@article {Hill039636, author = {Steven M. Hill and Nicole K. Nesser and Katie Johnson-Camacho and Mara Jeffress and Aimee Johnson and Chris Boniface and Simon E.F. Spencer and Yiling Lu and Laura M. Heiser and Yancey Lawrence and Nupur T. Pande and James E. Korkola and Joe W. Gray and Gordon B. Mills and Sach Mukherjee and Paul T. Spellman}, title = {Context-specificity in causal signaling networks revealed by phosphoprotein profiling}, elocation-id = {039636}, year = {2016}, doi = {10.1101/039636}, publisher = {Cold Spring Harbor Laboratory}, abstract = {Summary Signaling networks downstream of receptor tyrosine kinases are among the most extensively studied biological networks. However, it remains unclear whether signaling networks depend on biological context. Signaling networks encode causal influences {\textendash} and not just correlations {\textendash} between network components. Here, using a causal framework and systematic time-course assays of signaling proteins, we investigate the context-specificity of signaling networks in a cell line system. We focus on a well-defined set of signaling proteins profiled in four breast cancer cell lines under eight stimulus conditions and inhibition of specific kinases. The data, spanning multiple pathways and comprising approximately 70,000 phosphoprotein and 260,000 protein measurements, provide a wealth of testable, context-specific hypotheses, several of which we validate in independent experiments. Furthermore, the data provide a resource for computational methods development, permitting empirical assessment of causal network learning in a complex, mammalian setting.}, URL = {https://www.biorxiv.org/content/early/2016/02/15/039636}, eprint = {https://www.biorxiv.org/content/early/2016/02/15/039636.full.pdf}, journal = {bioRxiv} }