Signal transduction through cell surface receptors on B lymphocytes controls a diverse set of cellular responses, including cell cycle progression, apoptosis induction, cellular adhesion, etc. In order to understand how biochemical changes emanating from the receptors are translated into changes in cell physiology, the signaling field has generally focused on the analysis of single steps or single pathways in the signaling cascades. However, it is now possible to investigate signal transduction comprehensively by analyzing large numbers of molecules involved in signaling simultaneously using expression array and proteomic approaches. In order to maximize the information content of these experiments it is necessary to use bioinformatics to handle the large amounts of data generated, to develop quantitative models to analyze the data, and to go hack to biochemical and cell biological experiments to test predictions of the models developed. The specific aims of this project will be to develop a relational database to integrate data sets from multiple experimental approaches and to develop hierarchical clustering models for the computational analysis of the data generated. In the future, the final step will be to test specific aspects of these models using directed functional experiments in living cells in order to provide a comprehensive understanding of the complexities of signal transduction at a whole-cell level.