Yeast, Tar Heel

Our research uses mathematical modeling to understand the design principles that underlie complex biological systems.

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.


Signal Transduction
Airway Volume Regulation
Noise in Gene Expression
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Spatial Modeling
Software Development
Glycogen Regulation
Diffusion & Viscoelastic Media
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