We present a method to differentiate organisms solely by their motion based on the generalized Langevin equation (GLE) and use it to distinguish two different swimming modes of strongly confined unicellular microalgae . The GLE is a general model for active or passive motion of organisms and particles that can be derived from a time-dependent general many-body Hamiltonian and in particular includes non-Markovian effects (i.e., the trajectory memory of its past). We extract all GLE parameters from individual cell trajectories and perform an unbiased cluster analysis to group them into different classes. For the specific cell population employed in the experiments, the GLE-based assignment into the two different swimming modes works perfectly, as checked by control experiments. The classification and sorting of single cells and organisms is important in different areas; our method, which is based on motion trajectories, offers wide-ranging applications in biology and medicine.

中文翻译：

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通过数据驱动的单个细胞的非马尔可夫运动分类


我们提出了一种基于广义朗之万方程（GLE）的仅通过运动来区分生物体的方法，并用它来区分强限制性单细胞微藻的两种不同的游泳模式。 GLE 是有机体和粒子主动或被动运动的通用模型，可以从时间相关的一般多体哈密顿量导出，特别包括非马尔可夫效应（即其过去的轨迹记忆）。我们从单个细胞轨迹中提取所有 GLE 参数，并执行无偏聚类分析，将它们分为不同的类别。对于实验中使用的特定细胞群，根据对照实验的结果，基于 GLE 的两种不同游泳模式的分配效果非常好。单细胞和生物体的分类和分选在不同领域都很重要；我们的方法基于运动轨迹，在生物学和医学领域具有广泛的应用。