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

A dynamic programming algorithm for RNA structure prediction including pseudoknots

E Rivas1, S R Eddy

  • 1Department of Genetics, Washington University, St. Louis, MO, 63110, USA.

Journal of Molecular Biology
|February 2, 1999
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

Redefining periodic paralysis with CACNA1S mutation in a Spanish cohort.

Neurologia·2025
Same author

Estimating the air quality standard exceedance areas and the spatial representativeness of urban air quality stations applying microscale modelling.

The Science of the total environment·2025
Same author

How do meteorological conditions impact the effectiveness of various traffic measures on NO<sub>x</sub> concentrations in a real hot-spot?

The Science of the total environment·2024
Same author

Rationale and study design for an Individualized PeriopeRative Open lung VEntilatory approach in Emergency Abdominal Laparotomy/scopy: study protocol for a prospective international randomized controlled trial.

Revista espanola de anestesiologia y reanimacion·2024
Same author

Using dispersion models at microscale to assess long-term air pollution in urban hot spots: A FAIRMODE joint intercomparison exercise for a case study in Antwerp.

The Science of the total environment·2024
Same author

Impact of single and combined local air pollution mitigation measures in an urban environment.

The Science of the total environment·2024
Same journal

UPF3A and UPF3B shape the transcriptome cooperatively yet oppose cell function.

Journal of molecular biology·2026
Same journal

Antibody-secreting cells integrate efficient NMD with non‑canonical UPR signaling to maintain proteostasis and support massive immunoglobulin synthesis.

Journal of molecular biology·2026
Same journal

Small molecule stabilization of diverse amyloidogenic immunoglobulin light chains revealed by hydrogen-deuterium exchange mass spectrometry.

Journal of molecular biology·2026
Same journal

UPF1 at Work: Structural and Mechanistic Insights Into a Master Regulator of Nonsense-Mediated mRNA Decay.

Journal of molecular biology·2026
Same journal

Structural basis for the pro-amyloidogenic action and ligand binding of a novel W72R variant of human apolipoprotein A-I.

Journal of molecular biology·2026
Same journal

Cryo-EM Structure of the C. Elegans Septin Tetramer Reveals a Revised Architecture and Conserved Positional Orthology.

Journal of molecular biology·2026
See all related articles

This study introduces a novel dynamic programming algorithm for predicting optimal RNA secondary structures, including complex pseudoknots, using a thermodynamic model. The algorithm, though computationally intensive, represents a significant advancement in RNA folding prediction.

Area of Science:

  • Computational Biology
  • Bioinformatics
  • Molecular Biology

Background:

  • Predicting RNA secondary structure is crucial for understanding RNA function.
  • Existing algorithms often struggle with pseudoknots, which are important structural motifs.
  • Accurate thermodynamic modeling is essential for reliable structure prediction.

Purpose of the Study:

  • To develop a dynamic programming algorithm for predicting optimal RNA secondary structure, including pseudoknots.
  • To implement and demonstrate the algorithm's capability using a standard thermodynamic model.
  • To address the limitations of current RNA folding prediction methods.

Main Methods:

  • Developed a dynamic programming algorithm with O(N^6) time and O(N^4) storage complexity.

Related Experiment Videos

  • Utilized Feynman diagrams for a clearer representation of the complex algorithm.
  • Integrated standard RNA folding thermodynamic parameters with novel pseudoknot stability parameters.

    • Main Results:

    • Successfully implemented an algorithm to generate optimal minimum energy structures for single RNA sequences.
    • Demonstrated the algorithm's effectiveness on small pseudoknotted and non-pseudoknotted RNA examples.
    • The algorithm accurately predicts structures incorporating pseudoknots within the accepted thermodynamic model.

    Conclusions:

    • This work presents the first algorithm capable of folding optimal (minimum energy) pseudoknotted RNAs using the accepted thermodynamic model.
    • Despite high computational demands, the algorithm offers a powerful new tool for RNA structure prediction.
    • The graphical representation aids in understanding complex RNA folding algorithms.