Green Center for Systems Biology, Department of Pharmacology, Simmons Cancer Center, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA.
Curr Opin Cell Biol. 2013 Oct;25(5):538-42. doi: 10.1016/j.ceb.2013.04.004. Epub 2013 May 6.
The complex nature of cell migration highlights the power and challenges of applying mathematics to biological studies. Mathematics may be used to create model equations that recapitulate migration, which can predict phenomena not easily uncovered by experiments or intuition alone. Alternatively, mathematics may be applied to interpreting complex data sets with better resolution--potentially empowering scientists to discern subtle patterns amid the noise and heterogeneity typical of migrating cells. Iteration between these two methods is necessary in order to reveal connections within the cell migration signaling network, as well as to understand the behavior that arises from those connections. Here, we review recent quantitative analysis and mathematical modeling approaches to the cell migration problem.
细胞迁移的复杂性凸显了将数学应用于生物学研究的力量和挑战。可以使用数学方法创建再现迁移的模型方程，这些方程可以预测仅凭实验或直觉不易发现的现象。或者，数学可以应用于以更高的分辨率解释复杂的数据集——有可能使科学家能够在迁移细胞中典型的噪声和异质性中辨别微妙的模式。为了揭示细胞迁移信号网络中的连接，以及了解这些连接产生的行为，这两种方法之间的迭代是必要的。在这里，我们回顾了最近用于细胞迁移问题的定量分析和数学建模方法。
