search of network predictions from genomic data. Using our approach, we correctly predicted new functions for approximately 100 genes in yeast. I will discuss experimental validation for these predictions as well as our recent efforts to use predicted network models for directing large-scale genetic interaction screens.
Chris J. Myers (University of Utah) Design principles in synthetic biology
Abstract: Recently, numerous engineers have demonstrated that genetic circuits can be effectively modeled and analyzed utilizing methods originally developed for electrical circuits leading to new understanding of their behavior. If this is possible, then it may also be possible to design synthetic genetic circuits that behave like particular electrical circuits such as switches, oscillators, and communication networks. Synthetic genetic circuits have the potential to help us better understand how microorganisms function, produce drugs more economically, metabolize toxic chemicals, and even modify bacteria to hunt and kill tumors. There are, however, numerous challenges to design with genetic material. For example, genetic circuits are composed of very noisy components making their behavior more asynchronous, analog, and non-deterministic in nature. Therefore, design methods must be adapted to consider these issues. Interestingly, future electrical circuits may soon also face these challenges which opens up the very intriguing idea that these new design methods may in the future be utilized to produce more robust and power efficient electrical circuits.
Christopher R. Myers (Cornell University) Cellular information processing in the face of promiscuity and sloppiness
Abstract: Cellular information processing is carried out by complex biomolecular networks that are able to function reliably despite environmental noise and genetic mutations. The robustness and evolvability of biological systems is supported in part by neutral networks and neutral spaces that allow for the preservation of phenotype despite underlying genotypic variation. This talk will describe two such spaces. The first are sequence niches that emerge in the process of satisfying constraints needed to avoid crosstalk among sets of promiscuous and paralogous proteins. The second are highly anistropic, sloppy parameter spaces that arise in multiparameter models of biomolecular networks. Implications of the structure of these spaces for cellular information processing will be discussed.
Theoden Netoff (University of Minnesota) Dynamical approaches to understanding epilepsy
Abstract: Epilepsy is a dynamical disease of networks of neurons. I will talk about the different mathematical analysis tools used in our lab to help us understand the basic mechanisms of epilepsy. To understand this disease we need to bridge cellular activity to network activity. We use phase response curves to bridge changes at the cellular level to changes in behavior at the network level. To measure from hundreds of neurons simultaneously, we image slices of brain stained with calcium dyes. Processing the movies into a format that can be easily interpreted is another daunting task. We use independent component analysis and diffusion maps to process our data.
Donald Pfaff (Rockefeller University) Reverse engineering the lordosis behavior neuronal circuit
Abstract: For the simple reproductive behavior exhibited by female quadrupeds, the neural circuit and several genomic modules have been worked out (Drive, MIT Press, 1999). Feedback is most prominent in the hormonal mechanisms that support the behavior, whereas most of the behavioral dynamics exhibit feedforward relations. Emboldened by the success of the analysis of this simple behavior, we've enlarged the focus of our lab's work to encompass sexual arousal and generalized CNS arousal (Brain Arousal, Harvard Univ. Press, 2006). Shannon's information theoretical calculations probably apply to CNS arousal and its (universal) complementary phenomenon, habituation. We have speculated (BioEssays, August 2007) that in an animal or human at rest, CNS arousal systems live in a chaotic domain and quickly go through a phase transition to orderly dynamics as the animal or human responds. We are testing this theoretical idea with simulations of neural nets and with deep brain stimulation that raises the arousal level of a brain damaged animal.
Aravind R. Rammohan (Corning) Interaction of lipid bilayers with inorganic surfaces: experiments to modeling
Abstract: Joint work with David R. Heine and Jitendra Balakrishnan. Lipid bilayers typically serve as the scaffold for trans membrane protein receptors. These membrane protein receptors are targets for atleast 50% of the drug molecules developed by pharmaceutical companies. Drug development and testing typically is carried out in an invitro environment with these lipid membranes deposited on some synthetic surface organic or inorganic. Here we present details of the interactions between lipid bilayers and inorganic surfaces. The approach adopted to develop an understanding of these interactions has been a combination of a multiscale modeling framework in conjunction with specific experimental effort to complement the modeling effort. The multiscale modeling effort involves modeling the membrane surface interactions in detail at an atomistic level to looking at macroscopic membrane dynamics on surfaces with specific topologies. The experimental effort involves a combination of Surface Force Apparatus (SFA) and Atomic Force Microscopic (AFM) measurements to generate these insights. The talk will focus specifically on the role of surface topology in modulating membrane surface interactions.
Eric J. Rawdon (University of St. Thomas) Size and shape of polymers
Abstract: We use numerical simulations to investigate how chain length and knotting in freely fluctuating knotted polymer rings affect their size and shape. In particular, we find smallest containers, such as rectangular boxes, spheres, and polyhedra, which contain the simulated polymers. Ideal knots, and their relationship to the containers, also will be discussed.
Michael A. Savageau (University of California) Generic approach to construction of system design space
Abstract: Determining quality of performance for a biological system is critical to identifying and elucidation its design principles. This important task is greatly facilitated by enumeration of regions within the system's design space that exhibit qualitatively distinct function. First, I will review a few examples of design spaces that have proved useful in revealing design principles for elementary gene circuits. Then I will present a recently developed approach to the generic construction of design spaces, illustrate its application to common classes of biochemical network motifs, and test predictions for a specific class with experimental data from human erythrocytes.
Michael Schendel (Medtronic) Challenges for numerical analysis in medical device industries
Abstract: This presentation will provide an overview of how numerical analyses are currently being used in the development and reliability investigations for implantable medical devices. Specific emphasis will be given on the current methods being used and additionally the barriers to the usefulness of these numerical predictions.
Peter H. Schwartz (Indiana University Center for Bioethics and Indiana University School of Medicine) Pluralism about function
Abstract: There is no question that "systematic" functional analysis, which explains the capacities or features of a system based on interactions among its parts, plays an important role in biology. But an important role is also played by "selectionist" functional analysis, where engineering or design principles carry explanatory weight based on the action of natural selection. While some have questioned the legitimacy of selectionist functional analysis, asserting that it involves illegitimate teleological notions or an incorrect understanding of evolutionary theory, careful work by philosophers of biology over the last 35 years has helped explicate and defend this approach. Uses of the concept of function in biology may be interpreted, based on context, in terms of one or the other type of functional analysis, and sometimes in terms of both, and thus pluralism about function should be embraced.
Anirvan Sengupta (Rutgers University) Modeling epigenetic silencing
Abstract: We formulate a mathematical version of the conventional model of maintenance of silencing in S. cerevisiae and analyze the conditions for bistability as well as for formation of stationary boundaries. Although the model is perhaps too simple, the structure of the bifurcation diagram, describing parameter regions with different kinds of qualitative behavior, is likely to be more robust. We can place some of the known mutants in different regions of this diagram. One interesting finding of this study is that, under some conditions, the lowering of acetylation rates might have non-obvious consequences for silencing. Possible improvements of the model as well as experimental tests are discussed at the end.
Eduardo D. Sontag (Rutgers University) Monotone input/output systems as a technique for modular analysis of biomolecular network dynamics
Abstract: This talk present the basic ideas underlying a method developed by the speaker and his collaborators, for the analysis of the dynamics of certain biomolecular systems.
John J. Tyson (Virginia Polytechnic Institute and State University) Lecture 1: Cell physiology, molecular biology and mathematical modeling
Abstract: An introduction to cell growth and division, programmed cell death, cell differentiation, motility, and signaling. Basic molecular mechanisms governing these processes. Modeling molecular mechanisms with ordinary differential equations.
John J. Tyson (Virginia Polytechnic Institute and State University) Lecture 2: Network motifs: sniffers, buzzers, toggles and blinkers
Abstract: Simple models of regulatory motifs. Positive and negative feedback. Signal-response curves and bifurcation diagrams. Adaptation. Ultrasensitivity. Bistability and oscillations. Simple bifurcations: saddle-node and Hopf. Homoclinic bifurcations.
John J. Tyson (Virginia Polytechnic Institute and State University) Lecture 3: Cell cycle regulation
Abstract: Physiological characteristics of the cell division cycle. Molecular biology of cyclin-dependent kinases. Simple model of bistability and oscillations in the CDK control system of frog eggs. More complex models of yeast cell cycles. Mammalian cell cycle and cancer.
Dan Valente (Cold Spring Harbor Laboratory) Trajectory measures describing the locomotor behavior of Drosophila melanogaster in a circular arena
Abstract: Measuring locomotor behavior of Drosophila in enclosed arenas is a powerful way to obtain a quantitative behavioral phenotype. The measures previously used for this purpose are relatively coarse, thus ignoring fine scale movements of the fly. More importantly, they do not explicitly take into account how the arena shapes the dynamics of the locomotion. We acquired data using a video-tracking system to measure the trajectory of a fly over extended periods as it explores a circular arena. Based on this data, we present some metrics that take into consideration the dynamics of the trajectory, as well as the interactions of the trajectory with the geometry of the arena. The basic idea is to treat the locomotor trajectory of the fly as a stochastic process, and then estimate a set of marginal distributions of the probability measure describing this process. The measures include joint or individual distributions of position, speed, path curvature, inter-event times and re-orientation angles after stopping. These probability measures can be worked into other behavioral setups, are relatively easy to calculate using robust statistical estimation procedures, and can account for environmental effects on the behavior. They also serve as foundation for a quantitative stochastic process model of the walking behavior.
Glenn Vinnicombe (University of Cambridge) Fundamental limitations on noise reduction in the cell
Abstract: It is well known that, for a molecule being produced in an unregulated manner and degraded exponentially (constitutive gene expression for example) the intrinsic noise in the molecule number will be such that variance equals the mean. This talk will establish fundamental limits on the amount of noise reduction that can be obtained by regulation when delays in the mechanism (due to transport and the finite time required to synthesize intermediate molecules) and when that mechanism has limited information carrying capacity in the sense of Shannon (due to itself involving finite numbers of molecules).
Haibin Wang (Cold Spring Harbor Laboratory) Evolution of song culture in the zebra finch
Abstract: A number of Oscine songbirds are vocal learners. In these species, song shares a remarkable characteristic with human language: both are acquired through imitative learning. When reared in social and acoustic isolation, the Zebra Finch (the species of songbird under study here) can still sing, revealing the genetically encoded aspect of song. However, the isolate songs usually have longer syllables, and appear to be more variable than the wild type (WT) songs found in the wild or in laboratory colonies. In order to understand how the isolate song might evolve over multiple generations, we successively trained naïve juveniles starting with an isolate founding father. The first generation learners are in turn used as tutors to train the next generation, and so on. Thus, tutoring lineages are established through a recursive training processes. We found that small, yet systematic variations accumulate over generations of training. Remarkably, the descendants’ song structures are gradually transformed towards WT songs.
Visitors in Residence
Claudio Altafini International School for Advanced Studies (SISSA/ISAS) 4/15/2008 - 5/15/2008
Douglas N. Arnold University of Minnesota 7/15/2001 - 6/30/2008
Donald G. Aronson University of Minnesota 9/1/2002 - 8/31/2009
Anand R. Asthagiri California Institute of Technology 4/20/2008 - 4/25/2008
Bassam Bamieh University of California 4/20/2008 - 4/25/2008
Sankar Basu National Science Foundation 4/20/2008 - 4/25/2008
Daniel J. Bates University of Minnesota 9/1/2006 - 8/31/2008
John Baxter University of Minnesota 8/1/2007 - 7/30/2009
Banu Baydil Rensselaer Polytechnic Institute 3/1/2008 - 6/30/2008
Robert C. Berwick Massachusetts Institute of Technology 4/24/2008 - 4/25/2008
Prateek Bhansali University of Minnesota 4/21/2008 - 4/25/2008
Yermal Sujeet Bhat University of Minnesota 9/1/2006 - 8/31/2008
Kaushik Bhattacharya California Institute of Technology 4/28/2008 - 4/30/2008
Sudin Bhattacharya The Hamner Institutes for Health Sciences 4/16/2008 - 4/25/2008
Khalid Boushaba Iowa State University 1/15/2008 - 6/30/2008
Hans C. Breiter MD Massachusetts General Hospital 4/20/2008 - 4/25/2008
Don Button University of Alaska 4/17/2008 - 4/18/2008
Maria-Carme T. Calderer University of Minnesota 4/17/2008 - 4/25/2008
Hannah Callender University of Minnesota 9/1/2007 - 8/31/2009
John R. Cannon University of Central Florida 4/16/2008 - 4/26/2008
James A Carlson Clay Mathematics Institute 4/20/2008 - 4/25/2008
John Chadam University of Pittsburgh 4/28/2008 - 4/30/2008
Dmitri Chklovskii Cold Spring Harbor Laboratory 4/23/2008 - 4/25/2008
Yung-Sze Choi University of Connecticut 4/1/2008 - 5/31/2008
Sean P Corum University of Minnesota 4/21/2008 - 4/25/2008
Ludovica Cecilia Cotta-Ramusino University of Minnesota 10/1/2007 - 8/30/2009
Robert Cummins University of Illinois at Urbana-Champaign 4/23/2008 - 4/24/2008
Debopriya Das Lawrence Berkeley Laboratory 4/20/2008 - 4/22/2008
Tim Denison Medtronic 4/21/2008 - 4/25/2008
David Dill Stanford University 4/20/2008 - 4/25/2008
Kequan Ding Chinese Academy of Sciences 4/15/2008 - 5/31/2008
Marko Djordjevic Ohio State University 4/20/2008 - 4/25/2008
John C. Doyle California Institute of Technology 4/20/2008 - 4/24/2008
Olivier Dubois University of Minnesota 9/3/2007 - 8/31/2009
Geir Dullerud University of Illinois at Urbana-Champaign 4/20/2008 - 4/25/2008
Hana El-Samad University of California 4/20/2008 - 4/25/2008
Haitao Fan Georgetown University 4/20/2008 - 4/25/2008
Peng Feng Florida Gulf Coast University 4/16/2008 - 4/19/2008
W. Tecumseh Fitch University of St. Andrews 4/20/2008 - 4/25/2008
Christodoulos A. Floudas Princeton University 4/1/2008 - 6/30/2008
Daniel Forger University of Michigan 4/16/2008 - 4/26/2008
Melissa Gardner University of Minnesota 4/21/2008 - 4/25/2008
Jason E. Gower University of Minnesota 9/1/2006 - 8/31/2008
Chenjie Gu University of Minnesota 4/21/2008 - 4/25/2008
Robert Guy University of California 3/24/2008 - 6/24/2008
Esfandiar Haghverdi Indiana University 1/2/2008 - 6/30/2008
Susan Hamm National Science Foundation 4/28/2008 - 4/30/2008
Milena Hering University of Minnesota 9/1/2006 - 8/31/2008
Thomas Hillen University of Alberta 4/27/2008 - 5/10/2008
Franziska Babette Hinkelmann Virginia Polytechnic Institute and State University 4/16/2008 - 4/26/2008
Peter Hinow University of Minnesota 9/1/2007 - 8/31/2009
C.P. Hunter Harvard University 4/20/2008 - 4/25/2008
Richard D. James University of Minnesota 9/4/2007 - 6/30/2008
Imre M. Jánosi Eötvös Loránd University (ELTE) 2/1/2008 - 6/30/2008
Tiefeng Jiang University of Minnesota 9/1/2007 - 6/30/2008
Mihailo Jovanovic University of Minnesota 4/21/2008 - 4/25/2008
Hans Kaper National Science Foundation 4/28/2008 - 4/30/2008
Fumiaki Katagiri University of Minnesota 4/17/2008 - 4/18/2008
Sheldon Katz University of Illinois at Urbana-Champaign 4/28/2008 - 4/30/2008
Mustafa H. Khammash University of California 4/20/2008 - 4/25/2008
Varunyu Khamviwith University of Minnesota 4/17/2008 - 4/18/2008
David Kleinfeld University of California, San Diego 4/20/2008 - 4/25/2008
Debra Knisley East Tennessee State University 8/17/2007 - 6/1/2008
Jeff Knisley East Tennessee State University 4/2/2008 - 4/2/2008
Robert V. Kohn New York University 4/28/2008 - 4/29/2008
Peter R. Kramer Rensselaer Polytechnic Institute 1/8/2008 - 6/30/2008
Ilya A. Krishtal Northern Illinois University 4/18/2008 - 4/20/2008
Juan Latorre Rensselaer Polytechnic Institute 1/10/2008 - 6/30/2008
Reinhard Laubenbacher Virginia Polytechnic Institute and State University 4/20/2008 - 4/24/2008
Anton Leykin University of Minnesota 8/16/2006 - 8/15/2008
Patrick D Lincoln SRI International 4/20/2008 - 4/23/2008
Chun Liu Pennsylvania State University 4/28/2008 - 5/3/2008
Deborah F. Lockhart National Science Foundation 4/28/2008 - 4/30/2008
James Lu Johann Radon Institute for Computational and Applied Mathematics 4/16/2008 - 4/19/2008
Roger Y. Lui Worcester Polytechnic Institute 9/1/2007 - 6/30/2008
Laura Lurati University of Minnesota 9/1/2006 - 8/31/2008
Suping Lyu Medtronic 4/17/2008 - 4/18/2008
Oluwole Daniel Makinde University of Limpopo 4/20/2008 - 4/26/2008
Yi Mao Michigan State University 4/20/2008 - 4/25/2008
Peter D. March Ohio State University 4/28/2008 - 4/30/2008
Ezio Marchi Instituto de Matemática Aplicada 4/15/2008 - 4/25/2008
Catherine Mavriplis University of Oklahoma 4/28/2008 - 4/30/2008
Curt McNamara Logic Product Development 4/21/2008 - 4/25/2008
George Michailidis University of Michigan 4/20/2008 - 4/25/2008
Ezra Miller University of Minnesota 9/1/2007 - 6/30/2008
Bud Mishra New York University 4/20/2008 - 4/25/2008
Partha P. Mitra Cold Spring Harbor Laboratory 4/20/2008 - 4/25/2008
Alejandro Morales Valencia University of Guadalajara 4/16/2008 - 4/26/2008
Jeff Morgan University of Houston 4/17/2008 - 4/18/2008
Richard M. Murray California Institute of Technology 4/20/2008 - 4/25/2008
Chad L. Myers University of Minnesota 4/1/2008 - 4/1/2008
Chris J. Myers University of Utah 4/20/2008 - 4/25/2008
Christopher R. Myers Cornell University 4/20/2008 - 4/25/2008
Theoden Netoff University of Minnesota 4/17/2008 - 4/18/2008
Timothy Newman Arizona State University 9/1/2007 - 6/30/2008
Duane Nykamp University of Minnesota 9/1/2007 - 6/30/2008
David Odde University of Minnesota 1/9/2008 - 6/30/2008
Isamu Ohnishi Hiroshima University 4/16/2008 - 4/26/2008
Hans G. Othmer University of Minnesota 9/1/2007 - 6/30/2008
Antonis Papachristodoulou University of Oxford 4/19/2008 - 4/24/2008
Donald Pfaff Rockefeller University 4/22/2008 - 4/24/2008
Bobby Philip Los Alamos National Laboratory 4/16/2008 - 5/30/2008
Mary Porter University of Minnesota 4/17/2008 - 4/18/2008
Christine Queitsch Harvard University 4/20/2008 - 4/25/2008
Sharad Ramanathan Harvard University 4/20/2008 - 4/25/2008
Aravind R. Rammohan Corning 4/3/2008 - 4/4/2008
Eric J. Rawdon University of St. Thomas 1/10/2008 - 6/30/2008
Donald Richards Pennsylvania State University 4/28/2008 - 4/30/2008
Beatrice M. Riviere University of Pittsburgh 4/16/2008 - 4/18/2008
Leonid Rubchinsky Indiana University-Purdue University 4/16/2008 - 4/19/2008
Fadil Santosa University of Minnesota 4/23/2008 - 5/1/2008
Michael A. Savageau University of California 4/19/2008 - 4/25/2008
Jeffery G. Saven University of Pennsylvania 3/19/2008 - 6/10/2008
Michael Schendel Medtronic 4/11/2008 - 4/11/2008
Deena Schmidt University of Minnesota 9/1/2007 - 8/31/2009
Peter H. Schwartz Indiana University Center for Bioethics and Indiana University School of Medicine 4/23/2008 - 4/23/2008
Anirvan Sengupta Rutgers University 4/20/2008 - 4/25/2008
Gaukhar Shaikhova The L.N.Gumilyov Eurasian National University 4/15/2008 - 4/29/2008
Chehrzad Shakiban University of Minnesota 9/1/2006 - 8/31/2008
Lei Shi University of Minnesota 4/21/2008 - 4/24/2008
Ali Shojaie University of Michigan 4/17/2008 - 4/18/2008
Eduardo D. Sontag Rutgers University 4/20/2008 - 4/25/2008
Andrew Stein University of Minnesota 9/1/2007 - 8/31/2009
De Witt L. Sumners Florida State University 4/22/2008 - 4/30/2008
Vladimir Sverak University of Minnesota 9/1/2007 - 6/30/2008
Erkan Tüzel University of Minnesota 9/1/2007 - 8/31/2009
John J. Tyson Virginia Polytechnic Institute and State University 4/16/2008 - 4/18/2008
Dan Valente Cold Spring Harbor Laboratory 4/20/2008 - 4/25/2008
Prashanthi Vemuri Mayo Clinic 4/21/2008 - 4/25/2008
Glenn Vinnicombe University of Cambridge 4/20/2008 - 4/25/2008
Haibin Wang Cold Spring Harbor Laboratory 4/20/2008 - 4/25/2008
Haiyan Wang Arizona State University 4/16/2008 - 4/23/2008
Jin Wang SUNY 4/20/2008 - 4/26/2008
Zhian Wang University of Minnesota 9/1/2007 - 8/31/2009
Chris Warren University of Minnesota 4/17/2008 - 4/18/2008
Hans Weinberger University of Minnesota 2/13/2008 - 6/30/2008
Zhijun Wu Iowa State University 9/4/2007 - 6/1/2008
Richard Yamada University of Michigan 4/16/2008 - 4/26/2008
Yuncheng You University of South Florida 4/16/2008 - 4/20/2008
Hongchao Zhang University of Minnesota 9/1/2006 - 8/31/2008
Legend: Postdoc or Industrial Postdoc Long-term Visitor

IMA Affiliates:
3M, Arizona State University, Boeing, Carnegie Mellon University, Corning, ExxonMobil, Ford, General Electric, General Motors, Georgia Institute of Technology, Honeywell, IBM, Indiana University, Iowa State University, Johnson & Johnson, Kent State University, Lawrence Livermore National Laboratory, Lockheed Martin, Los Alamos National Laboratory, Medtronic, Michigan State University, Michigan Technological University, Microsoft Research, Mississippi State University, Motorola, Northern Illinois University, Ohio State University, Pennsylvania State University, Purdue University, Rice University, Rutgers University, Sandia National Laboratories, Schlumberger-Doll, Schlumberger-Doll Research, Seoul National University, Siemens, Telcordia, Texas A & M University, University of Central Florida, University of Chicago, University of Cincinnati, University of Delaware, University of Houston, University of Illinois at Urbana-Champaign, University of Iowa, University of Kentucky, University of Maryland, University of Michigan, University of Minnesota, University of Notre Dame, University of Pittsburgh, University of Tennessee, University of Texas, University of Wisconsin, University of Wyoming, US Air Force Research Laboratory, Wayne State University, Worcester Polytechnic Institute