title: Stochastic simulation and graphic visualization of mitotic processes.
abstract: Computational modeling can be extremely useful in interpreting experimental results. Here we describe how a relatively sophisticated stochastic model for microtubule dynamic instability in the mitotic spindle can be developed starting with straightforward rules and simple programming code. Once this model is developed, the method for comparing simulation results to experimental data must be carefully considered. The ultimate utility of any computational model relies on its predictive power and the ability to assist in designing new experiments. We describe how "deconstructing" the model through the use of quantitative animations contributes to a better qualitative understanding of model behavior. By extracting key qualitative elements of the model in this fashion, model predictions and new experiments can be more easily extracted from model results.
authors.affiliation: Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN 55455, USA.
authors.forename: Melissa K
authors.initials: MK
authors.lastname: Gardner
authors.forename: David J
authors.initials: DJ
authors.lastname: Odde
mesh_terms: D003198:Computer Simulation; D008870:Microtubules / Q000502:physiology; D008938:Mitosis; D013269:Stochastic Processes