Saxton M J
Institute of Theoretical Dynamics, University of California, Davis 95616.
Biophys J. 1994 Nov;67(5):2110-9. doi: 10.1016/S0006-3495(94)80694-0.
Single-particle tracking techniques make it possible to measure motion of individual particles on the cell surface. In these experiments, individual trajectories are observed, so the data analysis must take into account the randomness of individual random walks. Methods of data analysis are discussed for models combining diffusion and directed motion. In the uniform flow model, a tracer simultaneously diffuses and undergoes directed motion. In the conveyor belt model, a tracer binds and unbinds to a uniform conveyor belt moving with constant velocity. If a tracer is bound, it moves at the velocity of the conveyor belt; if it is unbound, it diffuses freely. Trajectories are analyzed using parameters that measure the extent and asymmetry of the trajectory. A method of assessing the usefulness of such parameters is presented, and pitfalls in data analysis are discussed. Joint probability distributions of pairs of extent and asymmetry parameters are obtained for a pure random walk. These distributions can be used to show that a trajectory is not likely to have resulted from a pure random walk.
单粒子追踪技术使得测量细胞表面单个粒子的运动成为可能。在这些实验中,会观察到单个粒子的轨迹,因此数据分析必须考虑到单个随机游走的随机性。本文讨论了结合扩散和定向运动的模型的数据分析方法。在均匀流模型中,示踪剂同时进行扩散和定向运动。在传送带模型中,示踪剂与以恒定速度移动的均匀传送带结合和解离。如果示踪剂被结合,它将以传送带的速度移动;如果未被结合,它将自由扩散。使用测量轨迹范围和不对称性的参数来分析轨迹。本文提出了一种评估此类参数有用性的方法,并讨论了数据分析中的陷阱。对于纯随机游走,获得了范围和不对称性参数对的联合概率分布。这些分布可用于表明轨迹不太可能是由纯随机游走产生的。