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有丝分裂过程的随机模拟和图形可视化。

Stochastic simulation and graphic visualization of mitotic processes.

机构信息

Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN 55455, USA.

出版信息

Methods. 2010 Jun;51(2):251-6. doi: 10.1016/j.ymeth.2010.01.021. Epub 2010 Jan 22.

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.

摘要

计算建模在解释实验结果方面非常有用。在这里,我们描述了如何从简单的规则和简单的编程代码开始,开发用于有丝分裂纺锤体中微管动态不稳定性的相对复杂的随机模型。一旦开发了此模型,就必须仔细考虑将模拟结果与实验数据进行比较的方法。任何计算模型的最终用途都依赖于其预测能力和协助设计新实验的能力。我们描述了如何通过使用定量动画“解构”模型来更好地定性理解模型行为。通过这种方式提取模型的关键定性要素,可以更轻松地从模型结果中提取模型预测和新实验。

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