Motif for controllable toggle switch in gene regulatory networks

Zhao, Chen; Bin, Ao; Ye, Weiming; Fan, Ying; Di, Zengru

doi:10.1016/j.physa.2014.10.028

Cited by 7 publications

(5 citation statements)

References 42 publications

(46 reference statements)

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“…Typically, different motifs serve distinct functions in different networks [33]. For example, the triangular motifs (M 1 − M 7 ) that are statistically significant exist in social networks; the feedforward loops M 5 are fundamental to transcriptional regulation networks and neural networks [31,57]; the two-hop paths (M 8 − M 13 ) help us to understand the travel patterns of air traffics [22,40]; the open bidirectional wedges (M 13 ) are the most potent motif for the information flow in functional brain networks [32]. M 5 and M 9 are tri-…”

Section: Salient Motifs and Functional Backbone Problemmentioning

confidence: 99%

Motif-h: a novel functional backbone extraction for directed networks

Bai

Fan

et al. 2021

Complex Intell. Syst.

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Dense networks are very pervasive in social analytics, biometrics, communication, architecture, etc. Analyzing and visualizing such large-scale networks are significant challenges, which are generally met by reducing the redundancy on the level of nodes or edges. Motifs, patterns of the higher order organization compared with nodes and edges, are recently found to be the novel fundamental unit structures of complex networks. In this work, we proposed a novel motif h-backbone (Motif-h) method to extract functional cores of directed networks based on both motif strength and h-bridge. Compared with the state-of-the-art method Motif-DF and Entropy, our method solves two main issues which are often found in existing methods: the Motif-h reconsiders weak ties into our candidate set, and those weak ties often have critical functions of bridges in networks; moreover, our method provides a trade-off between the motif size and the edge strength, which quantifies the core edges accordingly. In the simulations, we compare our method with Motif-DF in four real-world networks and found that Motif-h can streamline the extraction of crucial structures compared with the others with limited edges.

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Section: Salient Motifs and Functional Backbone Problemmentioning

confidence: 99%

Motif-h: a novel functional backbone extraction for directed networks

Bai

Fan

et al. 2021

Complex Intell. Syst.

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“…It is used to quantify the ability to steer a dynamical system from an arbitrary initial state to an arbitrary terminal state in finite time. In recent decades, with the development of the internet, the controllability of complex networks has attracted more and more attention and research in the field of engineering control, social networks, energy systems, chemical and biological engineering and other fields [2][3][4][5][6][7][8].…”

Section: Introductionmentioning

confidence: 99%

Effect of the interdependence between subnets on the structural controllability of complex networks

Yang

Chai

et al. 2023

Asian Journal of Control

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Controllability is a hot issue in complex networks. In this paper, without changing the number and the positions of the controllers, the effect of interdependence (viz., inter-coupling relations) between two directed subnets that are controllable or uncontrollable on the structural controllability of complex networks is investigated. According to the Kalman rank criterion and PBH rank criterion, some sufficient conditions and necessary conditions for the structural controllability or uncontrollability of interdependent networks are presented.The results show that (1) if the uncontrollable and controllable nodes in one subnet are inter-coupled with the controllable and uncontrollable nodes in the other subnet, respectively, and the directions are from controllable nodes to the uncontrollable nodes, then the interdependent network may be controllable ; (2) the interdependent network can be obtained structurally controllable if there are simply directed paths covering all the uncontrollable nodes of the two subnets, separately; and (3) the interdependent networks are structurally controllable no matter what kind of inter-couplings between two controllable subnets. All of these results are adaptive to undirected subnets. The final example verifies the effectiveness and correctness of the results provided in this paper.

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“…The first synthetic version of the TS network was built almost 20 years ago and was a milestone of synthetic biology (Gardner et al , ). Since then, it has been built multiple times, extensively studied, and used for its memory, bistability, or hysteresis properties (Kim et al , ; Lou et al , ; Chen & Arkin, ; Padirac et al , ; Sokolowski et al , ; Lebar et al , ; Purcell & Lu, ; Zhao et al , ; Nikolaev & Sontag, ; Andrews et al , ; Pokhilko et al , ; Yang et al , ), for stochasticity fate choice (Sekine et al , ; Wu et al , ; Axelrod et al , ; Perez‐Carrasco et al , ; Weber & Buceta, ; Lugagne et al , ), and to tune threshold activation (Gao et al , ). Nevertheless, its patterning capabilities controlled with a morphogen‐like signal have not been studied in a synthetic system.…”

Section: Introductionmentioning

confidence: 99%

“…Source data are available online for this figure. (Kim et al, 2006;Lou et al, 2010;Chen & Arkin, 2012;Padirac et al, 2012;Sokolowski et al, 2012;Lebar et al, 2014;Purcell & Lu, 2014;Zhao et al, 2015;Nikolaev & Sontag, 2016;Andrews et al, 2018;Pokhilko et al, 2018;Yang et al, 2019), for stochasticity fate choice (Sekine et al, 2011;Wu et al, 2013;Axelrod et al, 2015;Perez-Carrasco et al, 2016;Weber & Buceta, 2016;Lugagne et al, 2017), and to tune threshold activation (Gao et al, 2018). Nevertheless, its patterning capabilities controlled with a morphogen-like signal have not been studied in a synthetic system.…”

Section: Introductionmentioning

confidence: 99%

Controlling spatiotemporal pattern formation in a concentration gradient with a synthetic toggle switch

Barbier

Pérez-Carrasco

Schaerli

2020

Molecular Systems Biology

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The formation of spatiotemporal patterns of gene expression is frequently guided by gradients of diffusible signaling molecules. The toggle switch subnetwork, composed of two cross-repressing transcription factors, is a common component of gene regulatory networks in charge of patterning, converting the continuous information provided by the gradient into discrete abutting stripes of gene expression. We present a synthetic biology framework to understand and characterize the spatiotemporal patterning properties of the toggle switch. To this end, we built a synthetic toggle switch controllable by diffusible molecules in Escherichia coli. We analyzed the patterning capabilities of the circuit by combining quantitative measurements with a mathematical reconstruction of the underlying dynamical system. The toggle switch can produce robust patterns with sharp boundaries, governed by bistability and hysteresis. We further demonstrate how the hysteresis, position, timing, and precision of the boundary can be controlled, highlighting the dynamical flexibility of the circuit.

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Motif for controllable toggle switch in gene regulatory networks

Cited by 7 publications

References 42 publications

Motif-h: a novel functional backbone extraction for directed networks

Motif-h: a novel functional backbone extraction for directed networks

Effect of the interdependence between subnets on the structural controllability of complex networks

Controlling spatiotemporal pattern formation in a concentration gradient with a synthetic toggle switch

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