ENGR-E443/543 Computational Modeling Methods for Virtual Tissues

While data-based approaches to biology are well-established and successful in many situations, mechanism-based modeling of biological phenomena (also known as virtual-tissue modeling) is a new and growing field, which can address problems which are outside the reach of data-based methods. We will consider the dynamics networks which provide molecular control of cell behaviors and how the effects of those intracellular responses differ in a spatial context (whether in a tissue or a bacterial community). We will introduce the modeling the biology of cell behaviors and interactions computationally and examine the hypotheses that such models can address. The course will also cover basic concepts of transport and diffusion of chemical species. The course will consider both the formulation of meaningful quantitative models and their translation into executable simulations. Simulations will use Python scripting in the CC3D modeling environment, with subcellular models specified using the Antimony/Tellurium extensions to Python. Graduate and advanced undergraduate students from all areas of Computer Science and Informatics, as well as science students in Mathematics, Biology, Chemistry and Physics are welcome. By the end of the course, students will develop a simple model of a spatially organized system of interest to them and should understand how to design, build and apply virtual-tissue methods.

The course will include homework and a project, but no exams.

The course is scheduled to meet Tuesday 4:55PM-7:55PM Luddy 4063. Lectures will also be available online via Zoom and recorded.

Prerequisites–an interest in biological phenomena at the cell, tissue and organ levels. Students should bring their own laptops for in-class programming exercises. No specific programming, mathematical or biological expertise is required.

If you have any difficulty registering for the course or would like more information, please e-mail at jaglazier@gmail.com or call me at (812) 391-2159.