Datasets that simulated ion channel currents
收藏资源简介：
This repository contains pseudo-ion-channel current datasets described in the 2023 publication “Model-Free Idealization: Adaptive Integrated Approach for Idealization of Ion Channel Currents (AI2)”. The datasets simulate ion channel currents based on the two-state model (Gating Kinetics.tif) and contain two kinds of noise (experimental or white Gaussian noise) at different signal-to-noise ratios (SNRs=10.2, 5.14, and 1.82). Four values (1, 10, 100, and 1000 s<sup>-1</sup> ) were examined for k<sub>1</sub> and k<sub>2</sub> of the gating kinetics, yielding 16 combinations of k<sub>1</sub> and k<sub>2</sub> . The repository contains five time-series data for each combination of k<sub>1</sub> , k<sub>2</sub> , and SNR. Each dataset contains 5×10<sup>5</sup> points which correspond to a 20 s recording with a sampling frequency of 25 kHz. <br> Time-series 0-1 (closed-open) sequences were first simulated using the QuB software. White Gaussian noise was added to the 0-1 sequence by Python 3.7. Experimental noise was added to the 0-1 sequence through electrophysiological recordings using a patch-clamp amplifier and a model cell (Molecular Devices). Voltage sequences consisting of V<sub>0</sub> and V<sub>1</sub> , which corresponded to the closed and open states, respectively, were input to the model cell (10 MΩ resister), and the resulting currents were recorded with the amplifier. Each CSV file has time, ground truth (0 or 1), and current.
