Jove
Visualize
Contact Us

Related Concept Videos

MicroRNAs01:22

MicroRNAs

3.1K
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...
3.1K
MicroRNAs01:22

MicroRNAs

21.2K
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...
21.2K
MicroRNAs01:22

MicroRNAs

9.8K
9.8K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

De Novo Sequencing of Peptides from Tandem Mass Spectra and Applications in Proteogenomics.

Methods in molecular biology (Clifton, N.J.)·2024
Same author

Comprehensive Peptide Mapping Is Crucial for Proteogenomics and Proteomics.

Methods in molecular biology (Clifton, N.J.)·2024
Same author

The Role of MicroRNAs in HIV Infection.

Genes·2024
Same author

Deep learning in bioinformatics.

Turkish journal of biology = Turk biyoloji dergisi·2024
Same author

Alternative polyadenylation and dynamic 3' UTR length is associated with polysome recruitment throughout the cardiomyogenic differentiation of hESCs.

Frontiers in molecular biosciences·2024
Same author

PriPath: identifying dysregulated pathways from differential gene expression via grouping, scoring, and modeling with an embedded feature selection approach.

BMC bioinformatics·2023
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Video

Updated: May 5, 2026

MicroRNA Amplification and Recognition through Locked-nucleic-acid In situ Hybridization as a Novel Detection and Quantification Method
09:06

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

Published on: October 7, 2025

560

Computational and bioinformatics methods for microRNA gene prediction.

Jens Allmer1

  • 1Molecular Biology and Genetics, Izmir Institute of Technology, Izmir, Turkey.

Methods in Molecular Biology (Clifton, N.J.)
|November 26, 2013
PubMed
Summary

Computational methods predict microRNAs (miRNAs) due to experimental challenges. This chapter reviews RNA secondary structure prediction, homology, and ab initio miRNA prediction techniques.

More Related Videos

A Bioinformatics Pipeline to Accurately and Efficiently Analyze the MicroRNA Transcriptomes in Plants
06:34

A Bioinformatics Pipeline to Accurately and Efficiently Analyze the MicroRNA Transcriptomes in Plants

Published on: January 21, 2020

7.7K
Biotin-based Pulldown Assay to Validate mRNA Targets of Cellular miRNAs
11:00

Biotin-based Pulldown Assay to Validate mRNA Targets of Cellular miRNAs

Published on: June 12, 2018

13.5K

Related Experiment Videos

Last Updated: May 5, 2026

MicroRNA Amplification and Recognition through Locked-nucleic-acid In situ Hybridization as a Novel Detection and Quantification Method
09:06

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

Published on: October 7, 2025

560
A Bioinformatics Pipeline to Accurately and Efficiently Analyze the MicroRNA Transcriptomes in Plants
06:34

A Bioinformatics Pipeline to Accurately and Efficiently Analyze the MicroRNA Transcriptomes in Plants

Published on: January 21, 2020

7.7K
Biotin-based Pulldown Assay to Validate mRNA Targets of Cellular miRNAs
11:00

Biotin-based Pulldown Assay to Validate mRNA Targets of Cellular miRNAs

Published on: June 12, 2018

13.5K

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • MicroRNAs (miRNAs) are of significant research interest.
  • Experimental determination of miRNAs is complex.
  • Computational miRNA prediction methods are increasingly popular.

Purpose of the Study:

  • To review computational methods for microRNA (miRNA) prediction.
  • To introduce RNA secondary structure prediction as a basis for miRNA identification.
  • To assess homology and ab initio prediction approaches.

Main Methods:

  • Categorization of prediction methods into ab initio (sequence-based) and phylogenetically conserved approaches.
  • Emphasis on hairpin/stem-loop structures and RNA secondary structure prediction.
  • Discussion of machine learning, particularly classification, for miRNA prediction.

Main Results:

  • Acknowledges the difficulty in obtaining true negative examples for training machine learning classifiers.
  • Highlights the challenge in accurately assessing algorithm performance due to limited true negatives.
  • Reviews RNA secondary structure prediction, homology assessment, and ab initio prediction methods.

Conclusions:

  • Computational methods are essential for microRNA (miRNA) discovery.
  • Accurate assessment of prediction algorithms is hindered by the lack of definitive negative datasets.
  • Understanding RNA secondary structure and homology is crucial for effective miRNA prediction.