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A statistical inference approach to reconstruct intercellular interactions in cell migration experiments

机译:重建细胞迁移实验中的细胞间相互作用的统计推理方法

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Migration of cells can be characterized by two prototypical types of motion: individual and collective migration. We propose a statistical inference approach designed to detect the presence of cell-cell interactions that give rise to collective behaviors in cell motility experiments. This inference method has been first successfully tested on synthetic motional data and then applied to two experiments. In the first experiment, cells migrate in a wound-healing model: When applied to this experiment, the inference method predicts the existence of cell-cell interactions, correctly mirroring the strong intercellular contacts that are present in the experiment. In the second experiment, dendritic cells migrate in a chemokine gradient. Our inference analysis does not provide evidence for interactions, indicating that cells migrate by sensing independently the chemokine source. According to this prediction, we speculate that mature dendritic cells disregard intercellular signals that could otherwise delay their arrival to lymph vessels.
机译:可以通过两个原型类型的运动来表征细胞的迁移:个人和集体迁移。我们提出了一种统计推理方法,旨在检测细胞 - 细胞相互作用的存在,这引起细胞运动实验中的集体行为。本推断方法已经首先成功地测试了合成运动数据,然后应用于两个实验。在第一实验中,细胞在伤口愈合模型中迁移:当应用于该实验时,推导方法预测细胞 - 细胞相互作用的存在,正确镜像实验中存在的强细胞间触点。在第二种实验中,树突细胞在趋化因子梯度中迁移。我们的推断分析不提供相互作用的证据,表明细胞通过独立感测趋化因子来源来迁移。根据这种预测,我们推测成熟的树突细胞忽略了否则可能延迟到淋巴血管的细胞间信号。

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