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利用隐马尔可夫模型分析多通道膜片钳记录数据

Analysis of multichannel patch clamp recordings by hidden Markov models.

作者信息

Klein S, Timmer J, Honerkamp J

机构信息

Fakultät für Physik, Albert-Ludwigs-Universität, Freiburg, Germany.

出版信息

Biometrics. 1997 Sep;53(3):870-84.

PMID:9333349
Abstract

Conventional methods of analysis do not allow the kinetics of patch clamped ion channels to be completely determined if more than one channel is present in the patch. This hinders investigations on small ion channels as well as on channel cooperativity and the homogeneity of channel populations. We present a method to extract the rate constants and current amplitudes for each individual channel from multichannel patches by a one-step procedure. For this purpose, the current record is modeled by the superposed Markov processes of the opening and closing of each channel that is contaminated by noise (Hidden Markov Model). Channel parameters are obtained by maximum likelihood methods. Because the parameters can be calculated directly from the unfiltered record, the dwell time and missed event problems are widely diminished. Confidence bounds for the estimated parameters are given. Statistical tests to decide whether channels switch identically and/or independently are introduced. The application of the method is demonstrated with simulated data.

摘要

如果膜片中有多个离子通道,传统的分析方法无法完全确定膜片钳离子通道的动力学。这阻碍了对小离子通道以及通道协同性和通道群体同质性的研究。我们提出了一种通过一步程序从多通道膜片中提取每个单独通道的速率常数和电流幅度的方法。为此,电流记录由每个通道的开放和关闭的叠加马尔可夫过程建模,该过程被噪声污染(隐马尔可夫模型)。通过最大似然方法获得通道参数。由于可以直接从未滤波的记录中计算参数,驻留时间和漏检事件问题大大减少。给出了估计参数的置信区间。引入了用于确定通道是否相同和/或独立切换的统计检验。用模拟数据演示了该方法的应用。

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