Estimating rate constants from single ion channel currents when the initial distribution is known.
Single ion channel currents can be analysed by hidden or aggregated Markov models. A classical result from Fredkin et al. (Proceedings of the Berkeley conference in honor of Jerzy Neyman and Jack Kiefer, vol I, pp 269-289, 1985) states that the maximum number of identifiable parameters is bounded by 2n(o)n(c), where n(o) and n(c) denote the number of open and closed states, respectively. We show that this bound can be overcome when the probabilities of the initial distribution are known and the data consist of several sweeps.
The
Yu-Kai
YK
Institut für Physik, Albert-Ludwigs-Universität, Hermann-Herder-Strasse 3, 79104 Freiburg, Germany. yuki@fdm.uni-freiburg.de
Fernandez
Jacqueline
J
Popa
M Oana
MO
Lerche
Holger
H
Timmer
Jens
J
D001703:Biophysics / Q000379:methods*; D003198:Computer Simulation; D006801:Humans; D015640:Ion Channel Gating; D007473:Ion Channels / Q000737:chemistry*; D017136:Ion Transport; D007477:Ions; D007668:Kidney / Q000166:cytology; D007700:Kinetics; D016013:Likelihood Functions; D008390:Markov Chains; D008956:Models, Chemical; D015233:Models, Statistical; D009124:Muscle Proteins / Q000737:chemistry; D018482:Muscle, Skeletal / Q000166:cytology; D062553:NAV1.4 Voltage-Gated Sodium Channel; D015222:Sodium Channels / Q000737:chemistry; D013997:Time Factors; D014162:Transfection
D007473:Ion Channels; D007477:Ions; D009124:Muscle Proteins; D062553:NAV1.4 Voltage-Gated Sodium Channel; C106251:SCN4A protein, human; D015222:Sodium Channels