I have represented a coarse-grained model for the intra-cellular signal transduction networks as a probabilistic graphic model. New algorithms are being developed for learning the structure and parameters of the model from mRNA expression profiles of RNAi treated cells. Currently, the targeted subjects are the signaling networks in Drosophila cells. This is collaboration with the Perrimon Lab at Harvard Medical School . We have chosen to focus on protein Kinases and Phosphatases, which are biochemically related and of great interest as drug targets. The Kinases and Phosphatases will be systematically knocked out by RNA interference. Time-course mRNA expressions will be profiled after various extra-cellular stimulations both in the unperturbed and RNAi-treated cells. The gene expression data will be used as the primary data for inferring the structure of the Kinases/Phosphatases network. We have successfully designed a cDNA chip and are carrying out pilot experiments. This is a synergistic effort that integrates wet-lab and dry-lab to elucidate signaling networks.