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Regulation of mammalian cell differentiation by long non‐coding RNAs
Open accessAbstract
Differentiation of specialized cell types from stem and progenitor cells is tightly regulated at several levels, both during development and during somatic tissue homeostasis. Many long non‐coding RNAs have been recognized as an additional layer of regulation in the specification of cellular identities; these non‐coding species can modulate gene‐expression programmes in various biological contexts through diverse mechanisms at the transcriptional, translational or messenger RNA stability levels. Here, we summarize findings that implicate long non‐coding RNAs in the control of mammalian cell differentiation. We focus on several representative differentiation systems and discuss how specific long non‐coding RNAs contribute to the regulation of mammalian development.
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Metadata
- Authors
- Hu, W., Alvarez‐Dominguez, J. R., & Lodish, H. F.
- Venue
- EMBO reports
- Published
- 2012-10-16
- Volume
- 13
- Issue
- 11
- Pages
- 971-983
- ISSN
- 1469-221X (ISSN-L)
- 1469-3178
- OpenAlex
- W2095739285
- Cited by
- 309
- References
- 120
- FWCI
- 8.77
- Type
- journal article
- Language
- en
- Open access
- bronze
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.