Title: Geometric Algorithms for Structural Biology 报告人：居涛,Washington University in St. Louis 时间：7月20日下午3:00-4:00
地点：蒙民伟楼311会议室 Abstract: Structural biology is concerned with the 3D shape of
molecular complexes, and is also rich in geometric problems. This talk
will focus on two such problems, and our algorithmic solutions, that
are involved in recovering 3D protein structures from experimental
images. The first problem is how to identify tubular and plate-like
parts on a 3D object. In our image data, these two kinds of shapes
correspond respectively to key protein structures known as
alpha-helices and beta-sheets. I will present algorithms that convert a
3D object into a set of low-dimensional curves and surfaces,
representing respectively the two kinds of shape parts. The second
problem is how to establish the correspondence between two sets of
spatial features. Such correspondence could help biologists to recover
an unknown structure imaged at a low resolution from known structures,
based on sparse features identified from the low resolution images. I
will present a recent graph-based feature matching algorithm that uses
multiple rigid-body transformations. These algorithms, along with
several others, are distributed freely in our interactive molecular
modeling software, Gorgon. Bio: Tao Ju is an Associate Professor in the Department of Computer
Science and Engineering at the Washington University in St. Louis
(USA). He obtained his PhD degree in Computer Science from Rice
University (Houston, USA) in 2005, and his Bachelor degree from
Tsinghua University (Beijing, China) in 2000. His research area is
computer graphics, with focuses on geometric processing and
applications in bio-medicine. Dr. Ju has published in top venues in
both graphics and biology, including ACM Transactions on Graphics, IEEE
Transactions on Visualization and Computer Graphics, Structure, and
PLoS Computational Biology. He regularly serves on program committees
of premier forums including ACM SIGGRAPH, Eurographics and Pacific
Graphics. His work is supported by funds from NSF and NIH, including a
NSF CAREER Award in 2009.
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