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Pattern formation in the vertebrate neural tube: a sonic hedgehog morphogen-regulated transcriptional network
Abstract
Neuronal subtype specification in the vertebrate neural tube is one of the best-studied examples of embryonic pattern formation. Distinct neuronal subtypes are generated in a precise spatial order from progenitor cells according to their location along the anterior-posterior and dorsal-ventral axes. Underpinning this organization is a complex network of multiple extrinsic and intrinsic factors. This review focuses on the molecular mechanisms and general strategies at play in ventral regions of the forming spinal cord, where sonic hedgehog-based morphogen signaling is a key determinant. We discuss recent advances in our understanding of these events and highlight unresolved questions.
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Metadata
- Authors
- Dessaud, E., McMahon, A. P., & Briscoe, J.
- Venue
- Development
- Publisher
- The Company of Biologists
- Published
- 2008-08-01
- Volume
- 135
- Issue
- 15
- Pages
- 2489-2503
- ISSN
- 0950-1991 (ISSN-L)
- 1477-9129
- OpenAlex
- W2075994912
- Cited by
- 734
- References
- 119
- FWCI
- 18.24
- Type
- journal article
- Language
- en
- Open access
- closed
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.
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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.