Computational Physiology Lab

The fundamental processes regulating biological functions are complex, varying greatly from person to person and rapidly changing during disease. Over the past few decades, computational modeling has been recognized as a valuable counterpart to experimental physiology, and as a powerful tool to understand the mechanisms governing physiological responses during disease.  Computational modeling is increasingly becoming a platform for predictive medicine – that is, using models to predict new and better therapies for human disease.

Computational modeling is a highly multidisciplinary field, combining tools from engineering, biology, mathematics, physics, chemistry, and computational science.

Our lab is interested in developing cutting-edge computational tools to understand fundamental principles of disease and develop new therapies.  Our research spans a wide range of physiological areas and topics, including electrophysiology, cellular signaling pathways, and mechanobiology.   We use multiscale and stochastic models to study these complex physiological phenomena.

Research interests:

  • Cardiac electrophysiology and arrhythmias

  • Mechanotransduction

  • Calcium release and signaling

  • Nonlinear dynamics in biology

  • Stochastic processes

  • Computational neuroscience

Current projects:

  • Ion channel localization in cardiac conduction and disease

  • Elastic-stochastic modeling of fibronectin assembly

  • Stochastic calcium release in cardiac cells

  • Fractional-order modeling of excitable cells

  • Discrete-time map modeling of excitation-contraction coupling