Evidence map›Paper›PMID 14990476›Full record

ArticleBiophysical journal2004

Restoration of single-channel currents using the segmental k-means method based on hidden Markov modeling.

Feng Qin

Abstract readComparative StudyEvaluation StudyValidation Study
In one paragraph

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 167 papers.

0numbers the graph read from it
0cells of the map it votes in
167citing 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

167 citing papers in PubMed.

  1. Article
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  3. Review
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  8. Temperature Sensitive Glutamate Gating of AMPA-subtype iGluRs.bioRxiv : the preprint server for biology · 2024
    Article
  9. Article
  10. Structural basis for CFTR inhibition by CFTRProceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  11. Estimating the CaMethods in molecular biology (Clifton, N.J.) · 2024
    Article
  12. Article
  13. Article
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  15. Article
  16. Article
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  19. Membrane Stretch Gates NMDA Receptors.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2022
    Article
  20. Article

107 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

1 author.

Feng QinDepartment of Physiology and Biophysical Sciences, State University of New York at Buffalo, Buffalo, New York 14214, USA. qin@acsu.buffalo.edu

Funding

ALGORITHMS FOR MOLECULAR KINETICSR01RR011114 · NCRR · STATE UNIVERSITY OF NEW YORK AT BUFFALO · PI QIN, FENG · 1996 to 2008
$3.5M
Mechanisms of Heat Activation and Multimodal Functions of VR1 Receptor ChannelsR01GM065994 · NIGMS · STATE UNIVERSITY OF NEW YORK AT BUFFALO · PI QIN, FENG · 2002 to 2010
$2.4M
NCRR NIH HHS R01 RR011114NCRR NIH HHS R01-RR11114NIGMS NIH HHS R01 GM065994NIGMS NIH HHS R01-GM65994
6 · The paper itself

Abstract

Patch-clamp recording provides an unprecedented means for study of detailed kinetics of ion channels at the single molecule level. Analysis of the recordings often begins with idealization of noisy recordings into continuous dwell-time sequences. Success of an analysis is contingent on accuracy of the idealization. I present here a statistical procedure based on hidden Markov modeling and k-means segmentation. The approach assumes a Markov scheme involving discrete conformational transitions for the kinetics of the channel and a white background noise for contamination of the observations. The idealization is sought to maximize a posteriori probability of the state sequence corresponding to the samples. The approach constitutes two fundamental steps. First, given a model, the Viterbi algorithm is applied to determine the most likely state sequence. With the resultant idealization, the model parameters are then empirically refined. The transition probabilities are calculated from the state sequences, and the current amplitudes and noise variances are determined from the ensemble means and variances of those samples belonging to the same conductance classes. The two steps are iterated until the likelihood is maximized. In practice, the algorithm converges rapidly, taking only a few iterations. Because the noise is taken into explicit account, it allows for a low signal/noise ratio, and consequently a relatively high bandwidth. The approach is applicable to data containing subconductance levels or multiple channels and permits state-dependent noises. Examples are given to elucidate its performance and practical applicability.

Indexed as

Models, BiologicalModels, StatisticalAnimalsCell MembraneComputer SimulationIon Channel GatingIon ChannelsKineticsMarkov ChainsMembrane PotentialsMicePatch-Clamp TechniquesPotassium Channels, Calcium-ActivatedStochastic ProcessesIon ChannelsPotassium Channels, Calcium-Activated

Identifiers

PMID14990476
PMCPMC1303984

What OpenQuestion holds

Textmetadata
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.