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                       BIOINFORMATICS COLLOQUIUM
                    School of Computational Sciences
                        George Mason University
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       Computational Analysis and Comparison of Protein Structure

                           Iosif Vaisman
                                GMU

                      Tuesday, February 10, 2004
                               4:30 pm
               Verizon Auditorium, Prince William Campus

Two metrics (the Euclidean metric for identifying natural nearest
neighboring residues via the Delaunay tessellation in Cartesian space
and the distance between residues in sequence space) are used for a
novel topological representation of proteins.  Using this
representation, we introduce a quantitative and computationally
inexpensive method for the comparison of protein structural
topology. The method ultimately results in a numerical score quantifying
the distance between proteins in a heuristically defined topological
space. The properties of this scoring scheme are investigated and
correlated with the standard C distance root-mean-square deviation
measure of protein similarity calculated by rigid body structural
alignment. The topological comparison method is shown to have a
characteristic dependence on protein conformational differences and
secondary structure.  The ability of the comparison method to
successfully classify proteins into classes, superfamilies, folds, and
families that are consistent with standard classification methods, both
automated and human-driven, is demonstrated.

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