Structuring Cellular Data for Computational Modeling
Shankar Subramaniam
University of California, San Diego
Until recently our understanding of cellular systems has come from descriptive biology unique to each experimental investigation. This has inhibited our ability to draw generalized hypotheses that would in turn enable computational modeling in microscopic detail. The advent of high throughput biology and the emergence of comparative genomics approaches, provides for the first time, the ability to create more modular and quantitative definitions of sub-cellular systems. The iterative cycles between modeling and hypothesis will help us in formulating a systems approach to biology. This talk will explore approaches and barriers to structuring biological data that will aid mathematical modeling.
Created: 5/6/02 DAR
Edited: 5/6/02