Network motifs: Structure does not determine function.
Open accessAbstract
Background: A 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. Results: We 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. Conclusion: Even 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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Dynamic computational models often possess tens or hundreds of free parameters whose values can significantly affect model behavior.
“A major challenge with such models, however, is that they often possess tens or even hundreds of free parameters whose values can significantly affect model behavior [5,6].”
From Universally Sloppy Parameter Sensitivities in Systems Biology Models (2007) · cites this paper as [5]
The Discussion (page unavailable) says that variation in the bi-fan model’s behavior arises from the parameters used, supporting the claim that parameter values can affect behavior. The Methods describe approximately 30 differential equations, but do not establish that the model has tens or hundreds of free parameters; equations are not a parameter count. (LLM, conf=0.86)
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- Authors
- Ingram, P. J., Stumpf, M. P., & Stark, J.
- Affiliations
- Imperial College London (GB)
- Corresponding author
- Ingram, Piers J
- ORCID
- Stumpf, Michael PH
- Venue
- BMC Genomics
- Published
- 2006-05-05
- Volume
- 7
- Issue
- 1
- Pages
- 108-108
- ISSN
- 1471-2164 (ISSN-L)
- PMC
- PMC1488845
- OpenAlex
- W1808967201
- Cited by
- 267
- References
- 42
- Citations by year
- 2026: 13 · 2025: 5 · 2024: 8 · 2023: 5 · 2022: 4 · 2021: 13 · 2020: 10 · 2019: 11 · 2018: 16 · 2017: 9 · 2016: 20 · 2015: 12 · 2014: 19 · 2013: 29 · 2012: 15
- FWCI
- 6.53
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- BMC Genomics (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Minerva Access (University of Melbourne) (submittedVersion, cc-by)
- Funders
- Wellcome Trust
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Microbial Metabolic Engineering and Bioproduction
- Keywords
- network motifs, gene regulatory networks, transcription factors, ordinary differential equation model, network dynamics, Saccharomyces cerevisiae, kinetic parameters, structure-function relationship
- MeSH terms
- Genes, Fungal, Models, Biological, Saccharomyces cerevisiae, Transcription, Genetic, Gene Expression Regulation, Fungal, Computational Biology, Amino Acid Motifs
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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