title: Statistical discrimination of fractal and Markov models of single-channel gating.
abstract: A statistical comparison is presented of Markov and fractal models of ion channel gating. The analysis is based on single-channel data from two types of ion channels: open times from a 90 pS Ca-activated K channel from GH3 pituitary cells, and closed times from a nonselective channel from rabbit corneal endothelium (Liebovitch et al., 1987a). Maximum likelihood methods were used to fit the data. For both data sets the best Markov model had three exponential components. The best Markov model had a higher likelihood than the fractal model, and the Asymptotic Information Criterion favored the Markov model for each data set. A more detailed analysis, using the Monte Carlo methods described in Horn (1987), showed that the Markov model was not significantly better than the fractal model for the corneal endothelium channels. The inability to discriminate the models definitively in this case was shown to be due in part to the small size of the data set.
authors: Neurosciences Department, Roche Institute of Molecular Biology, Nutley, New Jersey 07110.
authors: S J
authors: SJ
authors: Korn
authors: R
authors: R
authors: Horn
mesh_terms: D000818:Animals; D002118:Calcium / Q000494:pharmacology; D002460:Cell Line; D003315:Cornea / Q000502:physiology; D004727:Endothelium / Q000502:physiology; D007473:Ion Channels / Q000502:physiology*; D008433:Mathematics; D008954:Models, Biological; D010911:Pituitary Neoplasms; D015221:Potassium Channels / Q000187:drug effects / Q000502:physiology*
chemical_list: D007473:Ion Channels; D015221:Potassium Channels; D002118:Calcium