ArticleBiophysical journal2007
Estimation of ion channel kinetics from fluctuations of macroscopic currents.
Article in Biophysical journal, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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15 citing papers in PubMed.
- Bayesian inference of functional asymmetry in the homotrimeric ligand-gated ion channel P2XCommunications biology · 2025Article
- Using Bayesian priors to overcome non-identifiablility issues in Hidden Markov models.bioRxiv : the preprint server for biology · 2025Article
- Parameter inference for stochastic reaction models of ion channel gating from whole-cell voltage-clamp data.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2025Article
- Fast functional mapping of ligand-gated ion channels.Communications biology · 2023Article
- Permissive and nonpermissive channel closings in CFTR revealed by a factor graph inference algorithm.Biophysical reports · 2022Article
- Article
- Estimating kinetic mechanisms with prior knowledge I: Linear parameter constraints.The Journal of general physiology · 2018Article
- Identifiability, reducibility, and adaptability in allosteric macromolecules.The Journal of general physiology · 2017Article
- The Dynamic Behavior of the P2XBiophysical journal · 2016Article
- Maximum likelihood estimation of biophysical parameters of synaptic receptors from macroscopic currents.Frontiers in cellular neuroscience · 2014Article
- Article
- Efficient maximum likelihood estimation of kinetic rate constants from macroscopic currents.PloS one · 2011Article
- Kinetic analysis of evoked IPSCs discloses mechanism of antagonism of synaptic GABAA receptors by picrotoxin.British journal of pharmacology · 2010Article
- A modeling study of T-type Ca2+ channel gating and modulation by L-cysteine in rat nociceptors.Biophysical journal · 2010Article
- Real-time kinetic modeling of voltage-gated ion channels using dynamic clamp.Biophysical journal · 2008Article
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1 author.
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Abstract
For single channel recordings, the maximum likelihood estimation (MLE) of kinetic rates and conductance is well established. A direct extrapolation of this method to macroscopic currents is computationally prohibitive: it scales as a power of the number of channels. An approximated MLE that ignored the local time correlation of the data has been shown to provide estimates of the kinetic parameters. In this article, an improved approximated MLE that takes into account the local time correlation is proposed. This method estimates the channel kinetics using both the time course and the random fluctuations of the macroscopic current generated by a homogeneous population of ion channels under white noise. It allows arbitrary kinetic models and stimulation protocols. The application of the proposed algorithm to simulated data from a simple three-state model on nonstationary conditions showed reliable estimates of all the kinetic constants, the conductance and the number of channels, and reliable values for the standard error of those estimates. Compared to the previous approximated MLE, it reduces by a factor of 10 the amount of data needed to secure a given accuracy and it can even determine the kinetic rates in macroscopic stationary conditions.
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