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The Elston lab is interested in understanding the dynamics of complex biological systems, and developing reliable mathematical models that capture the essential components of these systems. The projects in the lab encompass a wide variety of biological phenomena including signal transduction, cell fate decisions and gradient sensing in yeast, noise in gene networks and signaling pathways, airway homeostasis, and energy transduction in motor proteins. We also are interested in developing computational tools for performing stochastic and spatiotemporal simulations of signaling networks and image analysis.

Graduate students in the lab participate in the Bioinformatics and Computational Biology Graduate Program, the Applied Mathematics Program, and the Molecular and Cellular Biophysics Program.

Postdoctoral position available read more here

Congratulations to Connor Sandefur and Vinal Lakhani for their recent papers!

Sandefur CI, Boucher RC, Elston TC.  Mathematical model reveals role of nucleotide signaling in airway surface liquid homeostasis and its dysregulation in cystic fibrosis. Proc Natl Acad Sci U S A. 2017 Aug 29;114(35):E7272-E7281. doi: 10.1073/pnas.1617383114. Epub 2017 Aug 14

Lakhani V, Elston TC. Testing the limits of gradient sensing. PLoS Comput Biol. 2017 Feb 16;13(2):e1005386. doi: 10.1371/journal.pcbi.1005386. eCollection 2017 Feb.