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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...

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Related Experiment Video

Updated: Jun 27, 2026

Describing a Transcription Factor Dependent Regulation of the MicroRNA Transcriptome

Describing a Transcription Factor Dependent Regulation of the MicroRNA Transcriptome

Published on: June 15, 2016

Finding microRNA regulatory modules in human genome using rule induction.

Dang Hung Tran¹, Kenji Satou, Tu Bao Ho

¹School of Knowledge Science, Japan Advanced Institute of Science and Technology, 1-1 Asahidai, Nomi, Ishikawa 923-1292, Japan. hungtd@jaist.ac.jp

BMC Bioinformatics

|December 19, 2008

Summary

We developed a new method to identify miRNA regulatory modules (MRMs), which are groups of microRNAs (miRNAs) and target genes working together. This approach reveals functional gene relationships and potential roles in cancer.

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Last Updated: Jun 27, 2026

Describing a Transcription Factor Dependent Regulation of the MicroRNA Transcriptome

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Published on: June 15, 2016

Genome-wide Screen for miRNA Targets Using the MISSION Target ID Library

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mirMachine: A One-Stop Shop for Plant miRNA Annotation

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Area of Science:

Genomics
Molecular Biology
Bioinformatics

Background:

MicroRNAs (miRNAs) are small non-coding RNAs regulating gene expression.
Understanding miRNA regulatory mechanisms is crucial for complex cellular systems.
Identifying functional modules of miRNAs and target genes is essential.

Purpose of the Study:

To develop a method for identifying miRNA regulatory modules (MRMs).
To understand the cooperative roles of miRNAs and target genes in gene regulation.

Main Methods:

A rule-based learning approach was employed.
Integrated miRNA-target binding, gene expression, and miRNA expression data.
Applied to human genes and miRNAs.

Main Results:

Identified 79 miRNA regulatory modules (MRMs).
MRMs show correlated expression patterns for miRNAs and mRNAs.
mRNAs within modules share similar biological functions.

Conclusions:

The method effectively detects functionality-related genes.
MRMs highlight cooperative gene regulation by miRNAs.
miRNAs within identified modules are implicated in human cancers.