ArticleBMC medical genomics2015
RCARE: RNA Sequence Comparison and Annotation for RNA Editing.
Article in BMC medical genomics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
8 citing papers in PubMed, 21 citations in OpenAlex.
- RESIC: A Tool for Comprehensive Adenosine to Inosine RNA Editing Site Identification and Classification.Frontiers in genetics · 2021Article
- Transcriptional frameshifts contribute to protein allergenicity.The Journal of clinical investigation · 2020Article
- Systematic Nucleotide Exchange Analysis of ESTs From the Human Cancer Genome Project Report: Origins of 347 Unknown ESTs Indicate Putative Transcription of Non-Coding Genomic Regions.Frontiers in genetics · 2020Article
- A-to-I RNA Editing in Cancer: From Evaluating the Editing Level to Exploring the Editing Effects.Frontiers in oncology · 2020Review
- Article
- Genome-wide analysis of differential RNA editing in epilepsy.Genome research · 2017Article
- RED: A Java-MySQL Software for Identifying and Visualizing RNA Editing Sites Using Rule-Based and Statistical Filters.PloS one · 2016Article
- Connecting the dots in translational bioinformatics: TBC 2014 collection.BMC medical genomics · 2015Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The post-transcriptional sequence modification of transcripts through RNA editing is an important mechanism for regulating protein function and is associated with human disease phenotypes. The identification of RNA editing or RNA-DNA difference (RDD) sites is a fundamental step in the study of RNA editing. However, a substantial number of false-positive RDD sites have been identified recently. A major challenge in identifying RDD sites is to distinguish between the true RNA editing sites and the false positives. Furthermore, determining the location of condition-specific RDD sites and elucidating their functional roles will help toward understanding various biological phenomena that are mediated by RNA editing. The present study developed RNA-sequence comparison and annotation for RNA editing (RCARE) for searching, annotating, and visualizing RDD sites using thousands of previously known editing sites, which can be used for comparative analyses between multiple samples. RCARE also provides evidence for improving the reliability of identified RDD sites. RCARE is a web-based comparison, annotation, and visualization tool, which provides rich biological annotations and useful summary plots. The developers of previous tools that identify or annotate RNA-editing sites seldom mention the reliability of their respective tools. In order to address the issue, RCARE utilizes a number of scientific publications and databases to find specific documentations respective to a particular RNA-editing site, which generates evidence levels to convey the reliability of RCARE. Sequence-based alignment files can be converted into VCF files using a Python script and uploaded to the RCARE server for further analysis. RCARE is available for free at http://www.snubi.org/software/rcare/.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.