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MicroRNAs

MicroRNAs

MicroRNA (miRNA) are short, regulatory RNA transcribed from introns—non-coding regions of a gene—or intergenic regions—stretches of DNA present between genes. Several processing steps are required to form biologically active, mature miRNA. The initial transcript, called primary miRNA (pri-mRNA), base-pairs with itself forming a stem-loop structure. Within the nucleus, an endonuclease enzyme, called Drosha, shortens the stem-loop structure into hairpin-shaped pre-miRNA. After the pre-miRNA ends...

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Updated: May 11, 2026

mirMachine: A One-Stop Shop for Plant miRNA Annotation

mirMachine: A One-Stop Shop for Plant miRNA Annotation

Published on: May 1, 2021

DIANA-microT web server v5.0: service integration into miRNA functional analysis workflows.

Maria D Paraskevopoulou¹, Georgios Georgakilas, Nikos Kostoulas

¹DIANA-Lab, Biomedical Sciences Research Center Alexander Fleming, 16672 Vari, Greece. paraskevopoulou@fleming.gr

Nucleic Acids Research

|May 18, 2013

Summary

The DIANA-microT web server v5.0 offers enhanced microRNA target prediction and functional analysis. This updated tool provides sophisticated workflows for researchers, improving the understanding of gene regulation.

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Last Updated: May 11, 2026

mirMachine: A One-Stop Shop for Plant miRNA Annotation

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Published on: May 1, 2021

CRISPR Gene Editing Tool for MicroRNA Cluster Network Analysis

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Published on: April 25, 2022

Area of Science:

Bioinformatics
Genomics
Molecular Biology

Background:

MicroRNAs (miRNAs) are key regulators of gene expression impacting numerous biological processes.
The DIANA-microT web server has been a valuable resource for miRNA target prediction and analysis since 2009.

Purpose of the Study:

To introduce DIANA-microT v5.0, an enhanced version of the microRNA target prediction and functional analysis web server.
To highlight the improved prediction algorithm (DIANA-microT-CDS) and updated databases (miRBase v18, Ensembl v69).
To showcase new sophisticated workflows for advanced, multi-step miRNA functional analyses accessible via a redesigned web interface.

Main Methods:

Implementation of the DIANA-microT-CDS algorithm for improved miRNA target prediction.
Integration of updated miRBase (v18) and Ensembl (v69) databases.
Development of a redesigned web server featuring sophisticated, user-friendly workflows for functional analysis.
Integration with Taverna Workflow Management System (WMS) via a dedicated plug-in.

Main Results:

Prediction of over 11 million miRNA-gene interactions across four species (Homo sapiens, Mus musculus, Drosophila melanogaster, Caenorhabditis elegans).
A completely redesigned web server offering advanced, multi-step functional miRNA analyses through an intuitive interface.
Availability of integrated pipelines for target prediction, meta-analysis, and pathway enrichment.
Seamless integration with Taverna WMS for constructing high-throughput analysis pipelines.

Conclusions:

DIANA-microT v5.0 significantly advances miRNA target prediction and functional analysis capabilities.
The enhanced web server and new workflows empower researchers, even those without extensive bioinformatics infrastructure, to conduct complex miRNA studies.
The integration with Taverna WMS facilitates the creation of sophisticated, high-throughput miRNA analysis pipelines.