Technological innovations have revolutionized the scale and detail with which biological systems can be explored. With that revolution has come a demand for scientists who can develop and analyze quantitative and predictive models of biological systems. The doctoral minor in Quantitative Biology is designed to complement the depth of training in biological or quantitative sciences that a student achieves through UW–Madison’s graduate programs with the breadth that is needed to conduct research under this paradigm. In addition to coursework in biological, quantitative, and integrated courses, students in the program will take an inter-disciplinary research seminar to prepare them for research that crosses these boundaries. This training will prepare students for careers in academic and industrial settings, where the ability to cross disciplinary lines and work in teams with diverse expertise is critical.

 Students who are candidates for the Ph.D. degree in any department or program may obtain an interdisciplinary minor in Quantitative Biology by earning: 

  • A minimum of 10 credits from the courses listed below, divided into four categories:
    • A required, 1-credit research seminar (students are advised to take during first year of graduate program)
    • One course from a quantitative science
    • One course from a biological science
    • One integrated course
Special Topics in Biomedical Engineering (Methods in Quantitative Biology)
Quantitative Courses (Choose One)3-4
Intermediate Problems in Chemical Engineering
Machine Learning
Applied Linear Algebra
Numerical Linear Algebra
Numerical Analysis
Ordinary Differential Equations
Probability Theory
Stochastic Methods for Biology
Mathematical Methods for Continuum Modeling in Biology
Analysis of Partial Differential Equations
Methods of Computational Mathematics I
Introduction to the Theory of Probability
Introduction to Biostatistics
Statistical Methods for Bioscience I
Statistical Methods for Bioscience II
Mathematical Statistics I
Introduction to Statistical Inference
Introduction to Stochastic Processes
Mathematical Statistics
Mathematical Statistics
Integrated Courses (Choose One)3
Systems Biology: Mammalian Signaling Networks
Modeling Biological Systems
Design of Biological Molecules
Introduction to Bioinformatics
Mathematical Methods for Structural Biology
Mathematical Methods for Systems Biology
Advanced Bioinformatics
Statistical Methods for Molecular Biology
Advanced Genomic and Proteomic Analysis
Biological Courses (Choose One) 2-3
Introduction to Biochemistry
Protein and Enzyme Structure and Function
Prokaryotic Molecular Biology
Eukaryotic Molecular Biology
Plant Biochemistry
Mechanisms of Action of Vitamins and Minerals
Cellular Signal Transduction Mechanisms
Methods in Biochemistry
Chemical Biology
Regulation of Gene Expression in Prokaryotes
Principles of Genetics
Advanced Microbial Genetics
Biology and Genetics of Fungi
Advanced Genetics
Advanced Microbial Physiology
Microbiology at Atomic Resolution
Cell Biology
Total Credits9-11

Faculty: J. Williams (chair), R. Ashton, D. Beebe, W. Block, C. Brace, P. Campagnola, N. Chesler, S. Gong, J. Huisken, P. Keely, P. Kreeger, W. Li, M. McClean, K. Masters, M. Meyerand, W. Murphy, J. Rogers, K. Saha, M. Skala, D. Thelen, W. Tompkins, R. Vanderby, J. Webster; Instructional Staff and Faculty Associates: A. Nimunkar, J. Puccinelli, T. Puccinelli, A. Suminski, J. Towles, and M. Tyler. See also the BME Directory.