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Related Concept Videos

RNA-seq03:21

RNA-seq

RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases. 
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while microarray-based...
MicroRNAs01:22

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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Related Experiment Video

Updated: May 16, 2026

mirMachine: A One-Stop Shop for Plant miRNA Annotation
06:16

mirMachine: A One-Stop Shop for Plant miRNA Annotation

Published on: May 1, 2021

miRDeep*: an integrated application tool for miRNA identification from RNA sequencing data.

Jiyuan An1, John Lai, Melanie L Lehman

  • 1Australian Prostate Cancer Research Centre-Queensland, Institute of Health and Biomedical Innovation (IHBI), Queensland University of Technology, Princess Alexandra Hospital, Level 1, Building 1, Ipswich Road, Brisbane, Queensland, QLD 4102, Australia. j.an@qut.edu.au

Nucleic Acids Research
|December 11, 2012
PubMed
Summary

miRDeep* is a new tool that precisely identifies novel microRNAs (miRNAs) from small RNA sequencing data. It offers improved precursor miRNA detection and outperforms existing prediction tools.

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Last Updated: May 16, 2026

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MicroRNA Amplification and Recognition through Locked-nucleic-acid In situ Hybridization as a Novel Detection and Quantification Method

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Area of Science:

  • Bioinformatics
  • Genomics
  • Molecular Biology

Background:

  • MicroRNAs (miRNAs) are crucial regulatory molecules.
  • Accurate quantification and identification of known and novel miRNAs from small RNA sequencing (RNAseq) data are essential.
  • Existing tools like miRDeep have limitations in detecting novel miRNAs.

Purpose of the Study:

  • To introduce miRDeep*, an enhanced miRNA identification tool.
  • To improve the precision of novel miRNA detection using new strategies for precursor miRNA identification.
  • To provide a user-friendly, integrated application for miRNA analysis.

Main Methods:

  • miRDeep* models miRDeep but incorporates novel strategies for precursor miRNA identification.
  • The tool accepts raw sequencing data in FastQ, SAM, or BAM formats.
  • It features a graphical interface displaying miRNA expression, pre-miRNA hairpin structures, read locations, and predicted target genes using the TargetScan algorithm.

Main Results:

  • miRDeep* demonstrated improved precision in identifying novel precursor miRNAs.
  • The application provides a comprehensive display of miRNA expression and structural information.
  • miRDeep* outperformed existing miRNA prediction tools on LNCaP and other small RNAseq datasets.

Conclusions:

  • miRDeep* is an effective and user-friendly integrated tool for miRNA identification and analysis.
  • The tool offers enhanced precision for novel miRNA discovery.
  • miRDeep* is a valuable resource for researchers working with small RNA sequencing data.