2021/06/17 by Alexander S. Moffett, Moffett, Alexander S., Guiying Cui +11
Biochemistry, Genetics and Molecular Biology · Neuroscience · #Advanced Fluorescence Microscopy Techniques #FOS: Biological sciences #FOS: Electrical engineering #Photoreceptor and optogenetics research #Protein Structure and Dynamics #Quantitative Methods (q-bio.QM) #Signal Processing (eess.SP) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2106.09594
openalex publication_date 2021/06/17 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
We derive a factor graph EM (FGEM) algorithm, a technique that permits combined parameter estimation and statistical inference, to determine hidden kinetic microstates from patch clamp measurements. Using the cystic fibrosis transmembrane conductance regulator (CFTR) and nicotinic acetylcholine receptor (nAChR) as examples, we perform \em Monte Carlo simulations to demonstrate the performance of the algorithm. We show that the performance, measured in terms of the probability of estimation error, approaches the theoretical performance limit of maximum \em a posteriori estimation. Moreover, the algorithm provides a reliability score for its estimates, and we demonstrate that the score can be used to further improve the performance of estimation. We use the algorithm to estimate hidden kinetic states in lab-obtained CFTR single channel patch clamp traces.