Research
The Computational Biology Laboratory is a studio for mathematical aspects of life science. The lab applies mathematics, computation, and data science to biological questions in computational neuroscience, cell physiology, calcium signaling, quantitative pharmacology, pattern formation, and genomics.
We are life scientists and neuroscientists, and also interdisciplinary applied mathematicians. Our work uses differential equations, probability, high-performance computing, and practical data science methods to connect mechanistic models with biological function. Students in the lab work at the intersection of applied mathematics, biology, data science, and bioengineering.
Graduate students in the Computational Biology Lab are members of William & Mary’s Department of Applied Science in the School of Computing, Data Sciences & Physics.
Undergraduate researchers affiliated with the lab often major in Mathematics, Neuroscience, or CAMS Mathematical Biology. If you are an undergraduate interested in the lab, take a look at the CBL repository.
The lab is closely connected with William & Mary’s biomathematics and data science communities.
Current Projects
Receptor Oligomers: Mathematical and biophysical theory for multi-subunit receptors, with emphasis on symmetry, thermodynamic constraints, allostery, and quantitative pharmacology.
Eupnea & Sigh: Joint modeling and experimental work on the neural mechanisms that generate and couple normal breathing and sigh rhythms in the preBötzinger complex.
Membraneless organelles and phase separation: Phase-field and statistical-mechanical models of liquid-liquid phase separation in cellular organization, including post-synaptic density proteins.
Petal Patterns: Reaction-diffusion and spatial-statistical models of floral pigment patterns in hybrid monkeyflowers, developed in collaboration with experimental plant biologists.
Past Projects
Calcium Dynamics: Diffusion, buffering, stochastic release, sparks, puffs, waves, and local/global models of intracellular Ca2+ signaling.
Visual Thalamus: Conductance-based, firing-rate, and population-density models of thalamocortical relay and visual processing.