Kendall J. Blumer, Ph.D.
Affiliations: | Cell Biology and Physiology | Washington University School of Medicine, St. Louis, MO, United States |
Area:
G protein signaling, RGS proteinsGoogle:
"Kendall Blumer"Mean distance: 25647.8
Collaborators
Sign in to add collaboratorJohn Raymond Hepler | collaborator | ||
Anthony J. Muslin | collaborator | Washington University School of Medicine (Cell Biology Tree) |
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Publications
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Onken MD, Makepeace CM, Kaltenbronn KM, et al. (2021) Targeting primary and metastatic uveal melanoma with a G protein inhibitor. The Journal of Biological Chemistry. 100403 |
Sun X, Singh S, Blumer K, et al. (2018) Simulation of spontaneous G protein activation reveals a new intermediate driving GDP unbinding. Elife. 7 |
Onken MD, Makepeace CM, Kaltenbronn KM, et al. (2018) Targeting nucleotide exchange to inhibit constitutively active G protein α subunits in cancer cells. Science Signaling. 11 |
Sun X, Singh S, Blumer KJ, et al. (2018) Author response: Simulation of spontaneous G protein activation reveals a new intermediate driving GDP unbinding Elife |
Onken MD, Makepeace CM, Wang S, et al. (2018) Abstract 4363: Pharmacologic targeting of Gq reveals new pathways in uveal melanoma Cancer Research. 78: 4363-4363 |
Singh S, Sun X, Blumer KJ, et al. (2018) Direct Observation of GDP Unbinding Reveals Multiple Allosteric Pathways Underlie G-Protein Activation Biophysical Journal. 114: 398a |
Kanai SM, Edwards AJ, Rurik JG, et al. (2017) Proteolytic degradation of Regulator of G Protein Signaling 2 facilitates temporal regulation of Gq/11 signaling and vascular contraction. The Journal of Biological Chemistry |
Scherer SL, Cain MD, Kanai SM, et al. (2017) Regulation of neurite morphogenesis by interaction between R7 regulator of G protein signaling complexes and G protein subunit Gα13. The Journal of Biological Chemistry |
Onken MD, Makepeace CM, Wang S, et al. (2017) Abstract 1350: Direct pharmacological targeting of Gq/11 in uveal melanoma Cancer Research. 77: 1350-1350 |
Beeman SC, Osei-Owusu P, Duan C, et al. (2015) Renal DCE-MRI Model Selection Using Bayesian Probability Theory. Tomography (Ann Arbor, Mich.). 1: 61-68 |