Computational Modeling of Biological Systems
Using modeling, simulation, high-performance computing and data analysis to create testable hypotheses about mechanisms driving complex biological functions
Researchers within the Duke BME community focus on the study and advancement of computational methods and data analysis techniques to understand biological phenomena.
This quantitative research uses modeling and simulation, high-performance computing, and large-scale data analysis to create testable hypotheses about mechanisms driving complex biological function.
At Duke, this research spans many application areas including electrophysiology, patient-specific hemodynamics, cellular mechanisms, gene circuits, and synthetic biology. Researchers in this area are broadly interactive with departments throughout the university, including clinical departments of the Duke University School of Medicine, the “big data” Information Initiative at Duke (iiD), the Duke Cancer Institute, and the academic departments of Computer Science and Mechanical Engineering and Materials Science.
Associated Faculty
Warren M Grill, Ph.D.
James B. Duke Distinguished Professor of Biomedical Engineering
David Katz, Ph.D.
Nello L. Teer, Jr. Distinguished Professor of Biomedical Engineering, in the Edmund T. Pratt, Jr. School of Engineering
Dr Mike Lynch, M.D., Ph.D.
Director of Master’s Studies, W. H. Gardner, Jr. Associate Professor of Biomedical Engineering
Wanda Krassowska Neu
Professor Emeritus of Biomedical Engineering
George Truskey, Ph.D.
Associate Chair for Education, R. Eugene and Susie E. Goodson Distinguished Professor of Biomedical Engineering
Other Research Specialties
Explore additional specialty research areas in Duke BME and throughout the Pratt School of Engineering.