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Items: 1 to 20 of 77

1.

Parameter sensitivity analysis in electrophysiological models using multivariable regression.

Sobie EA.

Biophys J. 2009 Feb 18;96(4):1264-74. doi: 10.1016/j.bpj.2008.10.056.

2.

Regression analysis for constraining free parameters in electrophysiological models of cardiac cells.

Sarkar AX, Sobie EA.

PLoS Comput Biol. 2010 Sep 2;6(9):e1000914. doi: 10.1371/journal.pcbi.1000914.

3.

Parameter estimation in cardiac ionic models.

Dokos S, Lovell NH.

Prog Biophys Mol Biol. 2004 Jun-Jul;85(2-3):407-31.

PMID:
15142755
4.

Excitation-contraction coupling gain in ventricular myocytes: insights from a parsimonious model.

Sobie EA, Ramay HR.

J Physiol. 2009 Mar 15;587(Pt 6):1293-9. doi: 10.1113/jphysiol.2008.163915. Epub 2009 Jan 19.

5.

A global sensitivity tool for cardiac cell modeling: Application to ionic current balance and hypertrophic signaling.

Sher AA, Cooling MT, Bethwaite B, Tan J, Peachey T, Enticott C, Garic S, Gavaghan DJ, Noble D, Abramson D, Crampin EJ.

Conf Proc IEEE Eng Med Biol Soc. 2010;2010:1498-502. doi: 10.1109/IEMBS.2010.5626841.

PMID:
21096366
6.

High frequency stimulation of cardiac myocytes: a theoretical and computational study.

Weinberg SH.

Chaos. 2014 Dec;24(4):043104. doi: 10.1063/1.4897618.

PMID:
25554024
7.

Dynamical analysis of the calcium signaling pathway in cardiac myocytes based on logarithmic sensitivity analysis.

Kim TH, Shin SY, Choo SM, Cho KH.

Biotechnol J. 2008 May;3(5):639-47. doi: 10.1002/biot.200700247.

PMID:
18246569
8.

Frequency and release flux of calcium sparks in rat cardiac myocytes: a relation to RYR gating.

Zahradníková A, Valent I, Zahradník I.

J Gen Physiol. 2010 Jul;136(1):101-16. doi: 10.1085/jgp.200910380. Epub 2010 Jun 14.

9.

A generic ionic model of cardiac action potentials.

Guo T, Abed AA, Lovell NH, Dokos S.

Conf Proc IEEE Eng Med Biol Soc. 2010;2010:1465-8. doi: 10.1109/IEMBS.2010.5626853.

PMID:
21096358
10.

Parameter identifiability of cardiac ionic models using a novel CellML least squares optimization tool.

Hui BB, Dokos S, Lovell NH.

Conf Proc IEEE Eng Med Biol Soc. 2007;2007:5307-10.

PMID:
18003205
11.

EAD and DAD mechanisms analyzed by developing a new human ventricular cell model.

Asakura K, Cha CY, Yamaoka H, Horikawa Y, Memida H, Powell T, Amano A, Noma A.

Prog Biophys Mol Biol. 2014 Sep;116(1):11-24. doi: 10.1016/j.pbiomolbio.2014.08.008. Epub 2014 Sep 1.

12.

Parameter sensitivity analysis of stochastic models provides insights into cardiac calcium sparks.

Lee YS, Liu OZ, Hwang HS, Knollmann BC, Sobie EA.

Biophys J. 2013 Mar 5;104(5):1142-50. doi: 10.1016/j.bpj.2012.12.055.

13.
14.

Parameter fitting using multiple datasets in cardiac action potential modeling.

Guo T, Al Abed A, Lovell NH, Dokos S.

Conf Proc IEEE Eng Med Biol Soc. 2011;2011:158-61. doi: 10.1109/IEMBS.2011.6089918.

PMID:
22254274
15.

On the performance of an implicit-explicit Runge-Kutta method in models of cardiac electrical activity.

Spiteri RJ, Dean RC.

IEEE Trans Biomed Eng. 2008 May;55(5):1488-95. doi: 10.1109/TBME.2007.914677.

PMID:
18440894
16.

A comparison of non-standard solvers for ODEs describing cellular reactions in the heart.

Maclachlan MC, Sundnes J, Spiteri RJ.

Comput Methods Biomech Biomed Engin. 2007 Oct;10(5):317-26.

PMID:
17852182
17.

Simulation of Ca-calmodulin-dependent protein kinase II on rabbit ventricular myocyte ion currents and action potentials.

Grandi E, Puglisi JL, Wagner S, Maier LS, Severi S, Bers DM.

Biophys J. 2007 Dec 1;93(11):3835-47. Epub 2007 Aug 17.

18.
19.

Mathematical model of mouse embryonic cardiomyocyte excitation-contraction coupling.

Korhonen T, Rapila R, Tavi P.

J Gen Physiol. 2008 Oct;132(4):407-19. doi: 10.1085/jgp.200809961. Epub 2008 Sep 15.

20.

ATX-II effects on the apparent location of M cells in a computational model of a human left ventricular wedge.

Dos Santos RW, Otaviano Campos F, Neumann Ciuffo L, Nygren A, Giles W, Koch H.

J Cardiovasc Electrophysiol. 2006 May;17 Suppl 1:S86-S95.

PMID:
16686688

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