Methods and applications of mathematical models in biology, focusing on understanding, analyzing, and applying scientific literature using models and integrating real data. Topics may include parameter estimation in biological models, stochastic simulation of disease outbreaks, age structured population models, and others. Course may be repeated for credit under a different topic. Prerequisite: MATH 360 and (MATH 348 or STAT 380), both with a minimum grade of C-. Corequisite: MATH 348 or STAT 380 may be taken as a corequisite. Strongly Recommended: Experience with a computing platform such as R, MATLAB, or Python.
Methods and applications of mathematical models in biology, focusing on understanding, analyzing, and applying scientific literature using models and integrating real data. Topics may include parameter estimation in biological models, stochastic simulation of disease outbreaks, age structured population models, and others. Course may be repeated for credit under a different topic. Prerequisite: MATH 360 and (MATH 348 or STAT 380), both with a minimum grade of C-. Corequisite: MATH 348 or STAT 380 may be taken as a corequisite. Strongly Recommended: Experience with a computing platform such as R, MATLAB, or Python.
