Evidence map›Paper›PMID 15681642›Full record

ArticleBiophysical journal2005

Maximum likelihood estimation of ion channel kinetics from macroscopic currents.

Lorin S Milescu, Gustav Akk, Frederick Sachs

Abstract read
In one paragraph

Article in Biophysical journal, 2005. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 76 papers.

0numbers the graph read from it
0cells of the map it votes in
76citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

76 citing papers in PubMed.

  1. Article
  2. Article
  3. 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 · 2025
    Article
  4. Article
  5. Yoda1's energetic footprint on Piezo1 channels and its modulation by voltage and temperature.Proceedings of the National Academy of Sciences of the United States of America · 2022
    Article
  6. Article
  7. Article
  8. Calibration of ionic and cellular cardiac electrophysiology models.Wiley interdisciplinary reviews. Systems biology and medicine · 2020
    Review
  9. Article
  10. Article
  11. Four Ways to Fit an Ion Channel Model.Biophysical journal · 2019
    Article
  12. Phenomenological models of NaScientific reports · 2019
    Article
  13. Reproducible model development in the cardiac electrophysiology Web Lab.Progress in biophysics and molecular biology · 2018
    Article
  14. OpenWorm: overview and recent advances in integrative biological simulation ofPhilosophical transactions of the Royal Society of London. Series B, Biological sciences · 2018
    Review
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article

16 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Lorin S MilescuDepartment of Physiology and Biophysics, State University of New York, Buffalo, New York, USA.
Gustav Akk
Frederick Sachs

Funding

ALGORITHMS FOR MOLECULAR KINETICSR01RR011114 · NCRR · STATE UNIVERSITY OF NEW YORK AT BUFFALO · PI QIN, FENG · 1996 to 2008
$3.5M
NCRR NIH HHS R01 RR011114NCRR NIH HHS RR11114
6 · The paper itself

Abstract

We describe a maximum likelihood method for direct estimation of rate constants from macroscopic ion channel data for kinetic models of arbitrary size and topology. The number of channels in the preparation, and the mean and standard deviation of the unitary current can be estimated, and a priori constraints can be imposed on rate constants. The method allows for arbitrary stimulation protocols, including stimuli with finite rise time, trains of ligand or voltage steps, and global fitting across different experimental conditions. The initial state occupancies can be optimized from the fit kinetics. Utilizing arbitrary stimulation protocols and using the mean and the variance of the current reduce or eliminate problems of model identifiability (Kienker, 1989). The algorithm is faster than a recent method that uses the full autocovariance matrix (Celentano and Hawkes, 2004), in part due to the analytical calculation of the likelihood gradients. We tested the method with simulated data and with real macroscopic currents from acetylcholine receptors, elicited in response to brief pulses of carbachol. Given appropriate stimulation protocols, our method chose a reasonable model size and topology.

Indexed as

AlgorithmsAnimalsBiophysicsCalcium PhosphatesCarbacholComputer SimulationElectrophysiologyHumansIonsKineticsLigandsLikelihood FunctionsMarkov ChainsMiceModels, BiologicalModels, Chemicalcalcium phosphateCalcium PhosphatesCarbacholIonsLigandsReceptors, Cholinergic

Identifiers

PMID15681642
PMCPMC1305347

What OpenQuestion holds

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Read underepoch 390

Registered trials

None linked

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.