2014
DOI: 10.1186/1471-2105-15-221
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Steady state analysis of Boolean molecular network models via model reduction and computational algebra

Abstract: BackgroundA key problem in the analysis of mathematical models of molecular networks is the determination of their steady states. The present paper addresses this problem for Boolean network models, an increasingly popular modeling paradigm for networks lacking detailed kinetic information. For small models, the problem can be solved by exhaustive enumeration of all state transitions. But for larger models this is not feasible, since the size of the phase space grows exponentially with the dimension of the net… Show more

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Cited by 63 publications
(65 citation statements)
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“…Many mathematical tools have been developed for this purpose, leading to several types of modeling frameworks in Systems and Synthetic Biology ( [30,24,3,42,32]). Here we are interested in the link between continuous models (where the variations of concentrations in the molecules are represented by ordinary differential equations) and piecewise linear models as introduced by L. Glass in [14] (see [15,17,8]), where the equations combine piecewise constant production terms with linear degradation.…”
Section: Introductionmentioning
confidence: 99%
“…Many mathematical tools have been developed for this purpose, leading to several types of modeling frameworks in Systems and Synthetic Biology ( [30,24,3,42,32]). Here we are interested in the link between continuous models (where the variations of concentrations in the molecules are represented by ordinary differential equations) and piecewise linear models as introduced by L. Glass in [14] (see [15,17,8]), where the equations combine piecewise constant production terms with linear degradation.…”
Section: Introductionmentioning
confidence: 99%
“…In recent studies, computational algebra has been exploited to theoretically reduce the number of monomials considered, and this has led to the successful reconstruction of the discrete-time finite-state PDSs of gene networks [13,22,30,31,44,46]. In [30], the complicated polynomials created by interpolating time series data were simplified by using the Gröbner basis [12] computed from the data.…”
Section: Introductionmentioning
confidence: 99%
“…Large networks are hard to analyze mathematically, both from discrete and from continuous point of view [15], [17]. Usually in such cases a model reduction technique is applied [13], [17], [18], [19]. The authors of [1] base their model reduction strategy intended for CCNs on cell coloring.…”
Section: Problem Statementmentioning
confidence: 99%
“…Most methods are based on statistics, algebra, combinatorics and topology, see [9], [12], [13], [14]. We notice that a Boolean dynamical system must either have a steady state or a cycle or both; there is no possibility of oscillations and chaotic behaviors, which occur for continuous networks.…”
Section: Preliminaries a Boolean Functions And Dynamical Systemsmentioning
confidence: 99%