Bayesian traction force estimation using cell boundary-dependent force priors

BIOPHYSICAL JOURNAL(2023)

引用 0|浏览6
暂无评分
摘要
Understanding the principles of cell migration necessitates measurements of the forces generated by cells. In traction force microscopy (TFM), fluorescent beads are placed on a substrate's surface and the substrate strain caused by the cell traction force is observed as displacement of the beads. Mathematical analysis can estimate traction force from bead displacement. However, most algorithms estimate substrate stresses independently of cell boundary, which results in poor estimation accuracy in low-density bead environments. To achieve accurate force estimation at low density, we proposed a Bayesian traction force estimation (BTFE) algorithm that incorporates cell-boundary-dependent force as a prior. We evaluated the performance of the proposed algorithm using synthetic data generated with mathematical models of cells and TFM substrates. BTFE outperformed other methods, especially in low-density bead conditions. In addition, the BTFE algorithm provided a reasonable force estimation using TFM images from the experiment.
更多
查看译文
关键词
bayesian traction force estimation,boundary-dependent
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要