Stochastic simulation and graphic visualization of mitotic processes

Research output: Contribution to journalArticle

5 Citations (Scopus)

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.

Original languageEnglish (US)
Pages (from-to)251-256
Number of pages6
JournalMethods
Volume51
Issue number2
DOIs
StatePublished - Jun 1 2010

Fingerprint

Spindle Apparatus
Microtubules
Visualization
Stochastic models
Animation
Experiments

Keywords

  • Imaging
  • Microtubule
  • Mitosis
  • Simulation
  • Stochastic
  • Yeast

Cite this

Stochastic simulation and graphic visualization of mitotic processes. / Gardner, Melissa K; Odde, David J.

In: Methods, Vol. 51, No. 2, 01.06.2010, p. 251-256.

Research output: Contribution to journalArticle

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