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Up Directory CCL 09.11.11 Algorithms for Macromolecular Modeling (AM^3), Austin, Texas
From: chemistry-request at ccl.net
To: chemistry-request at ccl.net
Date: Wed Jul 1 06:54:24 2009
Subject: 09.11.11 Algorithms for Macromolecular Modeling (AM^3), Austin, Texas
url: http://www.ices.utexas.edu/ices/am3/
dates: 11/11/2009 - 11/15/2009
contact: Ruth Hengst ruth "at" ices.utexas.edu

Scope: 
With advances in multi-core systems, special purpose hardware and software,
and in algorithms and physics-based theory, molecular modeling and 
simulation has become a standard partner to experiment. Computer simulations
help to create plausible atomic structures from low-resolution images of 
large biomolecular complexes, and link the static experimental structures of
proteins and nucleic acids with their dynamic behavior in aqueous solution
and realistic environment of the cell. Molecular dynamics (MD) and other
modeling and simulation techniques can offer an effective tool for refining
experimental models and for probing systematically how molecules fold and
reshape and perform the basic functions of life. Modeling provides
comprehensive atomically detailed picture of the process that supplement
the average and more limited experimental information. Yet many fundamental
and practical limitations face biomolecular modelers. they include the 
approximate nature of the governing force fields as well as simulation 
protocols, the limited range of configurational sampling and relatively
short trajectory times, the neglect of quantum effects in 
classical molecular dynamics, and the enormous computational 
requirements (needed to simulate a solvated macro-molecular
system with full details of the environment). New
algorithmic approaches, hierarchical spatial representations, and improved
computing platforms are thus continuously in demand to enhance the
reliability of macromolecular simulations, enhance the scope of theoretical
 work, and address biological problems with great specificity.
In light of the highly multidisciplinary nature of macromolecular modeling,
educational efforts are also crucial for training the current generation of
young biomolecular modelers.
  

Invited Speakers
    * Giovanni Ciccotti University of Rome La Sapienza
    * Ulrich Hansmann Michigan Technological University
    * Ben Leimkuhler University of Edinburgh
    * Tamar Schlick The New York University
    * Robert Skeel Purdue University
    * De Witt Sumners Florida State University
    * Steve Bond University of Illinois at Urbana-Champaign
    * Giovanni Cicotti University of Rome La Sapienza
    * Eric Darve Stanford University
    * Jiali Gao University of Minnesota
    * Ulrich H.E. Hansmann Michigan Technological Institute
    * Christine Heitsch Georgia Tech
    * Bob Jernigan Iowa State University
    * L.V. Kale University of Illinois at Urbana-Champaign
    * Michael Klein University of Pennsylvania
    * Ben Leimkuhler University of Edinburgh
    * John F. Marko Northwestern University
    * Jaroslaw Meller University of Cincinnati College of Medicine
    * Vijay Pande Stanford University
    * Keshav Pingali ICES, The University of Texas at Austin
    * Benoit Roux University of Chicago
    * Harold Scheraga Cornell University
    * Tamar Schlick New York University
    * David ShawD.E Shaw Research, LLC
    * Carlos Simmerling State University of New York
    * Bob Skeel Purdue University
    * Jeff Skolnick Georgia Tech
    * John Straub Boston University
    * De Witt Sumners Florida State University
    * Eric Vanden-Eijnden Courant Institute, New York University
    * Greg Voth University of Utah
    * Peter Wolynes University of California, San Diego
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