Lattice Models and Agent-Based Models in Biology: Linking Individual Properties to Population Properties
Wednesday, June 16 at 09:30am (PDT)Wednesday, June 16 at 05:30pm (BST)Thursday, June 17 01:30am (KST)
Bhargav Karamched (Florida State University, United States of America)
Lattice models have a rich history in biological modeling. They provide a valuable framework for modeling complex spatiotemporal dynamics in biological tissues. Agent-based models provide realistic models of biological tissues and populations. Both have been used to model protein folding, cancer initiation and progression, and motor protein transport through a cell, amongst numerous other applications. Both frameworks have the important property of linking individual properties to population-level structure. Spatiotemporal dynamics in biological systems are often modeled by partial differential equations. Partial differential equation models offer scope for analysis, but they often coarse grain dynamics so that an individual's impact on the population is unclear. Lattice models are a viable alternative to the aforementioned. They capture individual properties at a high level but nevertheless sacrifice some fidelity to reality for the sake of analytical tractability. While agent-based models are less tractable, they are able to make concrete predictions about how systems behave in the lab--their results are easier to interpret for the non-theorist. This mini symposium will feature talks discussing lattice and agent-based models about specific biological systems, showing the relevance of such models today. How results therein can be interpreted and mapped to reality will also be discussed.