Title: Elastic Principal Graphs and Topological Grammars for Data Approximation
Speaker: Andrei Zinovyev, Institut Curie, Paris
Date: Tuesday, March 20, 2007 12:00 - 1:30 pm
Location: DyDan Center, CoRE Bldg, Room 431, Rutgers University, Busch Campus, Piscataway, NJ
Abstract:
Principal manifolds are defined as lines or surfaces passing through ``the middle'' of data distribution. Linear principal manifolds (Principal Components Analysis) are routinely used for dimension reduction, noise filtering and data visualization. Recently, methods for constructing non-linear principal manifolds were proposed, including our elastic maps approach which is based on a physical analogy with elastic membranes. We have developed a general geometric framework for constructing principal objects of various dimensions and topologies, including 'principal trees' and principal cubic complexes. In my talk I overview the method and its application to analysis of high-throughput data in molecular biology.