ArticleBMC systems biology2009
Specialized or flexible feed-forward loop motifs: a question of topology.
Article in BMC systems biology, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Dynamics and bifurcations in genetic circuits with fibration symmetries.Journal of the Royal Society, Interface · 2024Article
- Application of a novel numerical simulation to biochemical reaction systems.Frontiers in cell and developmental biology · 2024Article
- Circuits with broken fibration symmetries perform core logic computations in biological networks.PLoS computational biology · 2020Article
- A spectrum of modularity in multi-functional gene circuits.Molecular systems biology · 2017Article
- The combination of the functionalities of feedback circuits is determinant for the attractors' number and size in pathway-like Boolean networks.Scientific reports · 2017Article
- Form and function in gene regulatory networks: the structure of network motifs determines fundamental properties of their dynamical state space.Journal of the Royal Society, Interface · 2016Article
- Noise Decomposition Principle in a Coherent Feed-Forward Transcriptional Regulatory Loop.Frontiers in physiology · 2016Article
- Function does not follow form in gene regulatory circuits.Scientific reports · 2015Article
- Design principles of stripe-forming motifs: the role of positive feedback.Scientific reports · 2014Article
- Lessons from the modular organization of the transcriptional regulatory network of Bacillus subtilis.BMC systems biology · 2013Article
- Reducing the complexity of complex gene coexpression networks by coupling multiweighted labeling with topological analysis.BioMed research international · 2013Article
- Evolvability of feed-forward loop architecture biases its abundance in transcription networks.BMC systems biology · 2012Article
- Protein scaffolds can enhance the bistability of multisite phosphorylation systems.PLoS computational biology · 2012Article
- Review
- Structural discrimination of robustness in transcriptional feedforward loops for pattern formation.PloS one · 2011Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundNetwork motifs are recurrent interaction patterns, which are significantly more often encountered in biological interaction graphs than expected from random nets. Their existence raises questions concerning their emergence and functional capacities. In this context, it has been shown that feed forward loops (FFL) composed of three genes are capable of processing external signals by responding in a very specific, robust manner, either accelerating or delaying responses. Early studies suggested a one-to-one mapping between topology and dynamics but such view has been repeatedly questioned. The FFL's function has been attributed to this specific response. A general response analysis is difficult, because one is dealing with the dynamical trajectory of a system towards a new regime in response to external signals.
resultsWe have developed an analytical method that allows us to systematically explore the patterns and probabilities of the emergence for a specific dynamical response. The method is based on a rather simple, but powerful geometrical analysis of the system's nullclines complemented by an appropriate formalization of the response probability.
conclusionOur analysis allows to determine unambiguously the relationship between motif topology and the set of potentially implementable functions. The distribution probability distributions are linked to the degree of specialization or flexibility of the given network topology. The implications for the emergence of different motif topologies in complex networks are outlined.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.