MBI Emphasis Year on Mathematical Bioengineering
September 2007 - August 2008
Philip J. Holmes (Department of Mechanical and Aerospace Engineering, Princeton University);
Melissa Knothe Tate(Lerner Research Institute, Department of Biomedical Engineering, The Cleveland Clinic);
Art Kuo (Department of Mechanical Engineering, Department of Biomedical Engineering, Institute of Gerontology, University of Michigan);
Michael Savageau (Department of Biomedical Engineering, University of California, Davis);
Allen Tannenbaum (School of Electrical and Computer Engineering, Georgia Institute of Technology);
Dawn Taylor (Department of Biomedical Engineering, Case Western Reserve University)
Bioengineering lies at the interfaces of biology, the applied sciences and engineering. It combines the excitement of multi-disciplinary research with the promise of making improvements to society, especially in health care, e.g. in the diagnosis and treatments of degenerative diseases. However, it is a relatively new field that is still finding its way among the established engineering and biological disciplines. As a multi-discipline it presents particular problems for the seasoned researcher as much as for the new student: indeed, we are all new students when it comes to subfields in which we have not trained.
The 2007-2008 MBI Year in Mathematical Bioengineering will focus around six workshops on Metabolic Engineering, Cell and Tissue Engineering, Neuroengineering, Brain Imaging, and Neuromechanics, the latter being covered in two linked workshops. Tutorials will be offered to prepare participants, especially students and postdoctoral fellows interested in entering the field. While omitting large areas, these workshops provide examples of the central subject matter, and they highlight two key modes of operation of bioengineering: as a conduit for experimental methods, modeling and analytical tools from the physical sciences and mathematics into biology, and as a conduit for biological inspiration to the applied sciences and engineering, as in bio-inspired design of new devices and materials.
A common feature of the topics chosen, and indeed, of much of bioengineering, is their integrative nature. Biological systems are unavoidable complex, often containing many apparently redundant parts or pathways. In trying to understand, predict, control, change, or build such a complex system one must successfully reduce and combine a mass of detail. In this endeavor mathematical modeling and analysis offers a unifying language and set of principles that can draw together disparate ideas from genomics, molecular biology, neuroscience, biochemistry, physiology, imaging and signal processing (to name only topics germane to the six MBI workshops). Mathematics can also reveal common principles operating on different time and space scales, and guide the development of computational algorithms for simulation and data analysis.