Free Access
Med Sci (Paris)
Volume 26, Number 1, Janvier 2010
Page(s) 57 - 64
Section Biologie des systèmes
Published online 15 January 2010
  1. Rudy Y. From genetics to cellular function using computational biology. Ann NY Acad Sci 2004; 1015 : 261–70. [Google Scholar]
  2. Hunter PJ, Borg TK. Integration from proteins to organs: the Physiome Project. Nat Rev Mol Cell Biol 2003; 4 : 237–43. [Google Scholar]
  3. Brook BS, Waters SL. Mathematical challenges in integrative physiology. J Math Biol 2008; 56 : 893–6. [Google Scholar]
  4. Restrepo JG, Weiss JN, Karma A. Calsequestrin-mediated mechanism for cellular calcium alternans. Biophys J 2008; 95 : 3767–89. [Google Scholar]
  5. Saucerman J, Zhang J, Martin JC, et al. System analysis of PKA-mediated phosphorylation gradients in live cardiac myocytes. Proc Natl Acad Sci USA 2006; 103 :12923–8. [Google Scholar]
  6. Austin TM, Hooks DA, Hunter PJ, et al. Modeling cardiac electrical activity at the cell and tissue levels. Ann NY Acad Sci 2006; 1080 : 334–47. [Google Scholar]
  7. Moe GK, Rheinbolt WC, Abildskov JA. A computer model of atrial fibrillation. Am Heart J 1964; 67 : 200–20. [Google Scholar]
  8. Xie F, Qu Z, Garfinkel A, Weiss JN. Electrical refractory period restitution and spiral wave reentry in simulated cardiac tissue. Am J Physiol Heart Circ Physiol 2002; 283 : H448–60. [Google Scholar]
  9. Comtois P, Sakabe M, Vigmond EJ, et al. Mechanisms of atrial fibrillation termination by rapidly unbinding Na+ channel blockers: insights from mathematical models and experimental correlates. Am J Physiol 2008; 295 : H1489–504. [Google Scholar]
  10. Kléber AG, Rudy Y. Basic mechanisms of cardiac impulse propagation and associated arrhythmias. Physiol Rev 2004; 84 : 431–88. [Google Scholar]
  11. Lim ZY, Maskara B, Aguel F, et al. Spiral wave attachment to millimeter-sized obstacles. Circulation 2006; 114 : 2113–21. [Google Scholar]
  12. Ikeda T, Yashima M, Uchida T, et al. Attachment of meandering reentrant wave fronts to anatomic obstacles in the atrium. Role of obstacle size. Circ Res 1997; 81 : 753–64. [Google Scholar]
  13. Li D, Fareh S, Leung TK, et al. Promotion of atrial fibrillation by heart failure in dogs: atrial remodelling of a different sort. Circulation 1999; 100 : 87–95. [Google Scholar]
  14. Hanna N, Cardin S, Leung TK, et al. Differences in atrial versus ventricular remodelling in dogs with ventricular tachypacing-induced congestive heart failure. Cardiovasc Res 2004; 63 : 236–44. [Google Scholar]
  15. Pastore JM, Rosenbaum DS. Role of structural barriers in the mechanism of alternans-induced reentry. Circ Res 2000; 87 : 1157–63. [Google Scholar]
  16. Comtois P, Vinet A. Curvature effects on activation speed and repolarization in an ionic model of cardiac myocytes. Phys Rev E 1999; 60 : 4619–28. [Google Scholar]
  17. Sampson KJ, Henriquez CS. Interplay of ionic and structural heterogeneity on functional action potential duration gradients: Implications for arrhythmogenesis. Chaos 2002; 12 : 819–28. [Google Scholar]
  18. Ten Tusscher KHWJ, Panfilov AV. Influence of non excitable cells on spiral breakup in two-dimensional and three-dimensional excitable media. Phys Rev E 2003; 68 : 062902. [Google Scholar]
  19. Ten Tusscher KHWJ, Panfilov AV. Wave propagation in excitable media with randomly distributed obstacles. Multiscale Modeling Simulation 2005; 3 : 265–82. [Google Scholar]
  20. Malik M, Camm AJ. Components of heart rate variability- what they mean and what we really measure. Am J Cardiol 1993; 72 : 821–22. [Google Scholar]
  21. Ghosh S, Rhee EK, Avari JN, et al. Cardiac memory in patients with Wolff-Parkinson-White syndrome; noninvasive imaging of activation and repolarization before and after catheter ablation. Circulation 2008; 118 : 907–15. [Google Scholar]
  22. Potse M, Coronel R, Leblanc AR, Vinet A. The role of extracellular potassium transport in computer models of the ischaemic zone. Med Biol Eng Comput 2007; 45 : 1187–99. [Google Scholar]
  23. Henriquez CS. Simulating the electrical behavior of cardiac tissue using the bidomain model. CRC Crit Rev Biomed Eng 1993; 21 : 1–77. [Google Scholar]
  24. Plank G, Zhou L, Greenstein JL, et al. From mitochondrial ion channels to arrhythmias in the heart: Computational techniques to bridge the spatio-temporal scales. Philos Transact A Math Phys Eng Sci 2008; 366 : 3381–409. [Google Scholar]
  25. Potse M, Dubé B, Richer J, et al. A comparison of monodomain and bidomain reaction-diffusion models for action potential propagation in the human heart. IEEE Trans Biomed Eng 2006; 53 : 2425–35. [Google Scholar]
  26. Potse M, Baroudi G, Lanfranchi PA, et al. Generation of the T wave in the electrocardiogram: lessons to be learned from long-QT syndromes. Can J Cardiol 2007; 23 : 238C. [Google Scholar]
  27. Miller WT, Geselowitz DB. Simulation studies of the electrocardiogram; I. The normal heart. Circ Res 1978; 43 : 301–15. [Google Scholar]
  28. Sideman S. The challenge of cardiac modeling-interaction and integration. Ann NY Acad Sci 2006; 1080 : XI-XXIII. [Google Scholar]
  29. Reumann R, Gurev N, Rice JJ. Computational modeling of cardiac disease: potential for personalized medicine. Personnalized Med 2009 : 45–66. [Google Scholar]
  30. Vinet A, Chialvo DR, Michaels DC, Jalife J. Nonlinear dynamics of rate-dependent activation in models of single cardiac cells. Circ Res 1990; 67 : 1510–24. [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.