Evidence map›Paper›PMID 38856900›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2024

Creating Computational Models of Ion Channel Dynamics.

Max E Schoening, Jonathan R Silva

Abstract read
PubMed Publisher
In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

2 authors.

Max E SchoeningDepartment of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO, USA.
Jonathan R SilvaDepartment of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO, USA. jonsilva@wustl.edu.

Funding

Personalizing Class I anti-Arrhythmic Drug TherapyR01HL148803 · NHLBI · WASHINGTON UNIVERSITY · PI SILVA, JONATHAN R · 2020 to 2024
$3.2M
NHLBI NIH HHS R01 HL148803
6 · The paper itself

Abstract

Markov models are widely used to represent ion channel protein configurations as different states in the model's topology. Such models allow for dynamic simulation of ion channel kinetics through the simulated application of voltage potentials across a cell membrane. In this chapter, we present a general method for creating Markov models of ion channel kinetics using computational optimization alongside a fully featured example model of a cardiac potassium channel. Our methods cover designing training protocols, iteratively testing potential model topologies for structure identification, creation of algorithms for model simulation, as well as methods for assessing the quality of fit for a finalized model.

Indexed as

AlgorithmsIon ChannelsMarkov ChainsComputational BiologyComputer SimulationHumansIon Channel GatingKineticsMolecular Dynamics SimulationSoftwareIon ChannelsAction potentialsComputational optimizationIon channelsMarkov modelsModel creationModelingSimulation

Identifiers

PMID38856900

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.