Literature DB >> 34382116

Balanced truncation for model reduction of biological oscillators.

Alberto Padoan1, Fulvio Forni2, Rodolphe Sepulchre2.   

Abstract

Model reduction is a central problem in mathematical biology. Reduced order models enable modeling of a biological system at different levels of complexity and the quantitative analysis of its properties, like sensitivity to parameter variations and resilience to exogenous perturbations. However, available model reduction methods often fail to capture a diverse range of nonlinear behaviors observed in biology, such as multistability and limit cycle oscillations. The paper addresses this need using differential analysis. This approach leads to a nonlinear enhancement of classical balanced truncation for biological systems whose behavior is not restricted to the stability of a single equilibrium. Numerical results suggest that the proposed framework may be relevant to the approximation of classical models of biological systems.
© 2021. The Author(s).

Entities:  

Keywords:  Balanced truncation; Biological oscillators; Dominance theory; Model reduction

Mesh:

Year:  2021        PMID: 34382116      PMCID: PMC8382660          DOI: 10.1007/s00422-021-00888-4

Source DB:  PubMed          Journal:  Biol Cybern        ISSN: 0340-1200            Impact factor:   2.086


  16 in total

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5.  Rigorous elimination of fast stochastic variables from the linear noise approximation using projection operators.

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Authors:  Thomas P Prescott; Antonis Papachristodoulou
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Review 7.  A model for circadian oscillations in the Drosophila period protein (PER).

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Journal:  BMC Syst Biol       Date:  2011-09-07

9.  Reduced modeling of signal transduction - a modular approach.

Authors:  Markus Koschorreck; Holger Conzelmann; Sybille Ebert; Michael Ederer; Ernst Dieter Gilles
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10.  A model reduction method for biochemical reaction networks.

Authors:  Shodhan Rao; Arjan van der Schaft; Karen van Eunen; Barbara M Bakker; Bayu Jayawardhana
Journal:  BMC Syst Biol       Date:  2014-05-03
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