Computational Bioengineering

Director: Suzanne Shontz, Ph.D.

Computational Bioengineering generally describes the science of computational approaches to biological and medical problems ranging from molecular modeling to healthcare informatics including computational biomechanics and computational bioimaging.  Molecular modeling can include biological sequence analysis, the structure and function of proteins and nucleic acids, genetic networks and gene expression, molecular evolution, and hypothesis generation from large-scale data sources.  Computational molecular models can be used to inform rational drug design.  Healthcare informatics can be used to examine clinical data to better understand disease progression and treatment.  Computational methods can also be brought to bear in the understanding of biophysical phenomena such as fluid flow in blood vessels, in the mechanics of cartilage compression, and in the processing of medical images.

Central methodologies brought to bear on these problems are derived from probability and statistics, linear algebra, differential equations, optimization, graph theory, algorithms and their analysis, image processing, signal processing, data mining, databases, and linguistics.  The computational bioengineering core at KU provides the student with formal course work in methodologies and applications with an emphasis on research.  Students in this track are prepared for careers in industry, academia, and public service.  They are trained in computer science, mathematical and statistical methods and principles, biological and life sciences, and physical and chemistry principles.  While the program is firmly grounded on the techniques of computing, the nature of the research in inherently multidisciplinary. 

An accessible version of the content below will be made available upon request. Please contact bioe@ku.edu to request the content be made available in an accessible format.