Evidence map›Paper›PMID 25583365›Full record

ArticleGenome biology2015

CIRI: an efficient and unbiased algorithm for de novo circular RNA identification.

Yuan Gao, Jinfeng Wang, Fangqing Zhao

Abstract read
In one paragraph

Article in Genome biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 663 papers.

0numbers the graph read from it
0cells of the map it votes in
663citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

663 citing papers in PubMed.

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  15. HnRNP C binding to invertedScience advances · 2026
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603 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Yuan GaoComputational Genomics Lab, Beijing Institutes of Life Science, Chinese Academy of Sciences, Beijing, 100101, China. gaoyuan06@mails.ucas.ac.cn.
Jinfeng WangComputational Genomics Lab, Beijing Institutes of Life Science, Chinese Academy of Sciences, Beijing, 100101, China. wangjf@mail.biols.ac.cn.
Fangqing ZhaoComputational Genomics Lab, Beijing Institutes of Life Science, Chinese Academy of Sciences, Beijing, 100101, China. zhfq@mail.biols.ac.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recent studies reveal that circular RNAs (circRNAs) are a novel class of abundant, stable and ubiquitous noncoding RNA molecules in animals. Comprehensive detection of circRNAs from high-throughput transcriptome data is an initial and crucial step to study their biogenesis and function. Here, we present a novel chiastic clipping signal-based algorithm, CIRI, to unbiasedly and accurately detect circRNAs from transcriptome data by employing multiple filtration strategies. By applying CIRI to ENCODE RNA-seq data, we for the first time identify and experimentally validate the prevalence of intronic/intergenic circRNAs as well as fragments specific to them in the human transcriptome.

Indexed as

AlgorithmsBase SequenceComputer SimulationDatabases, Nucleic AcidExonsExoribonucleasesGene Expression RegulationHEK293 CellsHeLa CellsHumansIntronsMolecular Sequence DataReproducibility of ResultsRNARNA, CircularSequence Analysis, RNAExoribonucleasesribonuclease RRNARNA, Circular

Identifiers

PMID25583365
PMCPMC4316645

What OpenQuestion holds

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Registered trials

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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.