Literature DB >> 9579029

A methodological basis for description and analysis of systems with complex switch-like interactions.

E Plahte1, T Mestl, S W Omholt.   

Abstract

A wide range of complex systems appear to have switch-like interactions, i.e. below (or above) a certain threshold x has no or little influence on y, while above (or below) this threshold the effect of x on y saturates rapidly to a constant level. Switching functions are frequently described by sigmoid functions or combinations of these. Within the context of ordinary differential equations we present a very general methodological basis for designing and analysing models involving complicated switching functions together with any other non-linearities. A procedure to determine position and stability properties of all stationary points lying close to a threshold for one or several variables, so-called singular stationary points, is developed. Such points may represent homeostatic states in models, and are therefore of considerable interest. The analysis provides a profound insight into the generic effects of steep sigmoid interactions on the dynamics around homeostatic points. It leads to qualitative as well as quantitative predictions without using advanced mathematical methods. Thus, it may have an important heuristic function in connection with numerical simulations aimed at unfolding the predictive potential of realistic models.

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Year:  1998        PMID: 9579029     DOI: 10.1007/s002850050103

Source DB:  PubMed          Journal:  J Math Biol        ISSN: 0303-6812            Impact factor:   2.259


  18 in total

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3.  Statistical epistasis is a generic feature of gene regulatory networks.

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4.  Pattern formation by dynamically interacting network motifs.

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Journal:  Proc Natl Acad Sci U S A       Date:  2009-02-13       Impact factor: 11.205

5.  Nonlinear regulation enhances the phenotypic expression of trans-acting genetic polymorphisms.

Authors:  Arne B Gjuvsland; Ben J Hayes; Theo H E Meuwissen; Erik Plahte; Stig W Omholt
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6.  Monotonicity is a key feature of genotype-phenotype maps.

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7.  Geometric properties of a class of piecewise affine biological network models.

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Journal:  J Math Biol       Date:  2005-12-28       Impact factor: 2.164

8.  A computational framework for qualitative simulation of nonlinear dynamical models of gene-regulatory networks.

Authors:  Liliana Ironi; Luigi Panzeri
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9.  Spatial analysis of expression patterns predicts genetic interactions at the mid-hindbrain boundary.

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Journal:  PLoS Comput Biol       Date:  2009-11-20       Impact factor: 4.475

10.  Transforming Boolean models to continuous models: methodology and application to T-cell receptor signaling.

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