The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Critical Dynamics in Genetic Regulatory Networks: Examples from Four Kingdoms
Open accessAbstract
The coordinated expression of the different genes in an organism is essential to sustain functionality under the random external perturbations to which the organism might be subjected. To cope with such external variability, the global dynamics of the genetic network must possess two central properties. (a) It must be robust enough as to guarantee stability under a broad range of external conditions, and (b) it must be flexible enough to recognize and integrate specific external signals that may help the organism to change and adapt to different environments. This compromise between robustness and adaptability has been observed in dynamical systems operating at the brink of a phase transition between order and chaos. Such systems are termed critical. Thus, criticality, a precise, measurable, and well characterized property of dynamical systems, makes it possible for robustness and adaptability to coexist in living organisms. In this work we investigate the dynamical properties of the gene transcription networks reported for S. cerevisiae, E. coli, and B. subtilis, as well as the network of segment polarity genes of D. melanogaster, and the network of flower development of A. thaliana. We use hundreds of microarray experiments to infer the nature of the regulatory interactions among genes, and implement these data into the Boolean models of the genetic networks. Our results show that, to the best of the current experimental data available, the five networks under study indeed operate close to criticality. The generality of this result suggests that criticality at the genetic level might constitute a fundamental evolutionary mechanism that generates the great diversity of dynamically robust living forms that we observe around us.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Kitano, H. (2004) · Nature Reviews Genetics · doi:10.1038/nrg1471 · Cited by 2,278
Transcription regulation and animal diversity
Levine, M., & Tjian, R. (2003) · Nature · doi:10.1038/nature01763 · Cited by 1,309
Optimal dynamical range of excitable networks at criticality
Kinouchi, O., & Copelli, M. (2006) · Nature Physics · doi:10.1038/nphys289 · Cited by 831
Salgado, H. (2006) · Nucleic Acids Research · doi:10.1093/nar/gkj156 · Cited by 368
Cited by
Emergent complex neural dynamics
Chialvo, D. R. (2010) · Nature Physics · doi:10.1038/nphys1803 · Cited by 1,165
Alvarez-Buylla, E. R., Benítez, M., Corvera-Poiré, A., Chaos Cador, Á., de Folter, S., Gamboa de Buen, A., Garay-Arroyo, A., García-Ponce, B., Jaimes-Miranda, F., Pérez-Ruiz, R. V., et al. (2010) · The Arabidopsis Book · doi:10.1199/tab.0127 · Cited by 298
Self-citationThermodynamics and signatures of criticality in a network of neurons
Tkačik, G., Mora, T., Marre, O., Amodei, D., Palmer, S. E., Berry, M. J., & Bialek, W. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1514188112 · Cited by 253
Palva, J. M., & Palva, S. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.02.060 · Cited by 163
Guiding the self-organization of random Boolean networks
Gershenson, C. (2012) · Theory in Biosciences · doi:10.1007/s12064-011-0144-x · Cited by 68
Metadata
- Authors
- Balleza, E., Alvarez-Buylla, E. R., Chaos, A., Kauffman, S., Shmulevich, I., & Aldana, M.
- Venue
- PLoS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2008-06-18
- Volume
- 3
- Issue
- 6
- Pages
- e2456
- ISSN
- 1932-6203 (ISSN-L)
- OpenAlex
- W2081466838
- Cited by
- 214
- References
- 4
- FWCI
- 5.71
- Type
- journal article
- Language
- en
- Open access
- gold
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.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Critical Dynamics in Genetic Regulatory Networks: Examples from Four Kingdoms. https://app.cochat.ai/papers/10.1371/journal.pone.0002456
- The paper
- Balleza, E., Alvarez-Buylla, E. R., Chaos, A., Kauffman, S., Shmulevich, I., & Aldana, M. (2008). Critical Dynamics in Genetic Regulatory Networks: Examples from Four Kingdoms. PLoS ONE. https://doi.org/10.1371/journal.pone.0002456
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.