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I2 Lab Distinguished Seminar Series
Technical Lecture
Geometry and Signal Processing for Modeling Bio-Molecular Interactions

Dr. Chandrajit Bajaj
Thursday, January 11, 2007
4:00PM ENGR3-101

Abstract


Biological molecules (proteins, nucleic acids, etc.) have distinct three-dimensional structures that dictate not only their function, but also their interaction within their native cellular environment. Additionally, the intrinsic biophysical properties such as electrostatic potentials and hydrophobicity help to determine the mechanistic behaviors of individual macromolecules and their complexes. The understanding of both the physical and chemical properties becomes paramount in the successful application of structural and molecular information in areas such as drug discovery, and disease therapy. Complicating the analytics still further is the fact that most molecules are flexible, being able to adopt a number of different conformations that are of similar energy. For this reason, the rigid-model approximations once used to represent molecules are not sufficient to provide adequate predictions of chemical and physiological activity. Advances in the computational power, on the other hand, now allows less restrictive and more dynamic models of bio-molecular complexes to be employed in computations and simulations. In this talk I shall cover several geometric and signal processing algorithms that are required to support both the elucidation of atomic and quasi-atomic models of macromolecules from electron microscopy, and the validation of flexible and dynamic models of bio-molecular interactions.

Short Bio


Chandrajit Bajaj is the Computational Applied Mathematics Chair in Visualization Professor of computer science at the University of Texas at Austin , as well as the director of the Center for Computational Visualization, in the Institute for Computational and Engineering Sciences (ICES). He graduated from the Indian Institute of Technology, Delhi with a Bachelor's Degree in Electrical Engineering, in 1980 and received his M.S. and Ph.D. degrees in Computer Sciences from Cornell University , in 1983, and 1984 respectively. Prior to the University of Texas , Bajaj was a professor of computer sciences at Purdue University and director of the Purdue center for image analysis and visualization. Bajaj's research areas span Image Processing, Geometric Modeling, Computer Graphics, Visualization, and Computational Mathematics. His current research topics include de-noising, reconstruction and compression algorithms for volumetric and time-dependent imaging; as well as data structures that support multi-resolution finite element approximations of large geometries and multiple function fields. Bajaj has been developing integrated approaches to computational modeling, simulations, mathematical analysis and interrogative visualization, especially for dynamic bio-medical phenomena.

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