scholarly journals MTide: an integrated tool for the identification of miRNA-target interaction in plants

2014 ◽  
Vol 31 (2) ◽  
pp. 290-291 ◽  
Author(s):  
Z. Zhang ◽  
L. Jiang ◽  
J. Wang ◽  
P. Gu ◽  
M. Chen
Keyword(s):  
Mirna Target ◽  
Target Interaction

scholarly journals DPMIND: degradome-based plant miRNA–target interaction and network database

2017 ◽  
Vol 34 (9) ◽  
pp. 1618-1620 ◽  
Author(s):  
Yuhan Fei ◽  
Rui Wang ◽  
Haoyuan Li ◽  
Shu Liu ◽  
Hongsheng Zhang ◽  
...  
Keyword(s):  
Mirna Target ◽  
Target Interaction ◽  
Network Database ◽  
Plant Mirna

Obtaining miRNA‐Target Interaction Information from miRWalk2.0

2016 ◽  
Vol 55 (1) ◽  
Author(s):  
Alisha Parveen ◽  
Norbert Gretz ◽  
Harsh Dweep
Keyword(s):  
Mirna Target ◽  
Target Interaction ◽  
Interaction Information

Asthma MicroRNA Regulome Development Using Validated miRNA-Target Interaction Visualization

2018 ◽  
Vol 22 (9) ◽  
pp. 607-615 ◽  
Author(s):  
Simon Fekonja ◽  
Peter Korošec ◽  
Matija Rijavec ◽  
Taja Jeseničnik ◽  
Tanja Kunej
Keyword(s):  
Mirna Target ◽  
Target Interaction

scholarly journals miRTarBase 2020: updates to the experimentally validated microRNA–target interaction database

2019 ◽  
Author(s):  
Hsi-Yuan Huang ◽  
Yang-Chi-Dung Lin ◽  
Jing Li ◽  
Kai-Yao Huang ◽  
Sirjana Shrestha ◽  
...  
Keyword(s):  
Mirna Target ◽  
Target Genes ◽  
Biological Significance ◽  
Transcriptional Level ◽  
Biological Databases ◽  
Microrna Target ◽  
Mining System ◽  
Target Interaction ◽  
Interaction Database ◽  
Comprehensive Information

Abstract MicroRNAs (miRNAs) are small non-coding RNAs (typically consisting of 18–25 nucleotides) that negatively control expression of target genes at the post-transcriptional level. Owing to the biological significance of miRNAs, miRTarBase was developed to provide comprehensive information on experimentally validated miRNA–target interactions (MTIs). To date, the database has accumulated >13,404 validated MTIs from 11,021 articles from manual curations. In this update, a text-mining system was incorporated to enhance the recognition of MTI-related articles by adopting a scoring system. In addition, a variety of biological databases were integrated to provide information on the regulatory network of miRNAs and its expression in blood. Not only targets of miRNAs but also regulators of miRNAs are provided to users for investigating the up- and downstream regulations of miRNAs. Moreover, the number of MTIs with high-throughput experimental evidence increased remarkably (validated by CLIP-seq technology). In conclusion, these improvements promote the miRTarBase as one of the most comprehensively annotated and experimentally validated miRNA–target interaction databases. The updated version of miRTarBase is now available at http://miRTarBase.cuhk.edu.cn/.

WPMIAS: Whole-degradome-based Plant MicroRNA–target Interaction Analysis Server

2019 ◽  
Vol 36 (6) ◽  
pp. 1937-1939 ◽  
Author(s):  
Yuhan Fei ◽  
Yiyang Mao ◽  
Chengji Shen ◽  
Rui Wang ◽  
Hongsheng Zhang ◽  
...  
Keyword(s):  
Mirna Target ◽  
Interaction Analysis ◽  
Supplementary Information ◽  
Future Research ◽  
Microrna Target ◽  
Web Based ◽  
Target Interaction ◽  
Target Analysis ◽  
Target Mrnas ◽  
Plant Mirna

Abstract Summary A critical aspect for exploring the biological function of a microRNA (miRNA) lies on exact detection and validation of its target mRNAs. However, no convenient and efficient web-based server is available for plant biologists to identify the experimentally verified target mRNAs of miRNAs. In this work, we built a comprehensive web-based platform for miRNA–target analysis, named as Whole-degradome-based Plant MiRNA–target Interaction Analysis Server (WPMIAS), for validation of predicted interactions of miRNAs and their target mRNAs (MTIs) by user-submitted data or all available pre-loaded degradome data. Besides, the server can construct degradome-based miRNA regulatory networks (MRNs) based on the validated MTIs to help study the functions and relations among miRNAs and target mRNAs. WPMIAS is also suitable for other small RNAs (sRNAs), such as 21-nt phased siRNAs and natural antisense siRNAs, which direct cleavage of target mRNAs. Currently, WPMIAS supports 68 plant species with 189 cDNA and 271 pre-loaded plant degradome datasets. The user can identify all validated MTIs by analyzing all degradome data at a time and understand when and where MTIs take place and their cleavage levels. With the data obtained from WPMIAS, the user can build a plant miRNA–target map, where it is convenient to find interesting research ideas on miRNAs. In summary, WPMIAS is able to support a comprehensive web-based plant miRNA–target analysis and expected to greatly promote future research on plant miRNAs. Availability and implementation It can be freely accessed at https://cbi.njau.edu.cn/WPMIAS/. Supplementary information Supplementary data are available at Bioinformatics online.

Combing the Hairball: Improving Visualization of miRNA–Target Interaction Networks

2019 ◽  
pp. 279-289
Author(s):  
Francesco Russo ◽  
Jessica Xin Hu ◽  
Jose Alejandro Romero Herrera ◽  
Søren Brunak
Keyword(s):  
Mirna Target ◽  
Interaction Networks ◽  
Target Interaction

scholarly journals Prediction tools for miRNA targets: toward a better comprehension for Biologists

2019 ◽  
Author(s):  
Aurélien Quillet ◽  
Youssef Anouar ◽  
Thierry Lecroq ◽  
Christophe Dubessy
Keyword(s):  
Mirna Target ◽  
Prediction Models ◽  
Transcriptional Level ◽  
Regulate Gene Expression ◽  
Target Interaction ◽  
Prediction Tools ◽  
The Past ◽  
Lab Experiments ◽  
Wet Lab ◽  
Non Coding Rnas

MicroRNAs (miRNAs) are small non-coding RNAs which regulate gene expression at the post-transcriptional level. Because of their wide network of interactions, miRNAs became over the past decade the focus of many studies. To streamline the amount of potential wet lab experiments, the use of miRNAs targets predictions tools is nowadays the first step undertaken. However, the predictions made are very divergent from one tool to another. This is mostly due to miRNAs complex and still not fully understood mechanism of action. Such divergences bring biologists to wonder about which tool they should use to predict miRNAs targets. To address this issue, the review highlights the main characteristics of miRNA target interaction, describes prediction models currently used, and gives some insights on predictors’ performances evaluation.

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