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

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 microarray-based...
Ribosome Profiling02:24

Ribosome Profiling

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 helps...

You might also read

Related Articles

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

Sort by
Same author

Long-read transcriptomics corrects Trichomonas vaginalis intron annotations and refines transcript-end features.

Parasites & vectors·2026
Same author

Estimated Glomerular Filtration Rate, Nutritional Factors, and Their Relationships With Homocysteine in Community-Dwelling Older Adults.

Journal of nutrition and metabolism·2026
Same author

Reversible On-Off Switching of Chirality via Electrochemical Intercalation Control of Enantiopure Molecular Cations in a Layered van der Waals Material.

ACS nano·2026
Same author

Physalin A interferes with cell cycle in human oral squamous carcinoma cells via DNA topoisomerase II/ATM/ATR/Chk signaling for G2/M phase arrest.

Archives of biochemistry and biophysics·2026
Same author

Revisiting the Nutritional and Health-Promoting Properties of Soy Protein-Based Food Formulations for Infants and Adults.

Comprehensive reviews in food science and food safety·2026
Same author

Bifidobacterium breve promotes growth and lipid alteration in Trichomonas vaginalis transiently through transcriptomic reprogramming.

Scientific reports·2026

Related Experiment Video

Updated: Jun 13, 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

DSAP: deep-sequencing small RNA analysis pipeline.

Po-Jung Huang1, Yi-Chung Liu, Chi-Ching Lee

  • 1Institute of Bioinformatics and Structural Biology, National Tsing Hua University, Hsinchu, Taiwan.

Nucleic Acids Research
|May 19, 2010
PubMed
Summary
This summary is machine-generated.

Deep-sequencing Small RNA Analysis Pipeline (DSAP) offers a comprehensive solution for analyzing small RNA sequencing data. This automated web service facilitates ncRNA and miRNA identification and cross-species comparison.

More Related Videos

A Bioinformatics Pipeline to Accurately and Efficiently Analyze the MicroRNA Transcriptomes in Plants
06:34

A Bioinformatics Pipeline to Accurately and Efficiently Analyze the MicroRNA Transcriptomes in Plants

Published on: January 21, 2020

AQRNA-seq for Quantifying Small RNAs
05:12

AQRNA-seq for Quantifying Small RNAs

Published on: February 2, 2024

Related Experiment Videos

Last Updated: Jun 13, 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

A Bioinformatics Pipeline to Accurately and Efficiently Analyze the MicroRNA Transcriptomes in Plants
06:34

A Bioinformatics Pipeline to Accurately and Efficiently Analyze the MicroRNA Transcriptomes in Plants

Published on: January 21, 2020

AQRNA-seq for Quantifying Small RNAs
05:12

AQRNA-seq for Quantifying Small RNAs

Published on: February 2, 2024

Area of Science:

  • Bioinformatics
  • Genomics
  • Molecular Biology

Background:

  • Next-generation sequencing technologies generate vast amounts of small RNA data.
  • Analyzing this data requires specialized bioinformatics tools for accurate identification and quantification.

Purpose of the Study:

  • To introduce the Deep-sequencing Small RNA Analysis Pipeline (DSAP), an automated web service for comprehensive small RNA data analysis.
  • To provide a user-friendly platform for identifying non-coding RNAs (ncRNAs) and microRNAs (miRNAs) from sequencing data.

Main Methods:

  • DSAP processes tab-delimited input files containing unique sequence reads and their counts.
  • Analysis involves adaptor and nucleotide trimming, sequence clustering, and homology mapping against Rfam and miRBase databases.
  • Results are visualized using interactive charts and comparative tools.

Main Results:

  • DSAP successfully identifies and quantifies ncRNAs and known miRNAs from deep-sequencing small RNA datasets.
  • Expression levels are presented in user-friendly, clickable multi-color bar charts linked to external databases.
  • Cross-species comparative analysis of miRNA distribution is enabled.

Conclusions:

  • DSAP provides an integrated and automated solution for small RNA sequencing data analysis.
  • The tool facilitates efficient identification, quantification, and comparative analysis of ncRNAs and miRNAs.
  • DSAP enhances the utility of next-generation sequencing data for small RNA research.