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Related Concept Videos

Cis-regulatory Sequences02:02

Cis-regulatory Sequences

Cis-regulatory sequences are short fragments of non-coding DNA that are present on the same chromosomes as the genes that they regulate. These fragments serve as binding sites for transcriptional regulators, proteins that are responsible for controlling gene transcription and differential gene expression across cell types in eukaryotes. Cis-regulatory sequences can be close to the gene of interest or thousands of bases away in the DNA sequence; however, those sequences that are further away are...
Cis-regulatory Sequences02:02

Cis-regulatory Sequences

Cis-regulatory sequences are short fragments of non-coding DNA that are present on the same chromosomes as the genes that they regulate. These fragments serve as binding sites for transcriptional regulators, proteins that are responsible for controlling gene transcription and differential gene expression across cell types in eukaryotes. Cis-regulatory sequences can be close to the gene of interest or thousands of bases away in the DNA sequence; however, those sequences that are further away are...
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...
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...
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...
Enzyme-linked Receptors01:00

Enzyme-linked Receptors

Enzyme-linked receptors are proteins that act as both receptor and enzyme, activating multiple intracellular signals. This is a large group of receptors that include the receptor tyrosine kinase (RTK) family. Many growth factors and hormones bind to and activate the RTKs.
Neurotrophin (NT) receptors are a family of RTKs, including trkA, trkB, and trkC (tropomyosin-related kinase) receptors. TrkA is specific for nerve growth factor (NGF), neurotrophin-6, and neurotrophin-7. TrkB binds...

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Updated: May 27, 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

miREE: miRNA recognition elements ensemble.

Paula H Reyes-Herrera1, Elisa Ficarra, Andrea Acquaviva

  • 1Department of Control and Computer Engineering, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 TO, Italy. phreyes@gmail.com

BMC Bioinformatics
|November 26, 2011
PubMed
Summary
This summary is machine-generated.

We developed miREE, a novel computational tool for microRNA target prediction. It combines an Ab-Initio module and a machine learning module to improve accuracy and reduce false positives in identifying microRNA-mRNA interactions.

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Area of Science:

  • Computational Biology
  • Molecular Biology
  • Bioinformatics

Background:

  • MicroRNA (miRNA) target prediction is crucial for understanding gene regulation.
  • Current computational methods face challenges in accuracy and distinguishing true targets.

Purpose of the Study:

  • To introduce miREE, a novel ensemble tool for enhanced microRNA target prediction.
  • To improve the balance between sensitivity and specificity in miRNA target identification.

Main Methods:

  • miREE integrates an Ab-Initio module using genetic algorithms for duplex stability.
  • A Support Vector Machine (SVM) learning module assesses miRNA recognition elements.
  • The tool considers both miRNA-target structural stability and accessibility.

Main Results:

  • miREE significantly improves accuracy over existing state-of-the-art prediction tools.
  • Achieved a better balance between specificity and sensitivity across multiple species.
  • Reduced false positives through machine learning integration and representative negative record generation.

Conclusions:

  • The combined Ab-Initio and machine learning approach enhances miRNA target prediction accuracy.
  • miREE effectively balances filtering false positives with identifying true targets.
  • The miREE tool is publicly available online.