ArticleBiophysical journal2004
Model-based fitting of single-channel dwell-time distributions.
Article in Biophysical journal, 2004. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers.
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Who cites it
46 citing papers in PubMed.
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- Markov models and long-term memory in ion channels: A contradiction in terms?Biophysical journal · 2025Article
- Using Bayesian priors to overcome non-identifiablility issues in Hidden Markov models.bioRxiv : the preprint server for biology · 2025Article
- A deep learning approach to real-time Markov modeling of ion channel gating.Communications chemistry · 2024Article
- The fractal brain: scale-invariance in structure and dynamics.Cerebral cortex (New York, N.Y. : 1991) · 2023Review
- 2D-dwell-time analysis with simulations of ion-channel gating using high-performance computing.Biophysical journal · 2023Article
- Probing Transient Riboswitch Structures via Single Molecule Accessibility Analysis.Methods in molecular biology (Clifton, N.J.) · 2023Article
- Effects of ethanol on GluN1/GluN2A and GluN1/GluN2B NMDA receptor-ion channel gating kinetics.Alcoholism, clinical and experimental research · 2022Article
- An anionic ligand snap-locks a long-range interaction in a magnesium-folded riboswitch.Nature communications · 2022Article
- Allosteric cross-talk between the hydrophobic cleft and the BH4 domain of Bcl-2 in control of inositol 1,4,5-trisphosphate receptor activity.Exploration of targeted anti-tumor therapy · 2022Article
- Dynamic competition between a ligand and transcription factor NusA governs riboswitch-mediated transcription regulation.Proceedings of the National Academy of Sciences of the United States of America · 2021Article
- Local-to-global signal transduction at the core of a MnNature communications · 2019Article
- A HIDDEN MARKOV MODEL APPROACH TO CHARACTERIZING THE PHOTO-SWITCHING BEHAVIOR OF FLUOROPHORES.The annals of applied statistics · 2019Article
- High bandwidth approaches in nanopore and ion channel recordings - A tutorial review.Analytica chimica acta · 2019Review
- Probing RNA structure and interaction dynamics at the single molecule level.Methods (San Diego, Calif.) · 2019Review
- Noncompetitive antagonists induce cooperative AMPA receptor channel gating.The Journal of general physiology · 2019Article
- Single-channel recordings of RyR1 at microsecond resolution in CMOS-suspended membranes.Proceedings of the National Academy of Sciences of the United States of America · 2018Article
- Estimating kinetic mechanisms with prior knowledge I: Linear parameter constraints.The Journal of general physiology · 2018Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
Single-channel recordings provide unprecedented resolutions on kinetics of conformational changes of ion channels. Several approaches exist for analysis of the data, including the dwell-time histogram fittings and the full maximal-likelihood approaches that fit either the idealized dwell-time sequence or more ambitiously the noisy data directly using hidden Markov modeling. Although the full maximum likelihood approaches are statistically advantageous, they can be time-consuming especially for large datasets and/or complex models. We present here an alternative approach for model-based fitting of one-dimensional and two-dimensional dwell-time histograms. To improve performance, we derived analytical expressions for the derivatives of one-dimensional and two-dimensional dwell-time distribution functions and employed the gradient-based variable metric method for fast search of optimal rate constants in a model. The algorithm also has the ability to allow for a first-order correction for the effects of missed events, global fitting across different experimental conditions, and imposition of typical constraints on rate constants including microscopic reversibility. Numerical examples are presented to illustrate the performance of the algorithm, and comparisons with the full maximum likelihood fitting are discussed.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.