Generating Models that Predict

Haluk Resat, Session Chair

Generating Models that Predict will outline the process of converting biological data into descriptive and predictive models. Topics will range from how to deal with high-resolution spatial and temporal data, to applying data mining to new technologies, to the ability to use models to reprogram simple responses.

Session 2 Speakers

Mariko Hatakeyama, RIKEN Genomic Sciences Center, Yokohama, Japan, "Model-Aided Analysis of Cellular Signal Transduction Pathways"
Tim Galitski, Institute for Systems Biology, " Modeling the Control of Yeast Cell Differentiation"
Joanne Kelleher, Massachusetts Institute of Technology, " Mining Metabolomic Data for Systems Biology"
Haluk Resat, Pacific Northwest National Laboratory, "Modeling Signal Transduction in Space and Time"