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We derive a factor graph EM (FGEM) algorithm, a technique that permitscombined parameter estimation and statistical inference, to determine hiddenkinetic microstates from patch clamp measurements. Using the cystic fibrosistransmembrane conductance regulator (CFTR) and nicotinic acetylcholine receptor(nAChR) as examples, we perform {\em Monte Carlo} simulations to demonstratethe performance of the algorithm. We show that the performance, measured interms of the probability of estimation error, approaches the theoreticalperformance limit of maximum {\em a posteriori} estimation. Moreover, thealgorithm provides a reliability score for its estimates, and we demonstratethat the score can be used to further improve the performance of estimation. Weuse the algorithm to estimate hidden kinetic states in lab-obtained CFTR singlechannel patch clamp traces.

A factor graph EM algorithm for inference of kinetic microstates from patch clamp measurements