Computational Medicine Section
The Computational Medicine Section integrates data from molecular to physiological scales using Bayesian model selection and ideas from information theory and theoretical physics to investigate integrative metabolism, building up from mitochondrial ATP and free radical production, adipocyte development, and liver regeneration to whole-body predictions.
Endocrine and Neural Dynamics Section
Arthur Sherman, Ph.D.
The Endocrine and Neural Dynamics Section applies mathematical modeling to the biophysical basis of insulin secretion in pancreatic beta cells. The long-term goals are to understand how the membrane dynamics interact with intracellular events to regulate secretion and to generalize to other secretory cells and neurons.
The Integrative Physiology Section investigates how metabolism and body composition adapt in response to a variety of interventions. Experiments are performed in both humans and rodents to better understand the complex mechanisms regulating macronutrient metabolism, body composition, and energy expenditure. Mathematical models are developed to quantitatively describe, explain, integrate, and predict the experimental results.
Mathematical Biology Section
The Mathematical Biology Section seeks to understand how processes at the genetic, molecular, and cellular levels determine behavior at the organ, tissue, and whole-body levels. Areas of application include obesity, neural networks, and autism.