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Computational approaches to cellular rhythms

Author

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  • Albert Goldbeter

    (Unité de Chronobiologie théorique, Faculté des Sciences, Université Libre de Bruxelles)

Abstract

Oscillations arise in genetic and metabolic networks as a result of various modes of cellular regulation. In view of the large number of variables involved and of the complexity of feedback processes that generate oscillations, mathematical models and numerical simulations are needed to fully grasp the molecular mechanisms and functions of biological rhythms. Models are also necessary to comprehend the transition from simple to complex oscillatory behaviour and to delineate the conditions under which they arise. Examples ranging from calcium oscillations to pulsatile intercellular communication and circadian rhythms illustrate how computational biology contributes to clarify the molecular and dynamical bases of cellular rhythms.

Suggested Citation

  • Albert Goldbeter, 2002. "Computational approaches to cellular rhythms," Nature, Nature, vol. 420(6912), pages 238-245, November.
    • Handle: RePEc:nat:nature:v:420:y:2002:i:6912:d:10.1038_nature01259
    DOI: 10.1038/nature01259
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    Cited by:

    1. Hellweger, Ferdi L., 2008. "The role of inter-generation memory in diel phytoplankton division patterns," Ecological Modelling, Elsevier, vol. 212(3), pages 382-396.
    2. Wassim Abou-Jaoudé & Madalena Chaves & Jean-Luc Gouzé, 2011. "A Theoretical Exploration of Birhythmicity in the p53-Mdm2 Network," PLOS ONE, Public Library of Science, vol. 6(2), pages 1-12, February.
    3. Zhou, Peipei & Cai, Shuiming & Liu, Zengrong & Chen, Luonan & Wang, Ruiqi, 2013. "Coupling switches and oscillators as a means to shape cellular signals in biomolecular systems," Chaos, Solitons & Fractals, Elsevier, vol. 50(C), pages 115-126.
    4. Bottani, Samuel & Grammaticos, Basile, 2008. "A simple model of genetic oscillations through regulated degradation," Chaos, Solitons & Fractals, Elsevier, vol. 38(5), pages 1468-1482.
    5. Irene Otero-Muras & Julio R Banga, 2016. "Design Principles of Biological Oscillators through Optimization: Forward and Reverse Analysis," PLOS ONE, Public Library of Science, vol. 11(12), pages 1-26, December.
    6. Šimonka, Vito & Fras, Maja & Gosak, Marko, 2015. "Stochastic simulation of the circadian rhythmicity in the SCN neuronal network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 424(C), pages 1-10.
    7. Jie Chen & Kuang‐Chao Chang, 2008. "Discovering Statistically Significant Periodic Gene Expression," International Statistical Review, International Statistical Institute, vol. 76(2), pages 228-246, August.
    8. Treenut Saithong & Kevin J Painter & Andrew J Millar, 2010. "Consistent Robustness Analysis (CRA) Identifies Biologically Relevant Properties of Regulatory Network Models," PLOS ONE, Public Library of Science, vol. 5(12), pages 1-11, December.
    9. O. Slaby & S. Sager & O. S. Shaik & U. Kummer & D. Lebiedz, 2007. "Optimal control of self-organized dynamics in cellular signal transduction," Mathematical and Computer Modelling of Dynamical Systems, Taylor & Francis Journals, vol. 13(5), pages 487-502, October.

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