Creating Ion Channel Kinetic Models Using Cloud Computing. Issue 2 (17th February 2022)

• Record Type: Journal Article
• Authors: Mangold, Kathryn E.; Zhou, Zhuodong; Schoening, Max; Moreno, Jonathan D.; Silva, Jonathan R.
• Is Part Of: Current protocols. Volume 2:Issue 2(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-02-17
• Subjects: ion channels -- kinetic models -- optimization; Life sciences -- Laboratory manuals -- Periodicals; Biology -- Laboratory manuals -- Periodicals; Life sciences -- Technique -- Periodicals; Biology -- Technique -- Periodicals; 570.028
• DOI: 10.1002/cpz1.374
• Languages: English
• ISSNs: 2691-1299

Abstract

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