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For: Whittaker DG, Clerx M, Lei CL, Christini DJ, Mirams GR. Calibration of ionic and cellular cardiac electrophysiology models. Wiley Interdiscip Rev Syst Biol Med 2020;12:e1482. [PMID: 32084308 DOI: 10.1002/wsbm.1482] [Cited by in Crossref: 29] [Cited by in F6Publishing: 33] [Article Influence: 14.5] [Reference Citation Analysis]
Number Citing Articles
1 Şengül Ayan S, Süleymanoğlu S, Özdoğan H. A pilot study of ion current estimation by ANN from action potential waveforms. J Biol Phys 2022. [DOI: 10.1007/s10867-022-09619-7] [Reference Citation Analysis]
2 Kohjitani H, Koda S, Himeno Y, Makiyama T, Yamamoto Y, Yoshinaga D, Wuriyanghai Y, Kashiwa A, Toyoda F, Zhang Y, Amano A, Noma A, Kimura T. Gradient-based parameter optimization method to determine membrane ionic current composition in human induced pluripotent stem cell-derived cardiomyocytes. Sci Rep 2022;12:19110. [DOI: 10.1038/s41598-022-23398-0] [Reference Citation Analysis]
3 Coveney S, Roney CH, Corrado C, Wilkinson RD, Oakley JE, Niederer SA, Clayton RH. Calibrating cardiac electrophysiology models using latent Gaussian processes on atrial manifolds. Sci Rep 2022;12:16572. [PMID: 36195766 DOI: 10.1038/s41598-022-20745-z] [Reference Citation Analysis]
4 Whittaker DG, Wang J, Shuttleworth JG, Venkateshappa R, Kemp JM, Claydon TW, Mirams GR. Ion channel model reduction using manifold boundaries. J R Soc Interface 2022;19:20220193. [PMID: 35946166 DOI: 10.1098/rsif.2022.0193] [Reference Citation Analysis]
5 Kohjitani H, Koda S, Himeno Y, Makiyama T, Yamamoto Y, Yoshinaga D, Wuriyanghai Y, Kashiwa A, Toyoda F, Zhang Y, Amano A, Noma A, Kimura T. Gradient-based parameter optimization to determine membrane ionic current composition of human induced pluripotent stem cell-derived cardiomyocytes.. [DOI: 10.1101/2022.05.16.492203] [Reference Citation Analysis]
6 Sutanto H, Heijman J. Integrative Computational Modeling of Cardiomyocyte Calcium Handling and Cardiac Arrhythmias: Current Status and Future Challenges. Cells 2022;11:1090. [DOI: 10.3390/cells11071090] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 3.0] [Reference Citation Analysis]
7 Whittaker DG, Wang J, Shuttleworth JG, Venkateshappa R, Kemp JM, Claydon TW, Mirams GR. Ion channel model reduction using manifold boundaries.. [DOI: 10.1101/2022.03.11.483794] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
8 Mangold KE, Zhou Z, Schoening M, Moreno JD, Silva JR. Creating Ion Channel Kinetic Models Using Cloud Computing. Curr Protoc 2022;2:e374. [PMID: 35175690 DOI: 10.1002/cpz1.374] [Reference Citation Analysis]
9 Taghadosi H, Tabatabai Ghomsheh F, Jafarnia Dabanloo N, Farajidavar A. The Role of Potassium Channel Gates in the Electrophysiology of the Human Gastric Smooth Muscle Cell. Gene Cell Tissue 2022;9. [DOI: 10.5812/gct.119450] [Reference Citation Analysis]
10 Sher A, Niederer SA, Mirams GR, Kirpichnikova A, Allen R, Pathmanathan P, Gavaghan DJ, van der Graaf PH, Noble D. A Quantitative Systems Pharmacology Perspective on the Importance of Parameter Identifiability. Bull Math Biol 2022;84:39. [PMID: 35132487 DOI: 10.1007/s11538-021-00982-5] [Cited by in Crossref: 6] [Cited by in F6Publishing: 6] [Article Influence: 6.0] [Reference Citation Analysis]
11 Yuan L, Wu C, Guo X, Yang C. ParaCopasi: A package for parallel biochemical simulation and analysis. J Comput Chem 2022;43:144-54. [PMID: 34747038 DOI: 10.1002/jcc.26775] [Reference Citation Analysis]
12 Lachaud Q, Aziz MHN, Burton FL, Macquaide N, Myles RC, Simitev RD, Smith GL. Electrophysiological heterogeneity in large populations of rabbit ventricular cardiomyocytes. Cardiovasc Res 2022:cvab375. [PMID: 35020837 DOI: 10.1093/cvr/cvab375] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
13 Villaverde AF, Pathirana D, Fröhlich F, Hasenauer J, Banga JR. A protocol for dynamic model calibration. Brief Bioinform 2021:bbab387. [PMID: 34619769 DOI: 10.1093/bib/bbab387] [Cited by in Crossref: 13] [Cited by in F6Publishing: 16] [Article Influence: 13.0] [Reference Citation Analysis]
14 Agrawal A, Wang K, Polonchuk L, Cooper J, Hendrix M, Gavaghan DJ, Mirams GR, Clerx M. Models of the cardiac L-type calcium current: a quantitative review.. [DOI: 10.1101/2021.10.04.462988] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
15 Berman JP, Kaboudian A, Uzelac I, Iravanian S, Iles T, Iaizzo PA, Lim H, Smolka S, Glimm J, Cherry EM, Fenton FH. Interactive 3D Human Heart Simulations on Segmented Human MRI Hearts. 2021 Computing in Cardiology (CinC) 2021. [DOI: 10.23919/cinc53138.2021.9662948] [Reference Citation Analysis]
16 Lei CL, Mirams GR. Neural Network Differential Equations For Ion Channel Modelling. Front Physiol 2021;12:708944. [PMID: 34421652 DOI: 10.3389/fphys.2021.708944] [Reference Citation Analysis]
17 Kemp JM, Whittaker DG, Venkateshappa R, Pang Z, Johal R, Sergeev V, Tibbits GF, Mirams GR, Claydon TW. Electrophysiological characterization of the hERG R56Q LQTS variant and targeted rescue by the activator RPR260243. J Gen Physiol 2021;153:e202112923. [PMID: 34398210 DOI: 10.1085/jgp.202112923] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 3.0] [Reference Citation Analysis]
18 Mangold KE, Wang W, Johnson EK, Bhagavan D, Moreno JD, Nerbonne JM, Silva JR. Identification of structures for ion channel kinetic models. PLoS Comput Biol 2021;17:e1008932. [PMID: 34398881 DOI: 10.1371/journal.pcbi.1008932] [Cited by in Crossref: 6] [Cited by in F6Publishing: 7] [Article Influence: 6.0] [Reference Citation Analysis]
19 Jæger KH, Edwards AG, Giles WR, Tveito A. A computational method for identifying an optimal combination of existing drugs to repair the action potentials of SQT1 ventricular myocytes. PLoS Comput Biol 2021;17:e1009233. [PMID: 34383746 DOI: 10.1371/journal.pcbi.1009233] [Cited by in Crossref: 3] [Cited by in F6Publishing: 4] [Article Influence: 3.0] [Reference Citation Analysis]
20 Odening KE, Gomez AM, Dobrev D, Fabritz L, Heinzel FR, Mangoni ME, Molina CE, Sacconi L, Smith G, Stengl M, Thomas D, Zaza A, Remme CA, Heijman J. ESC working group on cardiac cellular electrophysiology position paper: relevance, opportunities, and limitations of experimental models for cardiac electrophysiology research. Europace 2021:euab142. [PMID: 34313298 DOI: 10.1093/europace/euab142] [Cited by in Crossref: 8] [Cited by in F6Publishing: 8] [Article Influence: 8.0] [Reference Citation Analysis]
21 Coveney S, Corrado C, Oakley JE, Wilkinson RD, Niederer SA, Clayton RH. Bayesian Calibration of Electrophysiology Models Using Restitution Curve Emulators. Front Physiol 2021;12:693015. [PMID: 34366883 DOI: 10.3389/fphys.2021.693015] [Cited by in Crossref: 3] [Cited by in F6Publishing: 5] [Article Influence: 3.0] [Reference Citation Analysis]
22 Clerx M, Mirams GR, Rogers AJ, Narayan SM, Giles WR. Immediate and Delayed Response of Simulated Human Atrial Myocytes to Clinically-Relevant Hypokalemia. Front Physiol 2021;12:651162. [PMID: 34122128 DOI: 10.3389/fphys.2021.651162] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 3.0] [Reference Citation Analysis]
23 Whittaker DG, Capel RA, Hendrix M, Chan XHS, Herring N, White NJ, Mirams GR, Burton RB. Cardiac TdP risk stratification modelling of anti-infective compounds including chloroquine and hydroxychloroquine. R Soc Open Sci 2021;8:210235. [PMID: 33996135 DOI: 10.1098/rsos.210235] [Cited by in Crossref: 4] [Cited by in F6Publishing: 5] [Article Influence: 4.0] [Reference Citation Analysis]
24 Del Corso G, Verzicco R, Viola F. On the electrophysiology of the atrial fast conduction system: an uncertain quantification study. Acta Mech Sin 2021;37:264-78. [DOI: 10.1007/s10409-021-01067-1] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
25 Pagani S, Dede' L, Manzoni A, Quarteroni A. Data integration for the numerical simulation of cardiac electrophysiology. Pacing Clin Electrophysiol 2021;44:726-36. [PMID: 33594761 DOI: 10.1111/pace.14198] [Cited by in Crossref: 5] [Cited by in F6Publishing: 6] [Article Influence: 5.0] [Reference Citation Analysis]
26 Paun LM, Colebank MJ, Olufsen MS, Hill NA, Husmeier D. Assessing model mismatch and model selection in a Bayesian uncertainty quantification analysis of a fluid-dynamics model of pulmonary blood circulation. J R Soc Interface 2020;17:20200886. [PMID: 33353505 DOI: 10.1098/rsif.2020.0886] [Cited by in Crossref: 10] [Cited by in F6Publishing: 11] [Article Influence: 5.0] [Reference Citation Analysis]
27 Kügler P. Modelling and Simulation for Preclinical Cardiac Safety Assessment of Drugs with Human iPSC-Derived Cardiomyocytes. Jahresber Dtsch Math Ver 2020;122:209-257. [DOI: 10.1365/s13291-020-00218-w] [Cited by in Crossref: 5] [Cited by in F6Publishing: 5] [Article Influence: 2.5] [Reference Citation Analysis]
28 Pathmanathan P, Galappaththige SK, Cordeiro JM, Kaboudian A, Fenton FH, Gray RA. Data-Driven Uncertainty Quantification for Cardiac Electrophysiological Models: Impact of Physiological Variability on Action Potential and Spiral Wave Dynamics. Front Physiol 2020;11:585400. [PMID: 33329034 DOI: 10.3389/fphys.2020.585400] [Cited by in Crossref: 7] [Cited by in F6Publishing: 8] [Article Influence: 3.5] [Reference Citation Analysis]
29 Zhang H, Zhang S, Wang W, Wang K, Shen W. A Mathematical Model of the Mouse Atrial Myocyte With Inter-Atrial Electrophysiological Heterogeneity. Front Physiol 2020;11:972. [PMID: 32848887 DOI: 10.3389/fphys.2020.00972] [Cited by in Crossref: 6] [Cited by in F6Publishing: 6] [Article Influence: 3.0] [Reference Citation Analysis]
30 Lei CL, Ghosh S, Whittaker DG, Aboelkassem Y, Beattie KA, Cantwell CD, Delhaas T, Houston C, Novaes GM, Panfilov AV, Pathmanathan P, Riabiz M, Dos Santos RW, Walmsley J, Worden K, Mirams GR, Wilkinson RD. Considering discrepancy when calibrating a mechanistic electrophysiology model. Philos Trans A Math Phys Eng Sci 2020;378:20190349. [PMID: 32448065 DOI: 10.1098/rsta.2019.0349] [Cited by in Crossref: 28] [Cited by in F6Publishing: 30] [Article Influence: 14.0] [Reference Citation Analysis]
31 Lei CL, Clerx M, Whittaker DG, Gavaghan DJ, de Boer TP, Mirams GR. Accounting for variability in ion current recordings using a mathematical model of artefacts in voltage-clamp experiments. Philos Trans A Math Phys Eng Sci 2020;378:20190348. [PMID: 32448060 DOI: 10.1098/rsta.2019.0348] [Cited by in Crossref: 20] [Cited by in F6Publishing: 22] [Article Influence: 10.0] [Reference Citation Analysis]
32 Clayton RH, Aboelkassem Y, Cantwell CD, Corrado C, Delhaas T, Huberts W, Lei CL, Ni H, Panfilov AV, Roney C, Dos Santos RW. An audit of uncertainty in multi-scale cardiac electrophysiology models. Philos Trans A Math Phys Eng Sci 2020;378:20190335. [PMID: 32448070 DOI: 10.1098/rsta.2019.0335] [Cited by in Crossref: 15] [Cited by in F6Publishing: 15] [Article Influence: 7.5] [Reference Citation Analysis]
33 Lei CL, Clerx M, Whittaker DG, Gavaghan DJ, de Boer TP, Mirams GR. Accounting for variability in ion current recordings using a mathematical model of artefacts in voltage-clamp experiments.. [DOI: 10.1101/2019.12.20.884353] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.3] [Reference Citation Analysis]