The DOI matches its Crossref record; 25 of the 25 references it cites were found in a registry or an index.
Cell–cell interaction and diversity of emergent behaviours
Abstract
Despite myriads of possible gene expression profiles, cells tend to be found in a confined number of expression patterns. The dynamics of Boolean models of gene regulatory networks has proven to be a likely candidate for the description of such self-organisation phenomena. Because cells do not live in isolation, but they constantly shape their functions to adapt to signals from other cells, this raises the question of whether the cooperation among cells entails an expansion or a reduction of their possible steady states. Multi random Boolean networks are introduced here as a model for interaction among cells that might be suitable for the investigation of some generic properties regarding the influence of communication on the diversity of cell behaviours. In spite of its simplicity, the model exhibits a non-obvious phenomenon according to which a moderate exchange of products among adjacent cells fosters the variety of their possible behaviours, which on the other hand are more similar to one another. On the contrary, a more invasive coupling would lead cells towards homogeneity.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“This may lead to an increased number of stable transcriptional states (attractors), as has been shown in computer simulations that connect each cell’s GRNs to a cell–cell interaction network (60).”
From Behavior-related gene regulatory networks: A new level of organization in the brain (2020) · cites this paper as [60]
Citations
Cites
The Origins of Order: Self-Organization and Selection in Evolution
Kauffman, S. A. (1993) · doi:10.1093/oso/9780195079517.001.0001 · Cited by 7,855
Self-citationMetabolic stability and epigenesis in randomly constructed genetic nets
Kauffman, S. A. (1969) · Journal of Theoretical Biology · doi:10.1016/0022-5193(69)90015-0 · Cited by 4,819
Self-citationKauffman, S. A. (2000) · doi:10.1093/oso/9780195121049.001.0001 · Cited by 950
Self-citationRandom Networks of Automata: A Simple Annealed Approximation
Derrida, B., & Pomeau, Y. (1986) · Europhysics Letters (EPL) · doi:10.1209/0295-5075/1/2/001 · Cited by 706
Reconstruction of cellular signalling networks and analysis of their properties
Papin, J. A., Hunter, T., Palsson, B. O., & Subramaniam, S. (2005) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm1570 · Cited by 532
A phase-shift model for the spatial and temporal organization of developing systems
Goodwin, B. C., & Cohen, M. H. (1969) · Journal of Theoretical Biology · doi:10.1016/s0022-5193(69)80017-2 · Cited by 330
Boolean Dynamics with Random Couplings
Aldana, M., Coppersmith, S., & Kadanoff, L. P. (2003) · Perspectives and Problems in Nolinear Science · doi:10.1007/978-0-387-21789-5_2 · Cited by 313
Marée, A. F. M., & Hogeweg, P. (2001) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.061535198 · Cited by 245
Eukaryotic cells are dynamically ordered or critical but not chaotic
Shmulevich, I., Kauffman, S. A., & Aldana, M. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0506771102 · Cited by 230
Self-citationControl of Sequential Compartment Formation in Drosophila
Kauffman, S. A., Shymko, R. M., & Trabert, K. C. (1978) · Science · doi:10.1126/science.413193 · Cited by 230
Self-citationHogeweg, P. (2000) · Journal of Theoretical Biology · doi:10.1006/jtbi.2000.1087 · Cited by 191
Scaling in Ordered and Critical Random Boolean Networks
Socolar, J. E. S., & Kauffman, S. A. (2003) · Physical Review Letters · doi:10.1103/physrevlett.90.068702 · Cited by 182
Self-citationChapter 5 Gene Regulation Networks: A Theory For Their Global Structure and Behaviors
Kauffman, S. A. (1971) · Current topics in developmental biology/Current Topics in Developmental Biology · doi:10.1016/s0070-2153(08)60640-7 · Cited by 167
Self-citationGenetic network models and statistical properties of gene expression data in knock-out experiments
Serra, R., Villani, M., & Semeria, A. (2004) · Journal of Theoretical Biology · doi:10.1016/j.jtbi.2003.10.018 · Cited by 163
Self-citationSerra, R., Villani, M., Graudenzi, A., & Kauffman, S. A. (2007) · Journal of Theoretical Biology · doi:10.1016/j.jtbi.2007.01.012 · Cited by 147
Self-citationPositional information and patterning revisited
Wolpert, L. (2010) · Journal of Theoretical Biology · doi:10.1016/j.jtbi.2010.10.034 · Cited by 133
A proposal for using the ensemble approach to understand genetic regulatory networks
Kauffman, S. A. (2004) · Journal of Theoretical Biology · doi:10.1016/j.jtbi.2003.12.017 · Cited by 130
Self-citationSpace-dependent cell determination under the control of a morphogen gradient
Meinhardt, H. (1978) · Journal of Theoretical Biology · doi:10.1016/0022-5193(78)90078-4 · Cited by 126
Perturbation avalanches and criticality in gene regulatory networks
Rämö, P., Kesseli, J., & Yli-Harja, O. P. (2006) · Journal of Theoretical Biology · doi:10.1016/j.jtbi.2006.02.011 · Cited by 122
Isologous diversification: A theory of cell differentiation
Kaneko, K., & Yomo, T. (1997) · Bulletin of Mathematical Biology · doi:10.1007/bf02459474 · Cited by 95
A Darwinian theory for the origin of cellular differentiation
Kupiec, J.-J. (1997) · Molecular and General Genetics MGG · doi:10.1007/s004380050490 · Cited by 94
Jackson, E. R., Johnson, D. R., & Nash, W. G. (1986) · Journal of Theoretical Biology · doi:10.1016/s0022-5193(86)80190-4 · Cited by 24
Coupled Random Boolean Network Forming an Artificial Tissue
Villani, M., Serra, R., Ingrami, P., & Kauffman, S. A. (2006) · Lecture notes in computer science · doi:10.1007/11861201_63 · Cited by 19
Self-citationPattern formation in insect embryogenesis: The evolution of concepts and mechanisms
Sander, K. (1996) · International Journal of Insect Morphology and Embryology · doi:10.1016/s0020-7322(96)00021-9 · Cited by 17
Rohlf, T., & Bornholdt, S. (2009) · Journal of Theoretical Biology · doi:10.1016/j.jtbi.2009.07.023 · Cited by 11
Research works printed but not linked: 8
- Berks, 1991, 113, 131
- Bull, L., and Alonso-Sanz, R.: ‘On coupling random Boolean networks’’, Adamatzky, A., Alonso-Sanz, R., Lawniczak, A., Martinez, G.J., Morita, K., Worsch, T., Automata-2008: Theory and Applications of Cellular Automata, (Luniver Press 2008), p. 292–305
- Serra, 2008, Proc. Eighth Int. Conf. on Cellular Auotomata ACRI 2008, 315
- Kauffman, S.A.: ‘At home in the universe’, (Oxford University Press 1995)
- Serra, 2007, Proc. European Conf. on Complex Systems, ECCS07, paper 35
- Damiani, 2008, WIVACE 2008, 271
- Okamoto, 1997, 57, 141
- Yacoubi, 2006, Seventh Int. Conf. on Cellular Automata for Research and Industry
Cited by
Behavior-related gene regulatory networks: A new level of organization in the brain
Sinha, S., Jones, B. M., Traniello, I. M., Bukhari, S. A., Halfon, M. S., Hofmann, H. A., Huang, S., Katz, P. S., Keagy, J., Lynch, V. J., et al. (2020) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1921625117 · Cited by 85
Metadata
- Authors
- Damiani, C., Serra, R., Villani, M., Kauffman, S. A., & Colacci, A.
- Affiliations
- Department of Social, Cognitive and Quantitative Sciences, Modena and Reggio Emilia University, via Allegri 9, Reggio Emilia, I-42100, Italia
- Complex Systems Centre, University of Vermont, 200C Farrell Hall, 210 Colchester Ave, Burlington, VT 05405, USA
- Excellence Environmental Carcinogenesis, Environmental Protection and Health Prevention Agency, Emilia-Romagna, viale Filopanti 22, Bologna, Italia
- Venue
- IET Systems Biology
- Published
- 2011-03-11
- Volume
- 5
- Issue
- 2
- Pages
- 137-144
- ISSN
- 1751-8849
- 1751-8857
- Cited by
- 38
- References
- 25
- Language
- en
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
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.