Publications
Profiles of Basal and stimulated receptor signaling networks predict drug response in breast cancer lines. Sci Signal. 2013;6(294):ra84.
. Protein kinases display minimal interpositional dependence on substrate sequence: potential implications for the evolution of signalling networks. Philos Trans R Soc Lond B Biol Sci. 2012;367(1602):2574-83.
. Qualitatively different T cell phenotypic responses to IL-2 versus IL-15 are unified by identical dependences on receptor signal strength and duration. J Immunol. 2014;192(1):123-35.
. Quantitative analysis of EGFRvIII cellular signaling networks reveals a combinatorial therapeutic strategy for glioblastoma. Proc Natl Acad Sci U S A. 2007;104(31):12867-72.
. Quantitative analysis of gradient sensing: towards building predictive models of chemotaxis in cancer. Curr Opin Cell Biol. 2012;24(2):284-91.
. Quantitative analysis of signaling networks across differentially embedded tumors highlights interpatient heterogeneity in human glioblastoma. J Proteome Res. 2014;13(11):4581-93.
. Quantitative phosphoproteomic analysis of signaling network dynamics. Curr Opin Biotechnol. 2008;19(4):404-9.
. . Rapid phospho-turnover by receptor tyrosine kinases impacts downstream signaling and drug binding. Mol Cell. 2011;43(5):723-37.
. The receptor AXL diversifies EGFR signaling and limits the response to EGFR-targeted inhibitors in triple-negative breast cancer cells. Sci Signal. 2013;6(287):ra66.
. Robust co-regulation of tyrosine phosphorylation sites on proteins reveals novel protein interactions. Mol Biosyst. 2012;8(10):2771-82.
. SAMNet: a network-based approach to integrate multi-dimensional high throughput datasets. Integr Biol (Camb). 2012;4(11):1415-27.
. SAMNetWeb: identifying condition-specific networks linking signaling and transcription. Bioinformatics. 2015;31(7):1124-6.
. Sequential application of anticancer drugs enhances cell death by rewiring apoptotic signaling networks. Cell. 2012;149(4):780-94.
. Signaling network state predicts twist-mediated effects on breast cell migration across diverse growth factor contexts. Mol Cell Proteomics. 2011;10(11):M111.008433.
. Simultaneous reconstruction of multiple signaling pathways via the prize-collecting steiner forest problem. J Comput Biol. 2013;20(2):124-36.
. Sloppy models, parameter uncertainty, and the role of experimental design. Mol Biosyst. 2010;6(10):1890-900.
. Spatial exclusivity combined with positive and negative selection of phosphorylation motifs is the basis for context-dependent mitotic signaling. Sci Signal. 2011;4(179):ra42.
. SteinerNet: a web server for integrating 'omic' data to discover hidden components of response pathways. Nucleic Acids Res. 2012;40(Web Server issue):W505-9.
. Stimulus design for model selection and validation in cell signaling. PLoS Comput Biol. 2008;4(2):e30.
. Structural determinants of 14-3-3 binding specificities and regulation of subcellular localization of 14-3-3-ligand complexes: a comparison of the X-ray crystal structures of all human 14-3-3 isoforms. Semin Cancer Biol. 2006;16(3):173-82.
. Studying Cellular Signal Transduction with OMIC Technologies. J Mol Biol. 2015;427(21):3416-40.
. Swimming upstream: identifying proteomic signals that drive transcriptional changes using the interactome and multiple "-omics" datasets. Methods Cell Biol. 2012;110:57-80.
. Systematic discovery of in vivo phosphorylation networks. Cell. 2007;129(7):1415-26.
. Toward quantitative phosphotyrosine profiling in vivo. Semin Cell Dev Biol. 2012;23(8):854-62.
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