细胞膜离子单通道电流重构的计算机仿真

细胞膜离子单通道电流十分微弱(PA级),用膜片钳技术测量离子电流往往淹没在强噪声背景中。目前,采用阈值检测方法恢复通道电流信号。但是,通道开放和关闭的电流阈值需要人为设定,并且阈值法在较低信噪比时失效。采用隐马尔可夫模型(HMM)重构离子单通道电流并估计模型参数。对离子通道HMM进行描述和分析;运用Baum-Welch迭代算法训练HMM并估计模型参数;利用Viterbi算法重构通道电流最佳状态序列。将HMM与阈值法进行比较,对不同信噪比和不同转移概率情况下HMM恢复算法进行计算机仿真。结果表明:HMM与阈值法相比,具有较强抗噪能力。在较低信噪比情况下,该模型恢复信号精度高,参数收敛速度快,且电流重构误差主要出现在状态突变点。

Computer simulation of current restoration for ionic single-channel

Single ion channel current signal of cell membrane is a stochastic ionic current in the order of picoampere（PA）.The background noise always dominates in the patch-clamp recordings.At present,the threshold detection method is used to restore channel current signal.However,the current threshold need be setted artificially,and this method cannot work satisfactorily when signal-to-noise ratio is lower.Hidden Markov Mode（lHMM）is adopted for restoring the ion-channel current and estimating parameters of the model.HMM on ion-channel is described and analyzed.Iterative algorithm based Baum-Welch is used for training HMM and estimating model parameters.Viterbi algorithm is adopted for restoring the best state sequence of ion-channel currents.Comparing HMM with the threshold detection method,the algorithm based HMM is simulated under the different transition probability and signal-to-noise ratio.The experimental results have shown that compared with the threshold detector,HMM has strong ability of anti-noise,high restoration precision,and fast convergent rate under the low signal-tonoise ratio.Moreover,the restored error appears mainly on the mutational points of the current signal.