|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 DiegoNOTE THAT E-MAIL ADDRESSES HAVE BEEN MODIFIED!!!
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