Department of Mathematics
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Masters degree: Mathematical Biology Track

Overview

Throughout most of its history, biology has been viewed as being primarily a descriptive rather than a predictive science. Biological processes and systems seemed far too complex to model, simulate or predict mathematically with anything approaching the accuracy and rigor achieved in the physical sciences and engineering. But that is rapidly changing do to dramatic advances in computational capabilities, fundamental understanding of biological processes and many areas of mathematics relevant to modeling biological systems. Mathematical biology is one of the fastest growing areas of applied mathematics and incorporates ideas and techniques from across the entire mathematical spectrum including all areas of core mathematics along much of computer science and statistics. The modern mathematical biologist must have broad training in the mathematical sciences and be acquainted with pertinent areas of the biological sciences.

The Mathematical Biology Track to the M.S. in Mathematics provides a foundation in mathematics, statistics and computational science central to most areas of mathematical biology, and then focuses on mathematical and biological topics most relevant to the student's chosen area of emphasis. The possible biological application areas one might choose form a vast array of the modern life science arena: genetics and bioinformatics, circadian clocks, complex ecosystems, evolutionary ecology, the spread of infectious diseases, mathematical physiology, mathematical medicine (e.g. modeling cardiovascular disease or cancer or wound healing or tissue engineering), computational neuroscience, medical imaging, in silico modeling of metabolic pathways, to name but a few.

Under this perspective, the Mathematical Biology is a multi-purpose track. On the one hand, it is intended to give sufficient training for beginning a career in some aspect of mathematical biology, but also it can be used as a springboard to the Ph.D. with an emphasis on applications to the life sciences.


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