Literature DB >> 35175690

Creating Ion Channel Kinetic Models Using Cloud Computing.

Kathryn E Mangold1, Zhuodong Zhou1, Max Schoening1, Jonathan D Moreno1,2, Jonathan R Silva1.   

Abstract

Computational modeling of ion channels provides key insight into experimental electrophysiology results and can be used to connect channel dynamics to emergent phenomena observed at the tissue and organ levels. However, creation of these models requires substantial mathematical and computational background. This tutorial seeks to lower the barrier to creating these models by providing an automated pipeline for creating Markov models of an ion channel kinetics dataset. We start by detailing how to encode sample voltage-clamp protocols and experimental data into the program and its implementation in a cloud computing environment. We guide the reader on how to build a containerized instance, push the machine image, and finally run the routine on cluster nodes. While providing open-source code has become more standard in computational studies, this tutorial provides unprecedented detail on the use of the program and the creation of channel models, starting from inputting the raw experimental data.
© 2022 Wiley Periodicals LLC. Basic Protocol: Creation of ion channel kinetic models with a cloud computing environment Alternate Protocol: Instructions for use in a standard high-performance compute cluster. © 2022 Wiley Periodicals LLC.

Entities:  

Keywords:  ion channels; kinetic models; optimization

Mesh:

Substances:

Year:  2022        PMID: 35175690      PMCID: PMC9006544          DOI: 10.1002/cpz1.374

Source DB:  PubMed          Journal:  Curr Protoc        ISSN: 2691-1299


  10 in total

1.  A quantitative description of membrane current and its application to conduction and excitation in nerve.

Authors:  A L HODGKIN; A F HUXLEY
Journal:  J Physiol       Date:  1952-08       Impact factor: 5.182

2.  Differential Expression and Remodeling of Transient Outward Potassium Currents in Human Left Ventricles.

Authors:  Eric K Johnson; Steven J Springer; Wei Wang; Edward J Dranoff; Yan Zhang; Evelyn M Kanter; Kathryn A Yamada; Jeanne M Nerbonne
Journal:  Circ Arrhythm Electrophysiol       Date:  2018-01

Review 3.  Computational biology in the study of cardiac ion channels and cell electrophysiology.

Authors:  Yoram Rudy; Jonathan R Silva
Journal:  Q Rev Biophys       Date:  2006-07-19       Impact factor: 5.318

4.  Markov models for ion channels: versatility versus identifiability and speed.

Authors:  Martin Fink; Denis Noble
Journal:  Philos Trans A Math Phys Eng Sci       Date:  2009-06-13       Impact factor: 4.226

5.  A state-mutating genetic algorithm to design ion-channel models.

Authors:  Vilas Menon; Nelson Spruston; William L Kath
Journal:  Proc Natl Acad Sci U S A       Date:  2009-09-16       Impact factor: 11.205

6.  Nonlinear and Stochastic Dynamics in the Heart.

Authors:  Zhilin Qu; Gang Hu; Alan Garfinkel; James N Weiss
Journal:  Phys Rep       Date:  2014-10-10       Impact factor: 25.600

Review 7.  Calibration of ionic and cellular cardiac electrophysiology models.

Authors:  Dominic G Whittaker; Michael Clerx; Chon Lok Lei; David J Christini; Gary R Mirams
Journal:  Wiley Interdiscip Rev Syst Biol Med       Date:  2020-02-21

8.  A computationally efficient algorithm for fitting ion channel parameters.

Authors:  Zachary R Teed; Jonathan R Silva
Journal:  MethodsX       Date:  2016-11-16

9.  Four Ways to Fit an Ion Channel Model.

Authors:  Michael Clerx; Kylie A Beattie; David J Gavaghan; Gary R Mirams
Journal:  Biophys J       Date:  2019-08-06       Impact factor: 4.033

  10 in total

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