The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Positional information and reaction-diffusion: two big ideas in developmental biology combine
Open accessAbstract
One of the most fundamental questions in biology is that of biological pattern: how do the structures and shapes of organisms arise? Undoubtedly, the two most influential ideas in this area are those of Alan Turing's ‘reaction-diffusion’ and Lewis Wolpert's ‘positional information’. Much has been written about these two concepts but some confusion still remains, in particular about the relationship between them. Here, we address this relationship and propose a scheme of three distinct ways in which these two ideas work together to shape biological form.
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Cites
The chemical basis of morphogenesis
Turing, A. M. (1952) · Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences · doi:10.1098/rstb.1952.0012 · Cited by 11,733
Reaction-Diffusion Model as a Framework for Understanding Biological Pattern Formation
Kondo, S., & Miura, T. (2010) · Science · doi:10.1126/science.1179047 · Cited by 1,651
Generation of the primary hair follicle pattern.
Mou, C., Jackson, B., Schneider, P., Overbeek, P. A., & Headon, D. J. (2006) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0600825103 · Cited by 206
Turing patterns in development: what about the horse part?
Marcon, L., & Sharpe, J. (2012) · Current Opinion in Genetics & Development · doi:10.1016/j.gde.2012.11.013 · Cited by 130
Self-citation
Cited by
Progress and potential in organoid research
Rossi, G., Manfrin, A., & Lutolf, M. P. (2018) · Nature Reviews Genetics · doi:10.1038/s41576-018-0051-9 · Cited by 1,182
Programming self-organizing multicellular structures with synthetic cell-cell signaling
Toda, S., Blauch, L. R., Tang, S. K. Y., Morsut, L., & Lim, W. A. (2018) · Science · doi:10.1126/science.aat0271 · Cited by 470
Programmed and self-organized flow of information during morphogenesis
Collinet, C., & Lecuit, T. (2021) · Nature Reviews Molecular Cell Biology · doi:10.1038/s41580-020-00318-6 · Cited by 322
Agent-based modeling of morphogenetic systems: advantages and challenges.
Glen, C. M., Kemp, M. L., & Voit, E. O. (2019) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1006577 · Cited by 116
Optimal control of gene regulatory networks for morphogen-driven tissue patterning
Pezzotta, A., & Briscoe, J. (2023) · Cell Systems · doi:10.1016/j.cels.2023.10.004 · Cited by 34
Metadata
- Authors
- Green, J. B. A., & Sharpe, J.
- Venue
- Development
- Publisher
- The Company of Biologists
- Published
- 2015-04-01
- Volume
- 142
- Issue
- 7
- Pages
- 1203-1211
- ISSN
- 0950-1991 (ISSN-L)
- 1477-9129
- OpenAlex
- W1969357685
- Cited by
- 421
- References
- 4
- FWCI
- 11.96
- Type
- journal article
- Language
- en
- Open access
- hybrid
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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.
