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

lncRNA - Long Non-coding RNAs02:39

lncRNA - Long Non-coding RNAs

2.9K
2.9K
Ribosome Profiling02:24

Ribosome Profiling

3.6K
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...
3.6K
RNA-seq03:21

RNA-seq

10.4K
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...
10.4K

You might also read

Related Articles

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

Sort by
Same author

A Stepped Care, Peer-Delivered Intervention to Improve Substance Use and HIV Medication Adherence in Primary Care in South Africa (Project <i>Khanya</i>): Protocol for a Hybrid Type 2 Effectiveness-Implementation Randomized Controlled Trial.

JMIR research protocols·2026
Same author

FM-GPT: Bayesian fine mapping for phenome-wide transcriptome-wide association studies.

bioRxiv : the preprint server for biology·2026
Same author

Neural Network Assisted Estimation for the Structural Nested Accelerated Failure Time Models.

Statistics in medicine·2026
Same author

Lifestyle risk factors of white matter brain aging: Evidence, potential mechanisms, and future direction.

Neural regeneration research·2026
Same author

Effects of HIV and alcohol stigma on biomarker-confirmed alcohol use following a peer-delivered intervention in South Africa.

Addictive behaviors reports·2025
Same author

Longitudinal Trajectories of Multimorbidity and Psychosocial Resilience Resources in Midlife and Older Adults: Findings From the Health and Retirement Study.

Journal of aging and health·2025
Same journal

Mapping the 3D Chromosome Organization of a Biosynthetic Gene Cluster by Capture Hi-C (CHi-C).

Methods in molecular biology (Clifton, N.J.)·2026
Same journal

Mapping the 3D Chromosome Organization of Streptomyces by Hi-C.

Methods in molecular biology (Clifton, N.J.)·2026
Same journal

CUT&Tag Epigenomic Profiling of Biosynthetic Gene Clusters in Arabidopsis thaliana.

Methods in molecular biology (Clifton, N.J.)·2026
Same journal

Rhizobium rhizogenes-Mediated Hairy Root Transformation Protocol for Lotus japonicus and Other Legumes.

Methods in molecular biology (Clifton, N.J.)·2026
Same journal

Characterization of Bioactive Saponins from Sea Cucumbers.

Methods in molecular biology (Clifton, N.J.)·2026
Same journal

Methods for Functional Validation of Terpenoid Metabolic Clusters in Nicotiana benthamiana and Aspergillus oryzae.

Methods in molecular biology (Clifton, N.J.)·2026
See all related articles

Related Experiment Video

Updated: Sep 12, 2025

CRISPR Gene Editing Tool for MicroRNA Cluster Network Analysis
10:40

CRISPR Gene Editing Tool for MicroRNA Cluster Network Analysis

Published on: April 25, 2022

2.5K

NGP: A Tool to Detect Noncoding RNA-Gene Regulatory Pairs from Transcriptomic Data.

Hongjie Ke1, Tianzhou Ma2

  • 1Department of Epidemiology and Biostatistics, School of Public Health, University of Maryland, College Park, MD, USA.

Methods in Molecular Biology (Clifton, N.J.)
|August 8, 2025
PubMed
Summary
This summary is machine-generated.

Noncoding RNAs (ncRNAs) regulate gene expression in cancer. A new R package, NGP, identifies essential ncRNA-gene pairs, improving upon methods that ignore complex interactions.

Keywords:
Gene expressionGene regulationNGPNoncoding RNA

More Related Videos

RNA Pull-down Procedure to Identify RNA Targets of a Long Non-coding RNA
09:36

RNA Pull-down Procedure to Identify RNA Targets of a Long Non-coding RNA

Published on: April 10, 2018

25.5K
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

11.8K

Related Experiment Videos

Last Updated: Sep 12, 2025

CRISPR Gene Editing Tool for MicroRNA Cluster Network Analysis
10:40

CRISPR Gene Editing Tool for MicroRNA Cluster Network Analysis

Published on: April 25, 2022

2.5K
RNA Pull-down Procedure to Identify RNA Targets of a Long Non-coding RNA
09:36

RNA Pull-down Procedure to Identify RNA Targets of a Long Non-coding RNA

Published on: April 10, 2018

25.5K
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

11.8K

Area of Science:

  • Genomics
  • Bioinformatics
  • Cancer Biology

Background:

  • Noncoding RNAs (ncRNAs) are crucial regulators in cancer development.
  • Current methods analyze ncRNA-gene interactions individually, missing complex regulatory networks.

Purpose of the Study:

  • To introduce a statistically rigorous and efficient software tool for identifying key ncRNA-gene regulatory pairs.
  • To provide practical guidance on using the NGP R package with real transcriptome data.

Main Methods:

  • Development of a novel computational tool for analyzing transcriptome-wide ncRNA and gene expression data.
  • Implementation of the tool within the R package 'NGP'.
  • Validation using real-world gene and ncRNA expression datasets.

Main Results:

  • The NGP tool effectively identifies significant ncRNA-gene regulatory relationships.
  • The software provides a more comprehensive analysis than traditional bivariate methods.
  • Demonstrated utility through practical examples in the accompanying guidance.

Conclusions:

  • The NGP R package offers a robust solution for dissecting complex ncRNA-gene interactions in cancer.
  • This tool facilitates deeper understanding of ncRNA roles in oncogenesis.
  • Enables more accurate identification of regulatory pathways for potential therapeutic targets.