CircNet 2.0: an updated database for exploring circular RNA regulatory networks in cancers. Issue Volume 50:Issue D1(2022) (26th November 2021)

• Record Type: Journal Article
• Authors: Chen, Yigang; Yao, Lantian; Tang, Yun; Jhong, Jhih-Hua; Wan, Jingting; Chang, Jingyue; Cui, Shidong; Luo, Yijun; Cai, Xiaoxuan; Li, Wenshuo; Chen, Qi; Huang, Hsi-Yuan; Wang, Zhuo; Chen, Weiming; Chang, Tzu-Hao; Wei, Fengxiang; Lee, Tzong-Yi; Huang, Hsien-Da
• Is Part Of: Nucleic acids research. Volume 50:Issue D1(2022)
• Page Start: D93
• Page End: D101
• Publication Date: 2021-11-26
• Subjects: Nucleic acids -- Periodicals; Molecular biology -- Periodicals; 572.805
• DOI: 10.1093/nar/gkab1036
• Languages: English
• ISSNs: 0305-1048

Abstract

Abstract: Circular RNAs (circRNAs), which are single-stranded RNA molecules that have individually formed into a covalently closed continuous loop, act as sponges of microRNAs to regulate transcription and translation. CircRNAs are important molecules in the field of cancer diagnosis, as growing evidence suggests that they are closely related to pathological cancer features. Therefore, they have high potential for clinical use as novel cancer biomarkers. In this article, we present our updates to CircNet (version 2.0), into which circRNAs from circAtlas and MiOncoCirc, and novel circRNAs from The Cancer Genome Atlas database have been integrated. In total, 2732 samples from 37 types of cancers were integrated into CircNet 2.0 and analyzed using several of the most reliable circRNA detection algorithms. Furthermore, target miRNAs were predicted from the full-length circRNA sequence using three reliable tools (PITA, miRanda and TargetScan). Additionally, 384 897 experimentally verified miRNA–target interactions from miRTarBase were integrated into our database to facilitate the construction of high-quality circRNA–miRNA–gene regulatory networks. These improvements, along with the user-friendly interactive web interface for data presentation, search, and visualization, showcase the updated CircNet database as a powerful, experimentally validated resource, for providing strong data support in the biomedical fields. CircNet 2.0 is currently accessible at https://awi.cuhk.edu.cn/∼CircNet .