Table 2. Databases used for circRNAs detection in cancers tissues and cells.

Databases	De novo?	Characteristics	URL	Refs
CircNet	No	Tissue-specific circRNA expression profiles; Integrated CiRNA-miRNA -mRNA networks.	http://circnet.mbc.nctu.edu.tw/	[29]
CIRCexplorer	No	Depending on the mapping strategy of aligners; CircRNAs annotation only.	http://yanglab.github.io/CIRCexplorer/	[41]
UROBORUS	No	Total RNA-seq data with no poly(A) depletion or RNase R treatment; Detecting lower expressed circRNAs; Lower false positive rate.	http://uroborus.openbioinformatics.org/en/latest/	[46]
Acfs	Yes	Quantification and fast; Highest F1 accuracy; Lowest false discovery rate; Identify fusion circRNAs.	https://github.com/arthuryxt/acfs	[87]
Circ-Seq	No	Genomic annotation; Fully automated; Running in a multi-threaded cluster.	http://bioinformaticstools.mayo.edu/research/circ-seq/	[102]
circBase	No	Downloading freely the merged and unified data sets of circRNAs	http://www.circbase.org/	[103]
Circ2Traits	No	A disease-circRNA association database Identifying diseases associated SNPs on circRNAs loci	http://gyanxet-beta.com/circdb/	[104]
starBase v2.0	No	Providing comprehensive circRNA–miRNA-mRNA and protein–circRNA interaction networks	http://starbase.sysu.edu.cn/	[105]