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IMA Newsletter #376

February 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.

Congratulations Arlie! We are delighted to report that one of the IMA board members, Arlie Petters, has been designated a Member of the Most Excellent Order of the British Empire by the Queen of England.

Opportunities at the IMA - If you are interested in applying for a General Membership for a period of one month to one year in residence at the IMA during the 2008-2009 thematic program: Mathematics and Chemistry , please find the application for this membership at our Applications site.

New Directions Short Course: The IMA is currently accepting applications for the 2008 New Directions Short Course - Mathematical Neuroscience June 16 - 27, 2008, taught by G. Bard Ermentrout, and Jonathan E. Rubin. This intensive short course is designed to efficiently provide researchers in the mathematical sciences and related disciplines the basic knowledge prerequisite to undertake research in mathematical neuroscience. Participation is by application only. Application deadline: April 1, 2008.

IMA Events
Schedule

Tuesday, February 5

11:15a-12:15pDesign under uncertainty using stochastic collocationLaura Lurati (University of Minnesota)Lind Hall 409 PS

Wednesday, February 6

11:15a-12:15pThree topics in the mathematics of molecular and cellular biologyRoger Y. Lui (Worcester Polytechnic Institute)Lind Hall 409 MMCB

Thursday, February 7

2:00p-3:00pWorking Seminar: Probabilistic methods in bioinformaticsChristopher J. Lee (University of California)Lind Hall 409

Friday, February 8

11:15a-12:15pApplications of numerical algebraic geometryAnton Leykin (University of Minnesota)Lind Hall 409

Tuesday, February 12

11:15a-12:15pLooping probability densities of elastic rodsLudovica Cecilia Cotta-Ramusino (University of Minnesota)Lind Hall 409 PS

Wednesday, February 13

11:15a-12:15pWhy is the microtubule lattice helical?Imre M. Jánosi (Eötvös Loránd University (ELTE))Lind Hall 409 MMCB
5:00p-6:30pReceptionLind Hall 400 PUB2.13.08
7:00p-8:15pMathematical modeling in medicine, sports, and the environmentAlfio Quarteroni (Politecnico di Milano)Willey Hall 125 PUB2.13.08

Thursday, February 14

2:00p-3:00pWorking seminar: Probabilistic methods in bioinformaticsChristopher J. Lee (University of California)Lind Hall 409 WSPMB

Friday, February 15

1:25p-2:25pLearning classifiers for computer aided diagnosis using local correlationsGlenn Fung (Siemens Medical Solution)Vincent Hall 570 IPS

Tuesday, February 19

11:15a-12:15pHomogenization of a nonlinear elliptic boundary value problem related to corrosion modelingYermal Sujeet Bhat (University of Minnesota)Lind Hall 409 PS

Wednesday, February 20

11:15a-12:15pMapping evolutionary pathways of HIV-1 drug resistance using conditional selection pressureChristopher J. Lee (University of California)Lind Hall 409 MMCB

Thursday, February 21

2:00p-3:00pWorking seminar: Probabilistic methods in bioinformaticsChristopher J. Lee (University of California)Lind Hall 409 WSPMB

Tuesday, February 26

Wednesday, February 27

11:15a-12:15pStochastic mathematical and computational models in microbiologyPeter R. Kramer (Rensselaer Polytechnic Institute)Lind Hall 409 MMCB

Thursday, February 28

2:00p-3:00pWorking seminar: Probabilistic methods in bioinformaticsChristopher J. Lee (University of California)Lind Hall 409 WSPMB
Abstracts
Yermal Sujeet Bhat (University of Minnesota) Homogenization of a nonlinear elliptic boundary value problem related to corrosion modeling
Abstract: We study a nonlinear elliptic boundary value problem motivated by a corrosion model used in the electrochemistry community in the study of heterogeneous electrode surfaces. The boundary condition is of an exponential type with periodically varying parameters. We treat the problem from the point of view of homogenization theory by constructing a first-order asymptotic approximation. We establish convergence estimates for both the two and three-dimensional case and provide two-dimensional numerical experiments.
Ludovica Cecilia Cotta-Ramusino (University of Minnesota) Looping probability densities of elastic rods
Abstract: We exploit elastic rod models to evaluate DNA looping probabilities, adopting a path integral formalism to compute approximations to the probability density function for the location and orientation of one end of a continuum elastic rod at thermodynamic equilibrium with a heat bath.
Glenn Fung (Siemens Medical Solution) Learning classifiers for computer aided diagnosis using local correlations
Abstract: computer aided diagnosis (CAD) applications the goal is to detect structures of interest to physicians in medical images: e.g. to identify potentially malignant lesions in an image (mammography, lung CT, Colon CT, heart ultrasound, etc.). In an almost universal paradigm, this problem is addressed by a 5 stage system:

1. Segmentation to identify/extract the general area of interest; 2. Candidate generation which identifies suspicious unhealthy candidate regions of interest (ROI) from a medical image; 3. feature extraction that computes descriptive features for each candidate; 4. classification that differentiates candidates based on candidate feature vectors; 5. visual presentation of CAD findings to the radiologist in order for him to accept or reject the CAD findings.

For the fourth stage, many standard algorithms (such as support vector machines (SVM), back-propagation neural nets, kernel Fisher discriminants) have been used to learn classifiers for detecting malignant structures. However, these general-purpose learning methods either make implicit assumptions that are commonly violated in CAD applications, or cannot effectively address the difficulties arisen when learning a CAD system.

Non-IID Data Traditional learning methods almost universally assume that the training samples are independently drawn from an identical albeit unobservable underlying distribution (the IID assumption), which is often not the case in CAD systems. Due to spatial adjacency of the regions identified by a candidate generator, both the features and the class labels of several adjacent candidates are highly correlated.

In this talk we present two recent proposed machine learning algorithms that successfully takes into account the correlation among candidates to significantly improve classification performance.

Peter R. Kramer (Rensselaer Polytechnic Institute) Stochastic mathematical and computational models in microbiology
Abstract: I shall discuss three areas of current research involving the use of stochastic methods for the physical modeling for microscopic processes in physiology. First, I exhibit a variation of the immersed boundary method designed, in joint work with Paul Atzberger (UCSB) and Charles Peskin (NYU) for simulating microbiological systems where thermal effects play a significant role, such as molecular motors, DNA and other polymer dynamics, and gel swelling. Statistical mechanical principles indicate that the thermal fluctuations should manifest themselves through a random force density in the fluid component of the immersed boundary equations. Secondly, I briefly review the mathematical procedure, currently being developed with Juan Latorre and Grigorios Pavliotis (Imperial), for coarse-graining stochastic molecular motor models. Finally, I shall discuss recent explorations with Adnan Khan (Lahore) and Shekhar Garde (Rensselaer, Biochemical Engineering) concerning the parameterization of a simple stochastic model for the behavior of water molecules near a solute surface which has the potential for improving substantially upon Brownian dynamics models more conventionally used in engineering applications. We use exactly solvable mathematical models as a testbed for addressing some basic data-driven parameterization issues.
Christopher J. Lee (University of California) Working Seminar: Probabilistic methods in bioinformatics
Abstract: Purpose: to discuss challenges arising from the analysis of massive datasets such as high-throughput genomics or proteomics data, and probabilistic methods for analyzing them. Chris will provide some useful introduction to various topics in each session, but leave the time open for informal discussion. Initial discussion: Introduction to the challenges of high-throughput data analysis in "post-genomic" biology, and methods of statistical inference used to solve these problems. lab webpage: http://www.bioinformatics.ucla.edu/leelab
blog: http://thinking.bioinformatics.ucla.edu
Christopher J. Lee (University of California) Working seminar: Probabilistic methods in bioinformatics
Abstract: Purpose: to discuss challenges arising from the analysis of massive datasets such as high-throughput genomics or proteomics data, and probabilistic methods for analyzing them. Chris will provide some useful introduction to various topics in each session, but leave the time open for informal discussion. Initial discussion: Introduction to the challenges of high-throughput data analysis in "post-genomic" biology, and methods of statistical inference used to solve these problems. lab webpage: http://www.bioinformatics.ucla.edu/leelab blog: http://thinking.bioinformatics.ucla.edu
Christopher J. Lee (University of California) Working seminar: Probabilistic methods in bioinformatics
Abstract: Purpose: to discuss challenges arising from the analysis of massive datasets such as high-throughput genomics or proteomics data, and probabilistic methods for analyzing them. Chris will provide some useful introduction to various topics in each session, but leave the time open for informal discussion. Initial discussion: Introduction to the challenges of high-throughput data analysis in "post-genomic" biology, and methods of statistical inference used to solve these problems. lab webpage: http://www.bioinformatics.ucla.edu/leelab blog: http://thinking.bioinformatics.ucla.edu
Christopher J. Lee (University of California) Working seminar: Probabilistic methods in bioinformatics
Abstract: Purpose: to discuss challenges arising from the analysis of massive datasets such as high-throughput genomics or proteomics data, and probabilistic methods for analyzing them. Chris will provide some useful introduction to various topics in each session, but leave the time open for informal discussion. Initial discussion: Introduction to the challenges of high-throughput data analysis in "post-genomic" biology, and methods of statistical inference used to solve these problems. lab webpage: http://www.bioinformatics.ucla.edu/leelab blog: http://thinking.bioinformatics.ucla.edu
Christopher J. Lee (University of California) Mapping evolutionary pathways of HIV-1 drug resistance using conditional selection pressure
Abstract: Can genomics provide a new level of strategic intelligence about rapidly evolving pathogens? We have developed a new approach to measure the rates of all possible evolutionary pathways in a genome, using conditional Ka/Ks to estimate their “evolutionary velocity”, and have applied this to several datasets, including clinical sequencing of 50,000 HIV-1 samples. Conditional Ka/Ks predicts the preferred order and relative rates of competing evolutionary pathways. We recently tested this approach using independent data generously provided by Shafer and coworkers (Stanford HIV Database), in which multiple samples collected at different times from each patient make it possible to track which mutations occurred first during this time-course. Out of 35 such mutation pairs in protease and RT, conditional Ka/Ks correctly predicted the experimentally observed order in 28 cases (p=0.00025). Conditional Ka/Ks data reveal specific accessory mutations that greatly accelerate the evolution of multi-drug resistance. Our analysis was highly reproducible in four independent datasets, and can decipher a pathogen’s evolutionary pathways to multi-drug resistance even while such mutants are still rare. Analysis of samples from untreated patients shows that these rapid evolutionary pathways are specifically associated with drug treatment, and vanish in its absence.
Anton Leykin (University of Minnesota) Applications of numerical algebraic geometry
Abstract: Numerical Algebraic Geometry provides a collection of new methods to treat the solutions of systems of polynomial equations. The numerical homotopy continuation technique forms a base for higher level algorithms in the area. This talk exposes three topics. First is a recent application of homotopy continuation to a problem in enumerative algebraic geometry: computation of Galois groups of Schubert problems. Second is a deflation method that restores the convergence of the Newton's method at a singular isolated solution of a polynomial system. Third is a new approach to detecting embedded components of an underlying complex variety dubbed numerical primary decomposition.
Roger Y. Lui (Worcester Polytechnic Institute) Three topics in the mathematics of molecular and cellular biology
Abstract: In this talk, I will discuss three topics in the mathematics of molecular and cellular biology. They are Protein Folding, Biochemical Network, and Cell Motility. I am an analyst by training so you are going to see a lot of equations in my talk. But I will try to make things interesting and easy to understand.
Laura Lurati (University of Minnesota) Design under uncertainty using stochastic collocation
Abstract: Optimization methods generally treat objectives, constraints and parameters as deterministic "perfectly known" values. However, this is often not the case for real problems. Uncertainty may enter the design process as early as the conceptual design phase, through manufacturing, as well as in the use/operation of the final product. Design optimization under uncertainty seeks to minimize the impact of random parameters on the design. Stochastic collocation methods are proposed as the underlying statistical method for robust/reliability design optimization using direct search methods. Examples demonstrate the ease of use of the method as well as its flexibility. Test problems include the robust design of an airfoil over a range of Mach numbers and robust/reliability design of a cantilever beam under manufacturing uncertainty. Possible modifications to the method for efficient representation of multiple random variables are discussed.
Alfio Quarteroni (Politecnico di Milano) Mathematical modeling in medicine, sports, and the environment
Abstract: Mathematical models are enabling advances in increasingly complex areas of engineering and technology. Recent developments in multiscale geometrical modeling have opened the way to progress in modeling such complex systems as the human circulatory system and the climate system. Professor Quarteroni leads a team which has harnessed mathematical modeling to design improved cardiac surgical interventions and to optimize the design of the twice winning America's cup yacht Alinghi. He will talk about this work, and their efforts to confront some of the great environmental challenges that face us.
David Umulis (University of Minnesota) Computational analysis of BMP-mediated embryonic patterning in Drosophila melanogaster
Abstract: The principal aim of developmental biology is to delineate how genes are turned on and off at the correct point in time and space to produce the multitude of specialized cell types present in the mature organism. The complexity of many developmental processes precludes an intuitive understanding of regulation at the systems level, making it difficult to construct new hypotheses and design experiments to reveal the molecular function of novel regulators. To address these challenges, we developed a unified approach that couples experimental methods such as fluorescent in situ hybridization (FISH), immunostaining, and in vitro kinetics with sophisticated 3D computational models to analyze early developmental processes in Drosophila melanogaster. In addition to elucidating molecular function, we used these mechanistic models to study the following questions, such as: How robust are developmental systems to perturbations in the underlying network structure and the quantities of the molecular regulators? How do different organisms within a species preserve proportion even though they vary substantially in body size? And, finally, how do cells respond to dynamic and noisy signals during development?
Visitors in Residence
Douglas N. Arnold University of Minnesota 7/15/2001 - 6/30/2008
Donald G. Aronson University of Minnesota 9/1/2007 - 8/31/2009
Daniel J. Bates University of Minnesota 9/1/2006 - 8/31/2008
John Baxter University of Minnesota 8/1/2007 - 7/30/2009
Yermal Sujeet Bhat University of Minnesota 9/1/2006 - 8/31/2008
Khalid Boushaba Iowa State University 1/15/2008 - 6/30/2008
Hannah Callender University of Minnesota 9/1/2007 - 8/31/2009
Ludovica Cecilia Cotta-Ramusino University of Minnesota 10/1/2007 - 8/30/2009
Olivier Dubois University of Minnesota 9/3/2007 - 8/31/2009
Glenn Fung Siemens Medical Solution 2/14/2008 - 2/16/2008
Jason E. Gower University of Minnesota 9/1/2006 - 8/31/2008
Esfandiar Haghverdi Indiana University 1/2/2008 - 6/30/2008
Milena Hering University of Minnesota 9/1/2006 - 8/31/2008
Mark Herman Virginia Polytechnic Institute and State University 2/7/2008 - 2/9/2008
Peter Hinow University of Minnesota 9/1/2007 - 8/31/2009
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
Debra Knisley East Tennessee State University 8/17/2007 - 6/1/2008
Peter R. Kramer Rensselaer Polytechnic Institute 1/8/2008 - 6/30/2008
Juan Latorre Rensselaer Polytechnic Institute 1/10/2008 - 6/30/2008
Christopher J. Lee University of California 1/10/2008 - 3/10/2008
Anton Leykin University of Minnesota 8/16/2006 - 8/15/2008
Roger Y. Lui Worcester Polytechnic Institute 9/1/2007 - 6/30/2008
Laura Lurati University of Minnesota 9/1/2006 - 8/31/2008
Ezra Miller University of Minnesota 9/1/2007 - 6/30/2008
Kenneth C. Millett University of California 1/10/2008 - 2/8/2008
Timothy Newman Arizona State University 9/1/2007 - 6/30/2008
Vincent Noireaux University of Minnesota 2/19/2008 - 2/19/2008
Duane Nykamp University of Minnesota 9/1/2007 - 6/30/2008
David Odde University of Minnesota 1/9/2008 - 6/30/2008
James Oliver University of Oxford 2/1/2008 - 5/30/2008
Hans G. Othmer University of Minnesota 9/1/2007 - 6/30/2008
Alfio Quarteroni Politecnico di Milano 2/12/2008 - 2/14/2008
Eric Rawdon University of St. Thomas 1/10/2008 - 6/30/2008
Fadil Santosa University of Minnesota 2/6/2008 - 2/10/2008
Fadil Santosa University of Minnesota 2/14/2008 - 2/16/2008
Deena Schmidt University of Minnesota 9/1/2007 - 8/31/2009
Brigitte Servatius Worcester Polytechnic Institute 1/10/2008 - 2/8/2008
Chehrzad Shakiban University of Minnesota 9/1/2006 - 8/31/2008
Andrew Stein University of Minnesota 9/1/2007 - 8/31/2009
Vladimir Sverak University of Minnesota 9/1/2007 - 6/30/2008
Erkan Tüzel University of Minnesota 9/1/2007 - 8/31/2009
David Umulis University of Minnesota 2/26/2008 - 2/26/2008
Zhian Wang University of Minnesota 9/1/2007 - 8/31/2009
Hans Weinberger University of Minnesota 2/13/2008 - 6/30/2008
Zhijun Wu Iowa State University 9/4/2007 - 6/1/2008
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