ArticleBMC genomics2006
Network motifs: structure does not determine function.
Article in BMC genomics, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 84 papers.
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Who cites it
84 citing papers in PubMed.
- Engineering principles in plant metabolism: integrating control, mechanics, and transport under dynamic environments.Plant physiology · 2026Review
- Symmetries in metabolic networks ofPNAS nexus · 2025Article
- QOMIC: quantum optimization for motif identification.Bioinformatics advances · 2025Article
- Dynamics and bifurcations in genetic circuits with fibration symmetries.Journal of the Royal Society, Interface · 2024Article
- Competition and evolutionary selection among core regulatory motifs in gene expression control.Nature communications · 2023Article
- A group theoretic approach to model comparison with simplicial representations.Journal of mathematical biology · 2022Article
- A synthetic synthesis to explore animal evolution and development.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2022Review
- Turing pattern design principles and their robustness.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2021Review
- Integrated omics networks reveal the temporal signaling events of brassinosteroid response in Arabidopsis.Nature communications · 2021Article
- Model comparison via simplicial complexes and persistent homology.Royal Society open science · 2021Article
- Dynamical modules in metabolism, cell and developmental biology.Interface focus · 2021Article
- Self-selection of evolutionary strategies: adaptiveHeliyon · 2021Article
- Testing biological network motif significance with exponential random graph models.Applied network science · 2021Article
- Likelihood-free nested sampling for parameter inference of biochemical reaction networks.PLoS computational biology · 2020Article
- Circuits with broken fibration symmetries perform core logic computations in biological networks.PLoS computational biology · 2020Article
- Integrated multi-omics framework of the plant response to jasmonic acid.Nature plants · 2020Article
- Stem-cell-ubiquitous genes spatiotemporally coordinate division through regulation of stem-cell-specific gene networks.Nature communications · 2019Article
- Article
- Feed-forward regulation adaptively evolves via dynamics rather than topology when there is intrinsic noise.Nature communications · 2019Article
- An enriched network motif family regulates multistep cell fate transitions with restricted reversibility.PLoS computational biology · 2019Article
24 more citing papers are in PubMed but not listed here.
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3 authors.
Funding
Abstract
backgroundA number of publications have recently examined the occurrence and properties of the feed-forward motif in a variety of networks, including those that are of interest in genome biology, such as gene networks. The present work looks in some detail at the dynamics of the bi-fan motif, using systems of ordinary differential equations to model the populations of transcription factors, mRNA and protein, with the aim of extending our understanding of what appear to be important building blocks of gene network structure.
resultsWe develop an ordinary differential equation model of the bi-fan motif and analyse variants of the motif corresponding to its behaviour under various conditions. In particular, we examine the effects of different steady and pulsed inputs to five variants of the bifan motif, based on evidence in the literature of bifan motifs found in Saccharomyces cerevisiae (commonly known as baker's yeast). Using this model, we characterize the dynamical behaviour of the bi-fan motif for a wide range of biologically plausible parameters and configurations. We find that there is no characteristic behaviour for the motif, and with the correct choice of parameters and of internal structure, very different, indeed even opposite behaviours may be obtained.
conclusionEven with this relatively simple model, the bi-fan motif can exhibit a wide range of dynamical responses. This suggests that it is difficult to gain significant insights into biological function simply by considering the connection architecture of a gene network, or its decomposition into simple structural motifs. It is necessary to supplement such structural information by kinetic parameters, or dynamic time series experimental data, both of which are currently difficult to obtain.
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