CircNet: a database of circular RNAs derived from transcriptome sequencing data

By Yu-Chen Liu, Jianrong Li, Chuan-Hu Sun, Erik Andrews, Rou-Fang Chao, F. Lin, Shun-Long Weng, Sheng-Da Hsu, Chieh-Chen Huang, Chao Cheng and 2 more. Nucleic Acids Res., 2015

305 citations recorded by the source corpus.

Circular RNAs (circRNAs) represent a new type of regulatory noncoding RNA that only recently has been identified and cataloged. Emerging evidence indicates that circRNAs exert a new layer of post-transcriptional regulation of gene expression. In this study, we utilized transcriptome sequencing datasets to systematically identify the expression of circRNAs (including known and newly identified ones by our pipeline) in 464 RNA-seq samples, and then constructed the CircNet database (http://circnet.mbc.nctu.edu.tw/) that provides the following resources: (i) novel circRNAs, (ii) integrated miRNA-target networks, (iii) expression profiles of circRNA isoforms, (iv) genomic annotations of circRNA isoforms (e.g. 282 948 exon positions), and (v) sequences of circRNA isoforms. The CircNet database is to our knowledge the first public database that provides tissue-specific circRNA expression profiles and circRNA–miRNA-gene regulatory networks. It not only extends the most up to date catalog of circRNAs but also provides a thorough expression analysis of both previously reported and novel circRNAs. Furthermore, it generates an integrated regulatory network that illustrates the regulation between circRNAs, miRNAs and genes.

Subfields: Cancer Research, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/52690291b820d81f79bbd418de72ccf99643c09c

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Cancer Research

1. Wanying Wu
2. Peifeng Ji
3. Fangqing Zhao
4. Burton B. Yang

In Molecular Biology

1. Wanying Wu
2. Peifeng Ji
3. Fangqing Zhao
4. Burton B. Yang

Citations in the corpus

• CSCD: a database for cancer-specific circular RNAs (2017, background): “CircNet provides circRNA expression profiles across hundreds of samples and illustrates circRNA-miRNA-gene regulatory networks (25).”
• Non-coding RNAs in disease: from mechanisms to therapeutics (2023, unknown): “Over the years, high-throughput sequencing and other technologies have led to the identification of a wide range of ncRNAs of different types and sizes 13,14 .”
• The bioinformatics toolbox for circRNA discovery and analysis (2020, background): “Plant databases include PlantcircBase [105], which collects publicly available BSJ positions of circRNAs across 16 different plant organisms and provides a tool, BLASTcirc, for prediction of circRNAs from query sequences, PlantCircNet [106], which contains circRNA-miRNA-mRNA interactions, and CropCi”
• CircAtlas: an integrated resource of one million highly accurate circular RNAs from 1070 vertebrate transcriptomes (2020, methodology): “For example, the CircNet [25] utilizes only microRNA-binding site prediction for circRNA annotation.”
• Circular RNAs: Promising Biomarkers for Human Diseases (2018, background): “tw/) provides tissue-specific circRNA expression profiles as well as circRNA-miRNA-gene regulatory networks [8,9].”
• Circbank: a comprehensive database for circRNA with standard nomenclature (2019, methodology): “Several databases are available now including CircBase [30], Circ2Traits [31], CircRNADb [24] and CicrNet [32].”