Arthur Sherman, Ph.D., Chief
Carson Chow, Ph.D.
Kevin D. Hall, Ph.D.
Vipul Periwal, Ph.D.
Our laboratory is defined by both its methodologies and its areas of application. We are primarily a group of theorists, trained in mathematics and physics, applying mathematical modeling to a variety of biological problems. The models are developed in concert with experiments, carried out by either ourselves or experimental collaborators, and validated by generating and testing predictions A common theme across these efforts is the study of systems as they change over time, using differential equations and stochastic simulations. The equations we study are more complicated than, but similar in spirit to, Newton’s laws of motion and similarly enable us to unify a wide range of phenomena and relate them to fundamental physical principles such as the laws of conservation of mass, charge, and energy. We also pay close attention to model fitting and statistics, both to aid in model selection and to analyze experimental data in order to find correlations that can suggest mechanistic models. Another approach relies on computational models of molecular structure for drug discovery.
The diseases and conditions we study are systemic in nature. We do not expect the related causes and solutions to revolve around single genes or environmental stressors, but rather to arise from the interaction of multiple genes, cell types, and organs. It is easy for investigators to find dysfunction in particular sub-systems and attribute the disease process to that element. On the other hand, putting these specific perturbations into context requires methods that can integrate data coming from multiple sources, including cells in vitro, animals, and human subjects. Mathematics is essential for success in such a program of research. In many cases, casting hypotheses in the form of mathematical models enforces quantitative consistency that can be overlooked when making verbal hypotheses: that is, making the numbers add up can expose problems in data collection and inconsistencies in proposed explanations.
Our research covers a wide range of phenomena in cell biology, genetics, and physiology with a primary common focus on diabetes, obesity, and metabolism. Specific projects include:
- Mechanisms and regulation of insulin secretion, including cell electrical activity, calcium homeostasis, metabolic oscillations, and vesicle exocytosis.
- How mitochondria produce ATP and by-products, such as reactive oxygen species, which both play positive signaling roles and cause cell stress and damage.
- Development and regeneration of tissues — including liver, pancreatic islets of Langerhans, and adipose depots — in response to injury and metabolic demand.
- How body composition and energy utilization vary with diet.
- The role of the brain in coordinating energy intake and energy expenditure.
- Methods for long-term measurement of energy intake and expenditure in humans and animals.
- Contributions of large numbers of genes to obesity, insulin resistance, and autism.
- Regulation of gene transcription.
Why it Matters
The incidence of type 2 diabetes is rising at an alarming rate. This increase appears to result from a mismatch between human metabolism, which evolved in ancient conditions of food scarcity, and a modern world of abundant and easily obtainable food. The recent rapid increase is obviously environmental in origin, but the responses of individuals to the environment are in large part genetic. The modern setting fosters the development of obesity, and obesity is the main trigger for the development of diabetes. Obesity itself also plays a major role in other degenerative diseases of aging, such as cardiovascular disease and dementia, and the loss of adequate blood glucose control greatly amplifies those disease processes as well. As the rest of the world transitions from subsistence to abundance over the next decades, these problems will intensify dramatically. Yet many individuals are resistant to obesity, and most obese individuals do not become diabetic, so we need to understand what accounts for these differences.
We invite you to visit the pages for our lab’s principal investigators, which may be reached by clicking on the names of the individuals included in the staff listing above, to see how each of us contributes to the mission of the lab.
LBM in the News
Welcome to Planet Math: NIDDK Laboratory of Biological Modeling turns 50. NIH Record. November 30, 2007.
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Why even resolute dieters often fail. The New York Times. September 19, 2011.