Ball F G, Sansom M S
Department of Mathematics, University of Nottingham, U.K.
Proc R Soc Lond B Biol Sci. 1989 May 22;236(1285):385-416. doi: 10.1098/rspb.1989.0029.
Patch-clamp data may be analysed in terms of Markov process models of channel gating mechanisms. We present a maximum likelihood algorithm for estimation of gating parameters from records where only a single channel is present. Computer simulated data for three different models of agonist receptor gated channels are used to demonstrate the performance of the procedure. Full details of the implementation of the algorithm are given for an example gating mechanism. The effects of omission of brief openings and closings from the single-channel data on parameter estimation are explored. A strategy for discriminating between alternative possible gating models, based upon use of the Schwarz criterion, is described. Omission of brief events is shown not to lead to incorrect model identification, except in extreme circumstances. Finally, the algorithm is extended to include channel gating models exhibiting multiple conductance levels.
膜片钳数据可以根据通道门控机制的马尔可夫过程模型进行分析。我们提出了一种最大似然算法，用于从仅存在单个通道的记录中估计门控参数。使用三种不同的激动剂受体门控通道模型的计算机模拟数据来证明该程序的性能。针对一个示例门控机制给出了算法实现的完整细节。探讨了单通道数据中遗漏短暂开放和关闭对参数估计的影响。描述了一种基于施瓦茨准则区分替代可能门控模型的策略。结果表明，除了在极端情况下，遗漏短暂事件不会导致错误的模型识别。最后，该算法被扩展到包括具有多个电导水平的通道门控模型。
