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.
Candidates should have an undergraduate degree in a biological, quantitative, or physical science/engineering. A minimum GPA of 3.0 (on a 4.0 scale) is required.
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
| Code | Title | Credits |
|---|---|---|
| Required | 1 | |
| Methods in Quantitative Biology | ||
| Quantitative Courses (Choose One) | 3-4 | |
| Intermediate Problems in Chemical Engineering | ||
| Introduction to Optimization | ||
| Machine Learning | ||
| Applied Linear Algebra | ||
| Numerical Linear Algebra | ||
| Numerical Analysis | ||
| Ordinary Differential Equations | ||
| Probability Theory | ||
| Stochastic Methods for 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 Systems Biology | ||
| Computational Network Biology | ||
| Advanced Bioinformatics | ||
| Statistical Methods for Molecular Biology | ||
| Computational Modeling of Biological Systems | ||
| Phylogenetic Analysis of Molecular Data | ||
| Advanced Genomic and Proteomic Analysis | ||
| Bioinformatics for Microbiologists | ||
| Bioinformatics for Biologists | ||
| 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 | ||
| Chemical Biology | ||
| Principles of Genetics | ||
| Biology and Genetics of Fungi | ||
| Advanced Genetics | ||
| Advanced Microbial Genetics | ||
| Microbiology at Atomic Resolution | ||
| Carcinogenesis and Tumor Cell Biology | ||
| Cellular and Molecular Biology/Pathology | ||
| Cell Biology | ||
QBI PhD minor committee:
A. Gitter (BMI)
M. McClean (BME)
S. Roy (BMI)
O. Venturelli (Biochem)
For a complete list of relevant QBio faculty, please see All Faculty.