Quantitative Biology at Clemson University Bob Kosinski (Biological Sciences) Jim Peterson (Mathematical Sciences) Abstract Clemson’s Departments of Biological Sciences and Mathematical Sciences have begun a multi-year collaboration to strengthen quantitative biology. The Present Situation. Since 2004, Peterson has taught a biology-oriented section of the second calculus course in a required two-semester sequence. Kosinski teaches the introductory biology sequence for biology majors, and has incorporated introductions to modeling, statistics, and bioinformatics. Several upper-division biology courses continue a modeling emphasis. However, many students transfer in without having taken the freshman courses, and there is a 1-2 year “math-free zone” between these courses and the freshman ones. Future Plans. Kosinski plans to expand his use of modeling, and Peterson plans to create biology-oriented sections of the first calculus course in the sequence and introduce a new course on modeling using partial differential equations. Biological Sciences is debating whether it should require more mathematics for all its majors, or create a Quantitative Biology emphasis area (12-18 credits) with more intense mathematics exposure for a smaller number of students. The latter option would avoid strong math resistance by both students and some faculty. BS in Biological Sciences, 2007 Introductory Biology I and II Calculus I (general) and Calculus II (for biologists) Biochemistry Genetics Animal or Plant Diversity (several choices) Evolutionary Biology Cell Biology Ecology (several choices) Physiology (several choices) Other upper-level biology courses No statistics required No bioinformatics required Introductory Biology Bob Kosinski Course population (~250/yr) is mostly premed students. Their favorite labs are dissections. Modeling--laboratories on- Stella simulation of biochemical reactions. Stella simulation of weight regulation Other quantitative topics (e.g., Hardy- Weinberg equilibrium, water potential) Elementary statistics (chi-square median test) Bioinformatics Phylogram of mtDNA control region in several African groups. Results Students can do the mathematical exercises, but they are not popular. Students don’t see modeling and bioinformatics as biology. Statistics is seen as useful, but understanding of statistical principles is rare. Immediate Future Plans Expansion of modeling and statistics using Excel spreadsheets. Excel is well-accepted by the students. Calculus of One Variable II Jim Peterson Calculus I is traditional, but Calculus II emphasizes the use of simple ordinary differential equations in modeling in the life sciences. Students (30 in Fall and 60 in Spring) are mainly majors in Biological Sciences and Microbiology. First order ordinary differential equations exponential growth and decay, cooling logistic growth integration by parts simple partial fraction expansion introduction to Matlab Linear second order differential equations the characteristic and its roots solutions of the associated differential eqs simple discretization numerical solutions using Matlab Coupled first order systems matrices and vectors eigenvalues and eigenvectors phase plane analysis Coupled nonlinear first order systems predator-prey models epidemiological models working with linearized systems solution and phase-plane analysis of nonlinear systems numerical solutions using Matlab Phase-space dynamics of the Lotka-Volterra predator-prey system. Results Student enjoy the course, but they need lots of attention. This makes the course very time-consuming to teach. It is also difficult to recruit faculty help or graders from Math. Sciences. Immediate Future Plans Enhancement of self-published text, creation of a modeling-based Calculus I course, and perhaps a 200- level course on modeling with PDEs. Upper-Division Courses Evolutionary Biology Margaret Ptacek This is a required course for all Biological Sciences majors. The course uses PAUP for phylogenetic analysis, and models fluctuations in allelic frequences with Populus. Populus simulation of genetic drift in replicate populations. Ecology Dave Tonkyn Students model population growth with discrete generations, competition, predator-prey dynamics, human demographics (using data derived from cemeteries), and island biogeography. Ecology also uses RAMAS software to investigate population dynamics. The endangered Leadbeater’s possum and its age-specific survival rates. Systems Physiology Jim Colacino Makes extensive use of Stella simulations to model gases in the alveoli and drug concentrations in different fluid compartments in the body. Simulation of the blood (blue) and brain (red) concentration of a drug with a priming dose and one missed dose (at 25 days).