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

Comparing sequence and expression for predicting microRNA targets using GenMiR3.

J C Huang1, B J Frey, Q D Morris

  • 1Probabilistic and Statistical Inference Group, University of Toronto, 10 King's College Rd., Toronto, ON, M5S 3G4, Canada. jim@psi.toronto.edu

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
|January 31, 2008
PubMed
Summary
This summary is machine-generated.

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

[Role of blood markers in predicting the failure of prosthesis removal and antibiotic-loaded bone cement spacer implantation for treatment of periprosthetic joint infection].

Zhonghua wai ke za zhi [Chinese journal of surgery]·2023
Same author

[Progress in the clinical research of malignant melanoma in nasal cavity and paranasal sinuses].

Zhonghua er bi yan hou tou jing wai ke za zhi = Chinese journal of otorhinolaryngology head and neck surgery·2023
Same author

[Efficacy of sacubitril/valsartan in peritoneal dialysis patients with HFpEF and its effect on residual renal function].

Zhonghua yi xue za zhi·2023
Same author

[Melanocytic eosinophilic metaplasia of nasopharyngeal mucosa: 3 cases report].

Zhonghua er bi yan hou tou jing wai ke za zhi = Chinese journal of otorhinolaryngology head and neck surgery·2022
Same author

[The urate-lowering efficacy of febuxostat and its relationship with residual renal function in peritoneal dialysis patients with hyperuricemia].

Zhonghua yi xue za zhi·2022
Same author

Nanoporous foam fabricated by dealloying AgAl thin film through supercritical fluid corrosion.

RSC advances·2022
Same journal

Trust, Reproducibility, and Progress: The Roles of Independent Blind Prediction and Assessment and Benchmarking in Computational Biology.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing·2026
Same journal

The Evolving Cyberinfrastructure at the National Institutes of Health to Support Data and AI in Biomedical Research.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing·2026
Same journal

Applications of AI & ML in Biomanufacturing of Cell and Gene Therapies.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing·2026
Same journal

AI for Health: Leveraging Artificial Intelligence to Revolutionize Healthcare.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing·2026
Same journal

Workshop Introduction: Advances of AI Methods in Single Cell Spatial Omics.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing·2026
Same journal

DRIVE-KG: Enhancing variant-phenotype association discovery in understudied complex diseases using heterogeneous knowledge graphs.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing·2026
See all related articles

We introduce GenMiR3, a model predicting microRNA (miRNA) targets by integrating mRNA sequence features with expression data. While hybridization energy is predictive, it offers minimal improvement over expression-based methods alone.

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • MicroRNAs (miRNAs) regulate gene expression post-transcriptionally.
  • Accurate prediction of miRNA-mRNA interactions is crucial for understanding gene regulation.
  • Existing models primarily rely on expression profiles, with limited integration of sequence features.

Purpose of the Study:

  • To develop and evaluate GenMiR3, a novel model for miRNA-mRNA interaction prediction.
  • To assess the utility of specific mRNA sequence features in enhancing prediction accuracy.
  • To investigate the predictive power of hybridization energy, target site conservation, and context scores.

Main Methods:

  • GenMiR3 integrates miRNA and mRNA expression profiles with sequence features.

Related Experiment Videos

  • Evaluation of three sequence features: hybridization energy, target site conservation, and context score.
  • Assessment of prediction accuracy using expression support and Gene Ontology (GO) enrichment analysis.

    • Main Results:

    • Total hybridization energy between miRNA and mRNA was found to be predictive of expression data and GO enrichment.
    • Target site conservation and context score showed limited predictive value.
    • The hybridization energy feature provided only a marginal increase in overall prediction accuracy when combined with expression features.

    Conclusions:

    • GenMiR3 offers an improved framework for miRNA target prediction by incorporating sequence information.
    • Hybridization energy is a relevant feature but does not substantially enhance predictions beyond expression-based approaches.
    • Further research may explore synergistic combinations of sequence and expression features for more robust miRNA target identification.