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Long Noncoding RNAs: Emerging Stars in Gene Regulation, Epigenetics and Human Disease
Abstract
Noncoding RNAs (ncRNAs) are classes of transcripts that are encoded by the genome and transcribed but never get translated into proteins. Though not translated into proteins, ncRNAs play pivotal roles in a variety of cellular functions. Here, we review the functions of long noncoding RNAs (lncRNAs) and their implications in various human diseases. Increasing numbers of studies demonstrate that lncRNAs play critical roles in regulation of protein‐coding genes, maintenance of genomic integrity, dosage compensation, genomic imprinting, mRNA processing, cell differentiation, and development. Misregulation of lncRNAs is associated with a variety of human diseases, including cancer, immune and neurological disorders. Different classes of lncRNAs, their functions, mechanisms of action, and associations with different human diseases are summarized in detail, highlighting their as yet untapped potential in therapy.
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Metadata
- Authors
- Bhan, A., & Mandal, S. S.
- Venue
- ChemMedChem
- Publisher
- Wiley
- Published
- 2014-03-26
- Volume
- 9
- Issue
- 9
- Pages
- 1932-1956
- ISSN
- 1860-7179 (ISSN-L)
- 1860-7187
- OpenAlex
- W2067337865
- Cited by
- 279
- References
- 265
- FWCI
- 6.22
- 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.
What counts as a claim ›How we measure confidence ›How we check this ›
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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.