Jove
Visualize
Contact Us
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 Videos

Genetic algorithm learning as a robust approach to RNA editing site prediction.

James Thompson1, Shuba Gopal

  • 1Department of Biological Sciences, Rochester Institute of Technology, Rochester, NY 14623, USA. tex@u.washington.edu

BMC Bioinformatics
|March 18, 2006
PubMed
Summary

A new computational method, REGAL (RNA Editing site prediction by Genetic Algorithm Learning), accurately identifies C --> U RNA editing sites. This machine learning approach offers a robust and generalizable tool for discovering novel editing sites in genomic sequences.

Related Concept Videos

You might also read

Related Articles

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

Sort by
Same author

School zone speed compliance in the ACT, Australia: Risks, findings and recommendations for improved safety.

Journal of safety research·2026
Same author

Effect of [<sup>68</sup>Ga]Ga-PSMA-11 PET-CT in the diagnosis of prostate cancer in men with equivocal or clinically high-risk non-suspicious findings on multiparametric MRI (PRIMARY2): a multicentre, non-inferiority, phase 3, randomised controlled trial.

The Lancet. Oncology·2026
Same author

Tubule and microbranch variations in human dentine: A quantitative 3D study with serial block-face scanning electron microscopy.

Journal of microscopy·2026
Same author

An AI system to help scientists write expert-level empirical software.

Nature·2026
Same author

Prospective Comparison of <sup>64</sup>Copper [<sup>64</sup>Cu]SAR-bisPSMA vs <sup>68</sup>Gallium[<sup>68</sup>Ga] PSMA-11 PET/CT for Biochemical Recurrence of Prostate Cancer Following Radical Prostatectomy (Co-PSMA Trial).

European urology·2026
Same author

Characteristics of Patients and Factors Associated With the Development of Hepatitis C Virus-Associated Hepatocellular Carcinoma in an Urban, Primary-Care Based Hepatitis C Clinic.

Journal of viral hepatitis·2026

Area of Science:

  • Genomics
  • Bioinformatics
  • Molecular Biology

Background:

  • RNA editing, a post-transcriptional modification, contributes to organismal complexity.
  • C --> U editing is a widespread but often serendipitously discovered form of RNA modification.
  • Computational analysis offers a rapid method for identifying novel C --> U RNA editing sites.

Purpose of the Study:

  • To develop a robust and generalizable computational method for identifying C --> U RNA editing sites.
  • To evaluate the method's performance on plant mitochondrial genomes.

Main Methods:

  • A machine learning approach utilizing a genetic algorithm.
  • Development of REGAL (RNA Editing site prediction by Genetic Algorithm Learning).

Related Experiment Videos

Main Results:

  • REGAL achieved 87% accuracy, 82% sensitivity, and 91% specificity on three mitochondrial genomes.
  • REGAL outperformed other ab initio prediction methods.
  • REGAL demonstrated comparable sensitivity and higher specificity than homology-based approaches, without requiring sequence conservation.

Conclusions:

  • Ab initio methods, particularly genetic algorithms, can generate robust classifiers for putative RNA editing sites.
  • REGAL is a promising tool for identifying C --> U RNA editing sites.
  • The REGAL approach has the potential for generalization to other organisms with C --> U RNA editing.