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

Open access
Gao, Yuan, Wang, Jinfeng, Zhao, Fangqing·2015·Genome Biology

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.

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Metadata

Authors
Gao, Y., Wang, J., & Zhao, F.
Venue
Genome Biology
Published
2015-01-13
Volume
16
Issue
1
Pages
4-4
ISSN
1465-6906 (ISSN-L)
OpenAlex
W2147625377
Cited by
1,112
References
31
FWCI
24.57
Type
journal article
Language
en
Open access
gold

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CoChat. (2026). Citation check: CIRI: an efficient and unbiased algorithm for de novo circular RNA identification. https://app.cochat.ai/papers/10.1186/s13059-014-0571-3
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Gao, Y., Wang, J., & Zhao, F. (2015). CIRI: an efficient and unbiased algorithm for de novo circular RNA identification. Genome Biology. https://doi.org/10.1186/s13059-014-0571-3

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