miRDB: an online resource for microRNA target prediction and functional annotations
By Nathan Wong, Xiaowei Wang. Nucleic Acids Res., 2014
1,678 citations recorded by the source corpus.
MicroRNAs (miRNAs) are small non-coding RNAs that are extensively involved in many physiological and disease processes. One major challenge in miRNA studies is the identification of genes regulated by miRNAs. To this end, we have developed an online resource, miRDB (http://mirdb.org), for miRNA target prediction and functional annotations. Here, we describe recently updated features of miRDB, including 2.1 million predicted gene targets regulated by 6709 miRNAs. In addition to presenting precompiled prediction data, a new feature is the web server interface that allows submission of user-provided sequences for miRNA target prediction. In this way, users have the flexibility to study any custom miRNAs or target genes of interest. Another major update of miRDB is related to functional miRNA annotations. Although thousands of miRNAs have been identified, many of the reported miRNAs are not likely to play active functional roles or may even have been falsely identified as miRNAs from high-throughput studies. To address this issue, we have performed combined computational analyses and literature mining, and identified 568 and 452 functional miRNAs in humans and mice, respectively. These miRNAs, as well as associated functional annotations, are presented in the FuncMir Collection in miRDB.
Subfields: Cancer Research, Molecular Biology
View Paper: https://www.semanticscholar.org/paper/feaece50ac2bfc236b96d3e8a000affe6b96f2a0
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
- Yuhao Chen
- Ana Kozomara
- Sam Griffiths-Jones
- Xiaowei Wang
- Maria Birgaoanu
- David P. Bartel
- V. Narry Kim
- Jiuyong Li
In Molecular Biology
- Yuhao Chen
- Ana Kozomara
- Sam Griffiths-Jones
- Xiaowei Wang
- Maria Birgaoanu
- David P. Bartel
- V. Narry Kim
- Thomas Tuschl
Citations in the corpus
- miRDB: an online database for prediction of functional microRNA targets (2019, methodology): “To facilitate the process of candidate target selection, we have previously developed an on-line database, miRDB, for miRNA target prediction and functional annotations (7,8).”
- miRBase: from microRNA sequences to function (2018, background): “For example, TargetScan (14), DIANA-microT (15) and miRDB (16) are amongst many resources that provide web interfaces to search and view the predicted target sites of most microRNAs.”
- mirDIP 4.1—integrative database of human microRNA target predictions (2017, neutral): “mirConnX 2011 yes yes (45) mirCoX 2013 yes yes (46) miRDB 2015 2016 yes yes yes yes (47)”
- miRTarBase 2016: updates to the experimentally validated miRNA-target interactions database (2015, background): “…repository that provides integrated interfaces for comprehensive microRNA nomenclature, sequence and annotation data. miRNA databases, such as microRNA.org (9), miRGator (10), miRDB (11) and miRNAMap (12) integrate target prediction programs to identify miRNA target-interactions (MTIs).”
- miRNet - dissecting miRNA-target interactions and functional associations through network-based visual analysis (2016, neutral): “(12), miRecords (15), SM2miR (17), Pharmaco-miR (16), miR2Disease (18), PhenomiR (19), StarBase (14), EpimiR (20), miRDB (26) and miRanda (27).”