ArticleFrontiers in bioengineering and biotechnology2015
Knowledge in the Investigation of A-to-I RNA Editing Signals.
Article in Frontiers in bioengineering and biotechnology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 18 citations in OpenAlex.
- Computational Analysis of MDR1 Variants Predicts Effect on Cancer Cells via their Effect on mRNA Folding.PLoS computational biology · 2024Article
- Recommendations for detection, validation, and evaluation of RNA editing events in cardiovascular and neurological/neurodegenerative diseases.Molecular therapy. Nucleic acids · 2024Review
- Benchmarking RNA Editing Detection Tools.Biotech (Basel (Switzerland)) · 2023Review
- Antennal Transcriptome of the Fruit-Sucking MothGenes · 2022Article
- RDDSVM: accurate prediction of A-to-I RNA editing sites from sequence using support vector machines.Functional & integrative genomics · 2021Article
- Article
- MiREDiBase, a manually curated database of validated and putative editing events in microRNAs.Scientific data · 2021Article
- Investigating RNA editing in deep transcriptome datasets with REDItools and REDIportal.Nature protocols · 2020Article
- A-to-I RNA Editing in Cancer: From Evaluating the Editing Level to Exploring the Editing Effects.Frontiers in oncology · 2020Review
- Single-nucleotide variants in human RNA: RNA editing and beyond.Briefings in functional genomics · 2019Review
- microRNA editing in seed region aligns with cellular changes in hypoxic conditions.Nucleic acids research · 2016Article
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
RNA editing is a post-transcriptional alteration of RNA sequences that is able to affect protein structure as well as RNA and protein expression. Adenosine-to-inosine (A-to-I) RNA editing is the most frequent and common post-transcriptional modification in human, where adenosine (A) deamination produces its conversion into inosine (I), which in turn is interpreted by the translation and splicing machineries as guanosine (G). The disruption of the editing machinery has been associated to various human diseases such as cancer or neurodegenerative diseases. This biological phenomenon is catalyzed by members of the adenosine deaminase acting on RNA (ADAR) family of enzymes and occurs on dsRNA structures. Despite the enormous efforts made in the last decade, the real biological function underlying such a phenomenon, as well as ADAR's substrate features still remain unknown. In this work, we summarize the major computational aspects of predicting and understanding RNA editing events. We also investigate the detection of short motif sequences potentially characterizing RNA editing signals and the use of a logistic regression technique to model a predictor of RNA editing events. The latter, named AIRlINER, an algorithmic approach to assessment of A-to-I RNA editing sites in non-repetitive regions, is available as a web app at: http://alpha.dmi.unict.it/airliner/. Results and comparisons with the existing methods encourage our findings on both aspects.
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