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

Ribosome Profiling02:24

Ribosome Profiling

4.3K
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...
4.3K
RNA-seq03:21

RNA-seq

12.4K
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...
12.4K

You might also read

Related Articles

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

Sort by
Same author

Scalable, fast and accurate differential gene expression testing from millions of cells of multiple patients.

Nature communications·2026
Same author

CRAK-Velo: chromatin accessibility kinetics integration improves RNA velocity estimation.

Genome biology·2026
Same author

Extending differential gene expression testing to handle genome aneuploidy in cancer.

PLoS computational biology·2026
Same author

Interpretable learning of temporal cellular dynamics from single-cell data.

Cell reports methods·2026
Same author

Multi-view deep learning of highly multiplexed imaging data improves association of cell states with clinical outcomes.

Bioinformatics advances·2026
Same author

Machine learning for RNA secondary structure prediction: a review of current methods and challenges.

RNA (New York, N.Y.)·2026

Related Experiment Video

Updated: Mar 12, 2026

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

5.4K

Robust statistical modeling improves sensitivity of high-throughput RNA structure probing experiments.

Alina Selega1, Christel Sirocchi2, Ira Iosub2

  • 1School of Informatics, University of Edinburgh, Edinburgh, UK.

Nature Methods
|November 8, 2016
PubMed
Summary
This summary is machine-generated.

This study introduces a new statistical modeling pipeline for RNA structure probing. Our method improves sensitivity and reduces data requirements, enabling more accurate analysis of gene expression regulation.

More Related Videos

RNA Secondary Structure Prediction Using High-throughput SHAPE
13:42

RNA Secondary Structure Prediction Using High-throughput SHAPE

Published on: May 31, 2013

32.4K
A Rapid High-throughput Method for Mapping Ribonucleoproteins RNPs on Human pre-mRNA
13:00

A Rapid High-throughput Method for Mapping Ribonucleoproteins RNPs on Human pre-mRNA

Published on: December 2, 2009

12.3K

Related Experiment Videos

Last Updated: Mar 12, 2026

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

5.4K
RNA Secondary Structure Prediction Using High-throughput SHAPE
13:42

RNA Secondary Structure Prediction Using High-throughput SHAPE

Published on: May 31, 2013

32.4K
A Rapid High-throughput Method for Mapping Ribonucleoproteins RNPs on Human pre-mRNA
13:00

A Rapid High-throughput Method for Mapping Ribonucleoproteins RNPs on Human pre-mRNA

Published on: December 2, 2009

12.3K

Area of Science:

  • Molecular Biology
  • Bioinformatics
  • Genomics

Background:

  • RNA structure plays a crucial role in gene expression regulation.
  • Current structure probing techniques coupled with high-throughput sequencing face limitations due to noise and high data requirements.

Purpose of the Study:

  • To develop a probabilistic modeling pipeline to enhance transcriptome-wide RNA structure probing.
  • To address limitations of existing methods by accounting for biological variability and biases.

Main Methods:

  • Development of a probabilistic modeling pipeline for RNA structure analysis.
  • Application of the pipeline to yeast datasets to assess its performance.

Main Results:

  • The pipeline yields statistically interpretable scores for nucleotide modification probability across the transcriptome.
  • Demonstrated increased sensitivity, identifying modified regions on significantly more transcripts compared to existing pipelines.
  • Achieved confident predictions at substantially lower sequence coverage levels.

Conclusions:

  • Statistical modeling significantly extends the scope and potential of transcriptome-wide RNA structure probing experiments.
  • The developed pipeline offers a more sensitive and efficient approach to studying RNA structure's role in gene regulation.