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                   B O S T O N   U N I V E R S I T Y
                      Computer Science Department
                          C O L L O Q U I U M
                      Wednesday, January 23, 3:00 PM 
                       (Coffee served at 2:45PM)
                         Seminar Room / MCS 135

			
        Systems Biology: Active Learning of Cellular Architectures.
			      
                               Simon Kasif
                            Boston University

	                         Abstract


In this talk I will describe the application of computational learning and
computer science algorithms to reverse engineering, predictive modeling
and analysis of biological cell function.

Genes and their post-translational interactions provide the basic scripts
for biological cell behavior. The problems we address include comparing of
the genomic content of human and mouse genomes, creating qualitative 
interpretations of gene expression data, and constructing functional 
gene-based models of biological cells.

In many cases the architectures we construct resemble simplistic computer
architectures and networks.  I would argue that cells can teach us a lot 
about computation, and the need to unravel the mystery of living
organisms provides an endless supply of challenging basic research problems
in computing.

Ultimately, we would like to develop the capability to program biological 
systems to do useful things or monitor and repair undesirable events which 
requires an adequate computational understanding of the biological components
and their interaction on different levels of resolution.

Host: Steve Homer
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