“Introduction to Modeling in Biology” is designed for biologists who would like to understand what contribution theory and modeling can make to science, who want to be able to read and understand papers that use modeling in their field of research, and who would like to become a little more comfortable with modeling approaches in biology. The class is not intended to teach students to themselves use specific modeling techniques. The class also focuses on the meaning of 'evidence' and how the scientific method produces it.

This class is an active-learning class, which means that students will be actively engaging with the material, sometimes working in pairs or groups (syllabus from a prior year). We will read several modeling papers, some seminal and some current. Instructors Anna Dornhaus and Joanna Masel will lead discussions to demystify each paper, and to help students understand exactly what it achieves and how. The modeling approaches discussed in the class will include differential equation models, network models, individual-based models, Markov processes, and others. Our focus is on students achieving enough familiarity with these approaches to be able to understand and evaluate them when presented in scientific papers or seminars. Students will also be using math to solve problems and programming some simple models, both using *Mathematica*. How to use *Mathematica *will be explained in class, and this program, for example, can solve differential equations without the students being required to have this skill themselves.

The course is designed for graduate students and advanced undergrads with a basic mathematics background and without prior modeling experience. Students with some prior modeling experience who wish to broaden their toolkit are also welcome. It should be noted that we consider the class useful even for students with a strong mathematical background, since such students may also not have had training in how to put mathematics, as a technique, to use in science and in how to integrate their insights in an empirical field of science. This is a 3-credit class. No textbook is required, but students will be required to have access to Mathematica (e.g. through a one-semester subscription; we recommend asking your advisor if a subscription may be available in your lab).

The class is typically held Mondays, Wednesdays, Fridays 1-2pm in BSW 212.

Readings and other material are available on the D2L course website, which is accessible to enrolled students from the beginning of the semester.

Please email me if you have any questions about the class: dornhaus@email.arizona.edu