These courses are taught by faculty in Biology, Mathematics, and Statistics, and are truly interdisciplinary (one is cross-listed between Biology and Mathematics). The fairly minimal mathematics prerequisites of the three fusion courses (two semesters of calculus, a two-credit course in linear algebra, and ideally a differential equations course) means that many students, particularly those with AP credit, can begin taking these courses in their sophomore year. The point during their studies when students take these courses and the order in which they take them is expected to be flexible.

Theory of Population and Evolutionary Ecology - M/BZ 348

Instructor: Colleen Webb, Asst. Prof., Dept. of Biology and Dept. of Mathematics.

Text: “Population Biology: Concepts and Models”, by Alan Hastings.

Course description: Theory of population and evolutionary ecology, reading theoretical literature, simple modeling, and advancement to more complex theory. Students complete problem sets and computer labs in Matlab by programming models and simulations. Topics: well-mixed vs. structured populations (e.g., discrete and continuous time, density dependence, Leslie matrices); multiple interacting populations (e.g., competition, predator-prey limit cycles, non-linear dynamics); models of micro-evolutionary processes (e.g., selection, mutation, gradient equations); game theory; evolutionary conflicts and dynamic programming; and adaptive dynamics (e.g. fast-slow dynamical systems, complex bifurcations).

Mathematics in Biology and Medicine - MATH 455

Instructor: Jennifer Mueller, Assoc. Prof., Dept. of Mathematics

Text: “Numerical Analysis: Mathematical Models in Biology”, by Leah Edelstein-Keshet

Course description: Models in population biology (predator-prey, host-parasitoid, plant-herbivore, infectious disease systems), bacterial growth in a chemostat, cell division, and biomedicine (blood flow, CO2 exchange, glucose-insulin kinetics, medical imaging). Mathematical topics include linear and nonlinear difference equations, the logistic equation, continuous processes and ordinary differential equations, stability considerations for both discrete and continuous models, and diffusion models.

Introduction to Bioinformatics Algorithms - ST480

Instructors: Hari Iyer, Prof., Dept. of Statistics, Asa Ben-Hur, Asst. Prof., Dept of Computer Sciences.

Text: “Computational Genome Analysis: An Introduction”, by M.S. Waterman, S. Tavar´e and R.C. Deonier.

Course Description: Biological Overview: Cells, Biological Words & Probability, Word Distributions and Occurrences: Restriction Endonucleases, Sequence Alignment: Basic Rapid Alignment Methods: FASTA and BLAST, Signals in DNA, Measuring Expression of Genome Information, Introduction to R, Internet Bioinformatics Resources.

The intellectual scope of FEScUE can be expanded by adding new cross-listed fusion courses. As an immediate example, a course taught in Biochemistry and Molecular Biology could be expanded for cross-listing as a fusion course by modifying content to include an appropriate level of mathematical rigor to serve a broader audience. “Theory of Population and Evolutionary Ecology” became cross-listed following just such a discussion. The biochemistry course currently exists as follows.

Quantitative Biochemistry - BC571

Instructor: Olve Peersen, Asst. Prof., Dept. of Biochemistry and Molecular Biology.

Text: “An Introduction to Error Analysis”, by John Taylor.

Course description: Statistical and computational methods applied to analysis and curve fitting of data from biochemical and biophysical experiments. Theoretical and practical aspects focus on the physical biochemistry behind common biochemical experiments, with a focus on experimental design. Tutorials using Microsoft Excel to import and process experimental data, Kaleidagraph for weighted curve fitting using customized equations, an emphasis on proper determination and propagation of experimental error.
(V) GRE preparation courses
For the past two years, the Department of Mathematics has run a 2-credit course to prepare majors for their subject GREs. Expansion to other departments is an initiative in the College of Natural Sciences.