Evidence map›Paper›PMID 25705700›Full record

ArticleBioMed research international2015

Application of stochastic automata networks for creation of continuous time Markov chain models of voltage gating of gap junction channels.

Mindaugas Snipas, Henrikas Pranevicius, Mindaugas Pranevicius, Osvaldas Pranevicius, Nerijus Paulauskas, Feliksas F Bukauskas

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Article in BioMed research international, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
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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

6 authors.

Mindaugas SnipasDepartment of Mathematical Modelling, Kaunas University of Technology, Studentų Street 50, 51368 Kaunas, Lithuania ; Laboratory of Systems Control and Automation, Lithuanian Energy Institute, Breslaujos Street 3, 44403 Kaunas, Lithuania.ORCID 0000-0003-2132-519X
Henrikas PraneviciusDepartment of Applied Informatics, Vytautas Magnus University, Vileikos Street 8-409, 44404 Kaunas, Lithuania ; Department of Business Informatics Research in Systems, Kaunas University of Technology, Studentų Street 56, 5142 Kaunas, Lithuania.
Mindaugas PraneviciusDepartment of Anesthesiology, Albert Einstein College of Medicine, 1300 Morris Park Avenue, Bronx, NY 10461, USA.
Osvaldas PraneviciusDepartment of Anesthesiology, New York Hospital Queens, 56-45 Main Street, Flushing, NY 11355, USA.
Nerijus PaulauskasDepartment of Business Informatics Research in Systems, Kaunas University of Technology, Studentų Street 56, 5142 Kaunas, Lithuania ; Institute of Cardiology, Lithuanian University of Health Sciences, Sukileliu Street 17, 50009 Kaunas, Lithuania.ORCID 0000-0001-9124-8551
Feliksas F BukauskasDepartment of Neuroscience, Albert Einstein College of Medicine, 1300 Morris Park Avenue, Bronx, NY 10461, USA.

Funding

Gating of Connexin-Based Gap Junction Channels and HemichannelsR01NS072238 · NINDS · ALBERT EINSTEIN COLLEGE OF MEDICINE · PI BUKAUSKAS, FELIKSAS · 2010 to 2013
$1.4M
NINDS NIH HHS R01 NS072238
6 · The paper itself

Abstract

The primary goal of this work was to study advantages of numerical methods used for the creation of continuous time Markov chain models (CTMC) of voltage gating of gap junction (GJ) channels composed of connexin protein. This task was accomplished by describing gating of GJs using the formalism of the stochastic automata networks (SANs), which allowed for very efficient building and storing of infinitesimal generator of the CTMC that allowed to produce matrices of the models containing a distinct block structure. All of that allowed us to develop efficient numerical methods for a steady-state solution of CTMC models. This allowed us to accelerate CPU time, which is necessary to solve CTMC models, ~20 times.

Indexed as

Markov ChainsNeural Networks, ComputerConnexinsGap JunctionsHumansIon ChannelsModels, TheoreticalConnexinsIon Channels

Identifiers

PMID25705700
PMCPMC4331413

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Registered trials

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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.