Signal Restoration and Parameters’ Estimation of Ionic Single-Channel Based on HMM-SR Algorithm
Single ion-channel signal of cell membrane is a stochastic ionic current in the order of picoampere (pA). Because of the weakness of the signal, the background noise always dominates in the patch-clamp recordings. The threshold detector is traditionally used to denoise and restore the ionic single channel currents. However, this method cannot work satisfactorily when signal-to-noise ratio is lower. A new approach based on hidden Markov model (HMM) is presented to restore ionic single-channel currents and estimate model parameters under white background noise. In the study, a global optimization method of HMM parameters based on stochastic relaxation (SR) algorithm is used to estimate the kinetic parameters of channel. Then, the ideal channel currents are reconstructed applying Viterbi algorithm from the patch-clamp recordings contaminated by noise. The theory and experiments have shown that the method performs effectively under the low signal-to-noise ratio (SNR<5.0) and has fast parameter convergence, high restoration precision and strong noise robusticity.
KeywordsHide Markov Model Current Amplitude Channel Current Viterbi Algorithm State Transition Probability
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