Authors
Chih-Hung Chou, Sirjana Shrestha, Chi-Dung Yang, Nai-Wen Chang, Yu-Ling Lin, Kuang-Wen Liao, Wei-Chi Huang, Ting-Hsuan Sun, Siang-Jyun Tu, Wei-Hsiang Lee, Men-Yee Chiew, Chun-San Tai, Ting-Yen Wei, Tzi-Ren Tsai, Hsin-Tzu Huang, Chung-Yu Wang, Hsin-Yi Wu, Shu-Yi Ho, Pin-Rong Chen, Cheng-Hsun Chuang, Pei-Jung Hsieh, Yi-Shin Wu, Wen-Liang Chen, Meng-Ju Li, Yu-Chun Wu, Xin-Yi Huang, Fung Ling Ng, Waradee Buddhakosai, Pei-Chun Huang, Kuan-Chun Lan, Chia-Yen Huang, Shun-Long Weng, Yeong-Nan Cheng, Chao Liang, Wen-Lian Hsu, Hsien-Da Huang
Publication date
2018/1/4
Journal
Nucleic acids research
Volume
46
Issue
D1
Pages
D296-D302
Publisher
Oxford University Press
Description
MicroRNAs (miRNAs) are small non-coding RNAs of ∼ 22 nucleotides that are involved in negative regulation of mRNA at the post-transcriptional level. Previously, we developed miRTarBase which provides information about experimentally validated miRNA-target interactions (MTIs). Here, we describe an updated database containing 422 517 curated MTIs from 4076 miRNAs and 23 054 target genes collected from over 8500 articles. The number of MTIs curated by strong evidence has increased ∼1.4-fold since the last update in 2016. In this updated version, target sites validated by reporter assay that are available in the literature can be downloaded. The target site sequence can extract new features for analysis via a machine learning approach which can help to evaluate the performance of miRNA-target prediction tools. Furthermore, different ways of browsing enhance user browsing specific MTIs. With …
Scholar articles
CH Chou, S Shrestha, CD Yang, NW Chang, YL Lin… - Nucleic acids research, 2018