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

Efficient pairwise RNA structure prediction and alignment using sequence alignment constraints.

Robin D Dowell1, Sean R Eddy

  • 1Howard Hughes Medical Institute and Department of Genetics, Washington University School of Medicine, 4444 Forest Park Blvd, Box 8510, St. Louis, MO 63108, USA. rdd@mit.edu

BMC Bioinformatics
|September 6, 2006
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

Improving calls of differentially transcribed enhancers and their upstream regulators.

Bioinformatics advances·2026
Same author

Cross-assay RNA modeling reveals cancer biomarkers.

bioRxiv : the preprint server for biology·2026
Same author

HMMER web server: 2026 update.

Nucleic acids research·2026
Same author

Improving confidence of differential transcription calls in enhancers.

bioRxiv : the preprint server for biology·2026
Same author

Base Composition Influences the Position and Precision of RNA Polymerase II Disassociation in Basal and Perturbed Conditions.

bioRxiv : the preprint server for biology·2026
Same author

Uncovering genetic interactions in the DNA repair network in response to endogenous damage and ionizing radiation.

Cell reports·2026
Same journal

OpenIMC: an open-source platform for analyzing single-cell and spatial proteomics by imaging mass cytometry.

BMC bioinformatics·2026
Same journal

NAP: an open source pipeline for cross-domain microbiome profiling using Nanopore sequencing-derived amplicon data.

BMC bioinformatics·2026
Same journal

SurvGME: an R package for survival analysis with graphical and measurement error models.

BMC bioinformatics·2026
Same journal

SimMapNet: a Bayesian framework for gene regulatory network inference using gene ontology similarities as external hint.

BMC bioinformatics·2026
Same journal

Dual channel drug-drug interactions extraction based on cross attention.

BMC bioinformatics·2026
Same journal

FeSseqdb: a curated sequence-level database and interpretable machine learning framework for identifying iron-sulfur proteins.

BMC bioinformatics·2026
See all related articles

Predicting RNA secondary structure is improved using pairwise structural alignment. This method incorporates comparative sequence data into RNA folding models, enhancing accuracy and efficiency for homologous RNA sets.

Area of Science:

  • Computational Biology
  • Bioinformatics
  • Molecular Biology

Background:

  • RNA secondary structure prediction is crucial for understanding RNA function.
  • Existing methods often struggle with small homologous RNA sets.
  • The Sankoff algorithm provides a foundation for simultaneous RNA folding and alignment.

Purpose of the Study:

  • To develop an improved RNA secondary structure prediction method for homologous sequences.
  • To address challenges in scoring and computational complexity within RNA folding algorithms.

Main Methods:

  • Utilized pair stochastic context-free grammars (pairSCFGs) for unified alignment and folding scores.
  • Developed a constrained pairSCFG structural alignment algorithm using 'pins' (known aligned positions).

Related Experiment Videos

  • Pins were identified based on posterior probabilities from probabilistic pairwise sequence alignment.

    • Main Results:

    • Pairwise RNA structural alignment significantly enhances structure prediction accuracy compared to single-sequence folding.
    • The constrained alignment approach effectively reduces computational runtime and memory usage.
    • The developed Consan algorithm demonstrates comparable performance to other leading pairwise Sankoff implementations.

    Conclusions:

    • Incorporating comparative sequence information via pairwise structural alignment improves RNA structure prediction.
    • The constrained Sankoff algorithm offers a practical and efficient solution for homologous RNA analysis.
    • Multiple implementations of the pairwise Sankoff algorithm exist, each with unique advantages.