Bifurcations and chaos in the MAPK signaling cascade

Zumsande, Martin; Groß, Thilo

doi:10.1016/j.jtbi.2010.04.025

Cited by 46 publications

(46 citation statements)

References 32 publications

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“…This scheme corresponds, for instance, to the top part of the MAPK cascade (Raf-Mek-Erk). These results were further studied by Zumsande and Gross (2010), who applied their approach of generalized modeling to the study of complex dynamical behaviors of MAPK cascades. The idea of this approach is to identify the bifurcations of the system within a whole class of plausible models, by parametrizing the underlying Jacobian matrix of the system equations, rather than parametrizing the rate laws in the model (Gross and Feudel 2006).…”

Section: Discussionmentioning

confidence: 99%

Intrinsic Feedbacks in MAPK Signaling Cascades Lead to Bistability and Oscillations

Sepulchre

Ventura

2013

Acta Biotheor

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Previous studies have demonstrated that double phosphorylation of a protein can lead to bistability if some conditions are fulfilled. It was also shown that the signaling behavior of a covalent modification cycle can be quantitatively and, more importantly, qualitatively modified when this cycle is coupled to a signaling pathway as opposed to being isolated. This property was named retroactivity. These two results are studied together in this paper showing the existence of interesting phenomena--oscillations and bistability--in signaling cascades possessing at least one stage with a double-phosphorylation cycle as in MAPK cascades.

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Section: Discussionmentioning

confidence: 99%

Intrinsic Feedbacks in MAPK Signaling Cascades Lead to Bistability and Oscillations

Sepulchre

Ventura

2013

Acta Biotheor

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“…However, when searching for the disruptive research result that provided insight into the design principles of the cascade and its evolutionary constraints, the seminal work by Huang and Ferrell [20] stands out, where the cascade was related to ultrasensitivity. A recent progress in understanding further generic principles is reported in [21], where the broad range of dynamical behaviors a MAPK cascade can potentially display was studied with a technique developed in Physics -generalized modeling [22].…”

Section: Physics and Systems Biology -Some Rules Of Interactionmentioning

confidence: 99%

The Physics behind Systems Biology

Radde

Hütt

2016

EPJ Nonlinear Biomed Phys

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Systems Biology is a young and rapidly evolving research field, which combines experimental techniques and mathematical modeling in order to achieve a mechanistic understanding of processes underlying the regulation and evolution of living systems. Systems Biology is often associated with an Engineering approach: The purpose is to formulate a data-rich, detailed simulation model that allows to perform numerical ('in silico') experiments and then draw conclusions about the biological system. While methods from Engineering may be an appropriate approach to extending the scope of biological investigations to experimentally inaccessible realms and to supporting data-rich experimental work, it may not be the best strategy in a search for design principles of biological systems and the fundamental laws underlying Biology. Physics has a long tradition of characterizing and understanding emergent collective behaviors in systems of interacting units and searching for universal laws. Therefore, it is natural that many concepts used in Systems Biology have their roots in Physics. With an emphasis on Theoretical Physics, we will here review the 'Physics core' of Systems Biology, show how some success stories in Systems Biology can be traced back to concepts developed in Physics, and discuss how Systems Biology can further benefit from its Theoretical Physics foundation.

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“…External stimulation on the cell induces a concentration fluctuation in the phosphorylation of the signaling molecules. More specifically, a fluctuation in the signaling molecules' concentration tentatively increases, followed by a decrease over a long duration, τ j , of several hours [7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23][24] (Figure 1). Here, we defined the occurrence probability, p j and p j * , which represents the selection probability of j-th step using X j or X j *, respectively:…”

Section: Introductionmentioning

confidence: 99%

Information Thermodynamics Derives the Entropy Current of Cell Signal Transduction as a Model of a Binary Coding System

Tsuruyama

2018

Entropy

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Abstract:The analysis of cellular signaling cascades based on information thermodynamics has recently developed considerably. A signaling cascade may be considered a binary code system consisting of two types of signaling molecules that carry biological information, phosphorylated active, and non-phosphorylated inactive forms. This study aims to evaluate the signal transduction step in cascades from the viewpoint of changes in mixing entropy. An increase in active forms may induce biological signal transduction through a mixing entropy change, which induces a chemical potential current in the signaling cascade. We applied the fluctuation theorem to calculate the chemical potential current and found that the average entropy production current is independent of the step in the whole cascade. As a result, the entropy current carrying signal transduction is defined by the entropy current mobility.

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Bifurcations and chaos in the MAPK signaling cascade

Cited by 46 publications

References 32 publications

Intrinsic Feedbacks in MAPK Signaling Cascades Lead to Bistability and Oscillations

Intrinsic Feedbacks in MAPK Signaling Cascades Lead to Bistability and Oscillations

The Physics behind Systems Biology

Information Thermodynamics Derives the Entropy Current of Cell Signal Transduction as a Model of a Binary Coding System

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