The DOI matches its Crossref record; 75 of the 75 references it cites were found in a registry or an index.
Genetic control of dendritic morphogenesis in Drosophila
Abstract
How the dendritic branching patterns of different neurons are specified is a fascinating question in developmental neurobiology. This question can now be addressed in detail in Drosophila, owing to technological advances that allow in vivo labeling of the dendrites of identifiable neurons. Recent genetic analyses in flies have uncovered several molecules, including transcription factors, cytoskeleton-associated proteins and membrane receptor-like molecules, that provide a glimpse into the complex regulatory network that controls dendritic morphogenesis.
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“Conversely, the bGRN indirectly controls NN activity via setting the production levels of neurotransmitter receptors, ion channels, axon outgrowths, dendritic arborizations, and other physico-chemical components of the NN (49–52).”
From Behavior-related gene regulatory networks: A new level of organization in the brain (2020) · cites this paper as [52]
Citations
Cites
Targeted gene expression as a means of altering cell fates and generating dominant phenotypes
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Lee, T., & Luo, L. (1999) · Neuron · doi:10.1016/s0896-6273(00)80701-1 · Cited by 2,587
The ancient regulatory-protein family of WD-repeat proteins
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Overexpression of Math1 induces robust production of extra hair cells in postnatal rat inner ears
Zheng, J. L., & Gao, W.-Q. (2000) · Nature Neuroscience · doi:10.1038/75753 · Cited by 798
Diversity and Dynamics of Dendritic Signaling
Häusser, M., Spruston, N., & Stuart, G. J. (2000) · Science · doi:10.1126/science.290.5492.739 · Cited by 782
Usui, T., Shima, Y., Shimada, Y., Hirano, S., Burgess, R. W., Schwarz, T. L., Takeichi, M., & Uemura, T. (1999) · Cell · doi:10.1016/s0092-8674(00)80046-x · Cited by 720
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Activity-dependent regulation of dendritic growth and patterning
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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
Intra-neuronal Competition for Synaptic Partners Conserves the Amount of Dendritic Building Material
Ryglewski, S., Vonhoff, F., Scheckel, K., & Duch, C. (2017) · Neuron · doi:10.1016/j.neuron.2016.12.043 · Cited by 30
Metadata
- Authors
- Gao, F.-B., & Bogert, B. A.
- Venue
- Trends in Neurosciences
- Publisher
- Elsevier BV
- Published
- 2003-05
- Volume
- 26
- Issue
- 5
- Pages
- 262-268
- ISSN
- 0166-2236
- Cited by
- 32
- References
- 75
- Language
- en
- Licence
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
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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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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.
