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

10.9K
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...
10.9K
Multi-species Conserved Sequences02:51

Multi-species Conserved Sequences

4.4K
Next-generation sequencing technologies have created large genomic databases of a variety of animals and plants. Ever since the human genome project was completed, scientists studied the genome of primates, mammals, and other phylogenetically distant living beings. Such large-scale  studies have provided new insights into the evolutionary relationship between organisms.
Although the genome of each species varies greatly from each other, a few sequences are highly conserved. Such conserved...
4.4K
Ribosome Profiling02:24

Ribosome Profiling

3.8K
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...
3.8K

You might also read

Related Articles

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

Sort by
Same author

HERA: a web server for host element reference-based aligner.

Nucleic acids research·2026
Same author

RegRegSEA: a web server for regulatory region set enrichment analysis of epigenomic data.

Nucleic acids research·2026
Same author

mRNA Sequencing of Limbal Epithelial Cells and mRNA/miRNA Profiling of Limbal Stromal Cells in <i>PAX6</i>-Related Congenital Aniridia.

Cells·2026
Same author

MCPmed: a call for Model Context Protocol-enabled bioinformatics web services for LLM-driven discovery.

Briefings in bioinformatics·2026
Same author

Cross-Species Self-supervised Transfer Learning for Pulmonary Lobe Segmentation in Nonhuman Primates.

Journal of imaging informatics in medicine·2026
Same author

MiRNAs shape mouse age-independent tissue adaptation to spaceflight via ECM and developmental pathways.

Nature communications·2026

Related Experiment Video

Updated: Nov 8, 2025

A Complete Pipeline for Isolating and Sequencing MicroRNAs, and Analyzing Them Using Open Source Tools
09:29

A Complete Pipeline for Isolating and Sequencing MicroRNAs, and Analyzing Them Using Open Source Tools

Published on: August 21, 2019

7.6K

miRMaster 2.0: multi-species non-coding RNA sequencing analyses at scale.

Tobias Fehlmann1, Fabian Kern1, Omar Laham1

  • 1Chair for Clinical Bioinformatics, Saarland University, 66123 Saarbrücken, Germany.

Nucleic Acids Research
|April 19, 2021
PubMed
Summary
This summary is machine-generated.

miRMaster 2 simplifies small non-coding RNA sequencing analysis with enhanced species and RNA class support. This updated tool offers new modules for UMI processing and differential expression analysis, improving data interpretation.

More Related Videos

Isolating, Sequencing and Analyzing Extracellular MicroRNAs from Human Mesenchymal Stem Cells
10:55

Isolating, Sequencing and Analyzing Extracellular MicroRNAs from Human Mesenchymal Stem Cells

Published on: March 8, 2019

8.4K
Multiplexed Single Cell mRNA Sequencing Analysis of Mouse Embryonic Cells
08:30

Multiplexed Single Cell mRNA Sequencing Analysis of Mouse Embryonic Cells

Published on: January 7, 2020

13.6K

Related Experiment Videos

Last Updated: Nov 8, 2025

A Complete Pipeline for Isolating and Sequencing MicroRNAs, and Analyzing Them Using Open Source Tools
09:29

A Complete Pipeline for Isolating and Sequencing MicroRNAs, and Analyzing Them Using Open Source Tools

Published on: August 21, 2019

7.6K
Isolating, Sequencing and Analyzing Extracellular MicroRNAs from Human Mesenchymal Stem Cells
10:55

Isolating, Sequencing and Analyzing Extracellular MicroRNAs from Human Mesenchymal Stem Cells

Published on: March 8, 2019

8.4K
Multiplexed Single Cell mRNA Sequencing Analysis of Mouse Embryonic Cells
08:30

Multiplexed Single Cell mRNA Sequencing Analysis of Mouse Embryonic Cells

Published on: January 7, 2020

13.6K

Area of Science:

  • Bioinformatics
  • Genomics
  • Molecular Biology

Background:

  • Analyzing small non-coding RNA sequencing data is complex.
  • Previous tools may lack comprehensive species and RNA class support.
  • Advancements in sequencing technologies necessitate updated analytical pipelines.

Purpose of the Study:

  • To present miRMaster 2, an updated software for small non-coding RNA sequencing data analysis.
  • To enhance the capabilities of miRMaster by incorporating new features and expanding support.
  • To provide a user-friendly and comprehensive tool for researchers in the field.

Main Methods:

  • Development and updates to the miRMaster software.
  • Inclusion of extended reference datasets for multiple species and RNA classes.
  • Integration of new modules for UMI processing, batch effect analysis, and sample embeddings (UMAP).
  • Updated annotation databases (miRBase, Ensembl, GtRNAdb).
  • Integration of differential expression analysis with miEAA.

Main Results:

  • miRMaster 2 supports analysis for eight species and 10 non-coding RNA classes.
  • New modules for UMI processing and advanced downstream analyses (e.g., UMAP) are included.
  • Improved output formats and graphics enhance data visualization and interpretation.
  • Integration with miEAA facilitates miRNA enrichment analysis.

Conclusions:

  • miRMaster 2 offers a significantly enhanced and expanded platform for small non-coding RNA sequencing data analysis.
  • The updated features cater to the growing needs of researchers, including single-cell data analysis.
  • miRMaster 2 provides a powerful, freely available resource for the scientific community.