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 Concept Videos

RNA-seq03:21

RNA-seq

9.5K
RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases. 
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...
9.5K
Next-generation Sequencing03:00

Next-generation Sequencing

88.0K
The first human genome sequencing project cost $2.7 billion and was declared complete in 2003, after 15 years of international cooperation and collaboration between several research teams and funding agencies. Today, with the advent of next-generation sequencing technologies, the cost and time of sequencing a human genome have dropped over 100 fold.
Next-Generation Sequencing Methods
Although all next-generation methods use different technologies, they all share a set of standard features....
88.0K
Ribosome Profiling02:24

Ribosome Profiling

3.2K
Ribosome profiling or ribo-sequencing is a deep sequencing technique that produces a snapshot of active translation in a cell. It selectively sequences the mRNAs protected by ribosomes to get an insight into a cell’s translation landscape at any given point in time.
Applications of ribosome profiling
Ribosome profiling has many applications, including in vivo monitoring of translation inside a particular organ or tissue type and quantifying new protein synthesis levels.
The technique...
3.2K
Nonsense-mediated mRNA Decay02:27

Nonsense-mediated mRNA Decay

9.4K
The Upf proteins that carry out nonsense-mediated decay (NMD) are found in all eukaryotic organisms, including humans. Each protein has an individual role, but they need to work in collaboration. Upf1 is an ATP-dependent RNA helicase that unwinds the RNA helix. Because Upf1 can unwind any RNA, Upf2 and Upf3 are required to help Upf1 discriminate between nonsense and normal mRNAs.
Usually, Upf3 binds to an Exon Junction Complex (EJC) at mRNA splice sites. If a ribosome fully translates the mRNA,...
9.4K
Mismatch Repair01:36

Mismatch Repair

38.2K
Overview
38.2K

You might also read

Related Articles

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

Sort by
Same author

Undesignable motifs in structural RNAs and combinatorial consequences.

Journal of mathematical biology·2026
Same author

Reconstructing Ancestral Non-Coding RNAs of Multiple Families Using Sequence and Structural Information with Tree Decomposition.

Journal of computational biology : a journal of computational molecular cell biology·2026
Same author

Designing molecular RNA switches with Restricted Boltzmann machines.

Nature communications·2025
Same author

RNA triplet repeats: improved algorithms for structure prediction and interactions.

Algorithms for molecular biology : AMB·2025
Same author

RNA inverse folding can be solved in linear time for structures without isolated stacks or base pairs.

Algorithms for molecular biology : AMB·2025
Same author

Improving the Reliability of Molecular String Representations for Generative Chemistry.

Journal of chemical information and modeling·2025
Same journal

GMSA: A Graph Matching and Point Cloud Registration-Based Method for Spatial Transcriptomics Data Alignment.

Journal of computational biology : a journal of computational molecular cell biology·2026
Same journal

Investigations on Multiple Protein Scaffold Filling.

Journal of computational biology : a journal of computational molecular cell biology·2026
Same journal

Cell Type Prediction for Single-Cell RNA Sequencing Utilizing Unsupervised Domain Adaptation and Semi-Supervised Learning.

Journal of computational biology : a journal of computational molecular cell biology·2026
Same journal

PPIGAN: Prediction of Protein-Protein Interactions Using Generative Adversarial Networks.

Journal of computational biology : a journal of computational molecular cell biology·2026
Same journal

Deep Structure-Enhanced Cell Clustering Model for Single-Cell RNA Sequencing Data.

Journal of computational biology : a journal of computational molecular cell biology·2026
Same journal

Asymmetric Drug-Drug Interaction Prediction Based on Generative Adversarial Networks and Knowledge Graph.

Journal of computational biology : a journal of computational molecular cell biology·2026
See all related articles

Related Experiment Video

Updated: May 6, 2026

Rare Event Detection Using Error-corrected DNA and RNA Sequencing
10:36

Rare Event Detection Using Error-corrected DNA and RNA Sequencing

Published on: August 3, 2018

14.6K

Using structural and evolutionary information to detect and correct pyrosequencing errors in noncoding RNAs.

Vladimir Reinharz1, Yann Ponty, Jérôme Waldispühl

  • 11 School of Computer Science, McGill University , Montreal, Canada .

Journal of Computational Biology : a Journal of Computational Molecular Cell Biology
|October 19, 2013
PubMed
Summary
This summary is machine-generated.

RNApyro corrects next-generation sequencing (NGS) errors by identifying mutations that enhance RNA sequence likelihood for a given structure. This efficient algorithm aids in refining RNA sequence data for evolutionary and technological applications.

More Related Videos

Genome-wide Surveillance of Transcription Errors in Eukaryotic Organisms
09:30

Genome-wide Surveillance of Transcription Errors in Eukaryotic Organisms

Published on: September 13, 2018

7.9K
Probing RNA Structure with Dimethyl Sulfate Mutational Profiling with Sequencing In Vitro and in Cells
10:34

Probing RNA Structure with Dimethyl Sulfate Mutational Profiling with Sequencing In Vitro and in Cells

Published on: December 9, 2022

4.7K

Related Experiment Videos

Last Updated: May 6, 2026

Rare Event Detection Using Error-corrected DNA and RNA Sequencing
10:36

Rare Event Detection Using Error-corrected DNA and RNA Sequencing

Published on: August 3, 2018

14.6K
Genome-wide Surveillance of Transcription Errors in Eukaryotic Organisms
09:30

Genome-wide Surveillance of Transcription Errors in Eukaryotic Organisms

Published on: September 13, 2018

7.9K
Probing RNA Structure with Dimethyl Sulfate Mutational Profiling with Sequencing In Vitro and in Cells
10:34

Probing RNA Structure with Dimethyl Sulfate Mutational Profiling with Sequencing In Vitro and in Cells

Published on: December 9, 2022

4.7K

Area of Science:

  • Computational Biology
  • Bioinformatics
  • Molecular Evolution

Background:

  • Accurate RNA sequence-structure relationship analysis is crucial for evolutionary studies and next-generation sequencing (NGS) error correction.
  • Computational challenges arise from large mutational/conformational landscapes and data volumes, necessitating efficient algorithms.
  • Existing NGS error-correction tools can be enhanced by precise sequence-structure property computation.

Purpose of the Study:

  • To develop an efficient algorithm for correcting errors in next-generation sequencing (NGS) data by analyzing RNA sequence-structure relationships.
  • To identify specific mutations that increase the probability of an RNA sequence conforming to a given structure and RNA family.
  • To introduce RNApyro, an algorithm designed for fast and accurate computation of mutational probabilities under structural and evolutionary constraints.

Main Methods:

  • Introduced RNApyro, a linear time and space inside-outside algorithm.
  • Computed exact mutational probabilities considering secondary structure and evolutionary constraints from multiple sequence alignments.
  • Developed a scoring scheme combining stacking base-pair energies and novel isostericity scores.

Main Results:

  • RNApyro efficiently computes mutational probabilities for RNA sequences.
  • The algorithm was applied to correct pointwise errors in 5s and 16s ribosomal RNA (rRNA) sequences.
  • Demonstrated the potential of RNApyro to improve the accuracy of NGS data.

Conclusions:

  • RNApyro offers an efficient solution for calculating sequence-structure properties in RNA analysis.
  • The algorithm shows promise as a complementary tool for NGS error-correction pipelines.
  • Accurate RNA sequence analysis using RNApyro can benefit both evolutionary research and biotechnological applications.