Bayraktar, F, Benson, AP orcid.org/0000-0003-4679-9842, Holden, AV et al. (1 more author) (2019) Transcriptomic Approaches to Modelling Long Term Changes in Human Cardiac Electrophysiology. In: Coudière, Y, Ozenne, V, Vigmond, E and Zemzemi, N, (eds.) Lecture Notes in Computer Science. FIMH 2019: Functional Imaging and Modeling of the Heart, 06-08 Jun 2019, Bordeaux, France. Springer Verlag , pp. 3-10. ISBN 9783030219482
Abstract
Slow changes in the activity of the heart occur with time scales from days through to decades, and may in part result from changes in cardiomyocyte properties. The cellular mechanisms of the cardiomyocyte action potential have time scales from < ms to hundreds of ms. Although the quantitative dynamic relations between mRNA transcription, protein synthesis, trafficking, recycling, and membrane protein activity are unclear, mRNA-Seq can be used to inform parameters in cell excitation equations. We use such transcriptomic data from a non-human primate to scale maximal conductances in the O’Hara-Rudy (2011) family of human ventricular cell models, and to predict diurnal changes in human ventricular action potential durations. These are related to circadian changes in the incidence of sudden cardiac deaths. Transcriptomic analysis of human fetal hearts between 9 and 16 weeks gestational age is beginning to be used to inform ventricular cell and tissue models of the electrophysiology of the developing fetal heart.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © Springer Nature Switzerland AG 2019. This is a post-peer-review, pre-copyedit version of an conference paper published in Functional Imaging and Modeling of the Heart . The final authenticated version is available online at: https://doi.org/10.1007/978-3-030-21949-9_1 |
Keywords: | Transcriptomics; Circadian; Fetal |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Biological Sciences (Leeds) > School of Biomedical Sciences (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 31 Jul 2019 11:54 |
Last Modified: | 31 Jul 2019 11:54 |
Status: | Published |
Publisher: | Springer Verlag |
Identification Number: | 10.1007/978-3-030-21949-9_1 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:149184 |