Dynamics of the Genetic Regulatory Network forArabidopsis thalianaFlower Morphogenesis

Mendoza, Luis; Álvarez-Buylla, Elena

doi:10.1006/jtbi.1998.0701

Cited by 228 publications

(183 citation statements)

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“…A relevant example showing the biological relevance of studying attractors is that of the network which regulates the Arabidopsis thaliana flower morphogenesis [27,79,80]. This network can be modeled by a threshold Boolean automata network.…”

Section: Appendix F Biological Importance Of Attractorsmentioning

confidence: 99%

“Immunetworks”, intersecting circuits and dynamics

Demongeot

Elena

Noual

et al. 2011

Journal of Theoretical Biology

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This paper proposes a study of biological regulatory networks based on a multi-level strategy. Given a network, the first structural level of this strategy consists in analysing the architecture of the network interactions in order to describe it. The second dynamical level consists in relating the patterns found in the architecture to the possible dynamical behaviours of the network. It is known that circuits are the patterns that play the most important part in the dynamics of a network in the sense that they are responsible for the diversity of its asymptotic behaviours. Here, we pursue further this idea and argue that beyond the influence of underlying circuits, intersections of circuits also impact significantly on the dynamics of a network and thus need to be payed special attention to. For some genetic regulation networks involved in the control of the immune system ("immunetworks"), we show that the small number of attractors can be explained by the presence, in the underlying structures of these networks, of intersecting circuits that "inter-lock".

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Section: Appendix F Biological Importance Of Attractorsmentioning

confidence: 99%

“Immunetworks”, intersecting circuits and dynamics

Demongeot

Elena

Noual

et al. 2011

Journal of Theoretical Biology

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“…First, in a Boolean network, a number of elements (genes) are directly connected to one another (e.g., Thomas 1973;Kauffman 1993;Mendoza and Á lvarez-Buylla 1998). The state of each element of the system is either 0 ('OFF') or 1 ('ON') and depends on (i) its state one time unit earlier, (ii) the states, one time unit earlier, of the other elements that serve as input to it, and (iii) the Boolean function determining how its state changes as a function of its input elements.…”

Section: Relaxing Constraints On Theory Correction and Deductive Infementioning

confidence: 99%

Schaffner's Model of Theory Reduction: Critique and Reconstruction

Winther¹

2009

Philosophy of Science

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Schaffner's model of theory reduction has played an important role in philosophy of science and philosophy of biology. Here, the model is found to be problematic because of an internal tension. Indeed, standard antireductionist external criticisms concerning reduction functions and laws in biology do not provide a full picture of the limits of Schaffner's model. However, despite the internal tension, his model usefully highlights the importance of regulative ideals associated with the search for derivational, and embedding, deductive relations among mathematical structures in theoretical biology. A reconstructed Schaffnerian model could therefore shed light on mathematical theory development in the biological sciences and on the epistemology of mathematical practices more generally. Kenneth Schaffner (1967, 1969, 1993a, 1993b has played an important role in the literature on reduction. It provided a clear logical empiricist account of theory reduction. It also served as a counterpoint for critics to develop alternative views of reduction and antireduction. In this paper I wish to complement previous literature on Schaffner's model in two ways. First, I articulate a previously unexplored critique that arises from noticing a tension internal to the model. The model fails on its own terms. Indeed, previous external criticisms regarding the model's logical empiricist assumptions about laws and reduction functions provide an inadequate and incomplete picture of the weaknesses of the model. Introduction. The general model of theory reduction presented by

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“…Gene regulatory network models grounded on experimental data are also important to validate inferences of network connectivity from functional genomic data. Indeed, the network that we proposed for cell fate determination during floral organ specification (Mendoza and Alvarez-Buylla 1998) has been used by several researchers to validate methods of GRN architecture inference (Perkins and others 2004;Aracena and Demongeot 2004).…”

Section: Introductionmentioning

confidence: 99%

From Genes to Flower Patterns and Evolution: Dynamic Models of Gene Regulatory Networks

Chaos

Aldana²,

Espinosa‐Soto

et al. 2006

J Plant Growth Regul

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Genes and proteins form complex dynamical systems or gene regulatory networks (GRN) that can reach several steady states (attractors). These may be associated with distinct cell types. In plants, the ABC combinatorial model establishes the necessary gene combinations for floral organ cell specification. We have developed dynamic gene regulatory network (GRN) models to understand how the combinatorial selection of gene activity is established during floral organ primordia specification as a result of the concerted action of ABC and non-ABC genes. Our analyses have shown that the floral organ specification GRN reaches six attractors with gene configurations observed in primordial cell types during early stages of flower development and four that correspond to regions of the inflorescence meristem. This suggests that it is the overall GRN dynamics rather than precise signals that underlie the ABC model. Furthermore, our analyses suggest that the steady states of the GRN are robust to random alterations of the logical functions that define the gene interactions. Here we have updated the GRN model and have systematically altered the outputs of all the logical functions and addressed in which cases the original attractors are recovered. We then reduced the original threestate GRN to a two-state (Boolean) GRN and performed the same systematic perturbation analysis. Interestingly, the Boolean GRN reaches the same number and type of attractors as reached by the three-state GRN, and it responds to perturbations in a qualitatively identical manner as the original GRN. These results suggest that a Boolean model is sufficient to capture the dynamical features of the floral network and provide additional support for the robustness of the floral GRN. These findings further support that the GRN model provides a dynamical explanation for the ABC model and that the floral GRN robustness could be behind the widespread conservation of the floral plan among eudicotyledoneous plants. Other aspects of evolution of flower organ arrangement and ABC gene expression patterns are discussed in the context of the approach proposed here.Á lvaro Chaos, Max Aldana and Elena Alvarez-Buylla contributed equally to this work.

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Dynamics of the Genetic Regulatory Network forArabidopsis thalianaFlower Morphogenesis

Cited by 228 publications

References 0 publications

“Immunetworks”, intersecting circuits and dynamics

“Immunetworks”, intersecting circuits and dynamics

Schaffner's Model of Theory Reduction: Critique and Reconstruction

From Genes to Flower Patterns and Evolution: Dynamic Models of Gene Regulatory Networks

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