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

3.8K
3.8K
lncRNA - Long Non-coding RNAs02:39

lncRNA - Long Non-coding RNAs

10.0K
In humans, more than 80% of the genome gets transcribed. However, only around 2% of the genome codes for proteins. The remaining part produces non-coding RNAs which includes ribosomal RNAs, transfer RNAs, telomerase RNAs, and regulatory RNAs, among other types. A large number of regulatory non-coding RNAs have been classified into two groups depending upon their length – small non-coding RNAs, such as microRNA, which are less than 200 nucleotides in length, and long non-coding RNA...
10.0K
Genetic Screens02:46

Genetic Screens

5.8K
Genetic screens are tools used to identify genes and mutations responsible for phenotypes of interest. Genetic screens help identify individuals or a group of people at risk of developing  genetic diseases and help them with early intervention, targeted therapy, and reproductive options.
Forward genetic screens
Forward or “classical” genetic screens involve creating random mutations in an organism’s DNA using radiation, mutagens, or insertion of additional bases, which...
5.8K
RNA-seq03:21

RNA-seq

12.2K
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...
12.2K

You might also read

Related Articles

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

Sort by
Same author

Inflammatory immune modulators of AML lung infiltration and respiratory failure.

Nature immunology·2026
Same author

Cell autonomous inflammation in VEXAS is mediated by cGAS-STING.

bioRxiv : the preprint server for biology·2026
Same author

RAS pathway activation and microenvironmental adaptation as hallmarks of myeloid sarcoma.

Blood cancer discovery·2026
Same author

LIF-Induced Tumor Plasticity Establishes an Immunosuppressive Myeloid Niche in LKB1-Mutant Lung Cancer.

Cancer discovery·2026
Same author

3D Chromosome Remodeling in B-cell Development and Acute Lymphoblastic Leukemia.

Blood cancer discovery·2026
Same author

Epigenetic reactivation of the tumor suppressor ZBTB7A by KDM4 inhibition in human acute myeloid leukemia.

Science translational medicine·2026

Related Experiment Video

Updated: Mar 1, 2026

Genome-wide RNAi Screening to Identify Host Factors That Modulate Oncolytic Virus Therapy
08:51

Genome-wide RNAi Screening to Identify Host Factors That Modulate Oncolytic Virus Therapy

Published on: April 3, 2018

9.5K

lncRNA-screen: an interactive platform for computationally screening long non-coding RNAs in large genomics datasets.

Yixiao Gong1,2, Hsuan-Ting Huang3, Yu Liang4

  • 1Department of Pathology and Laura and Isaac Perlmutter Cancer Center, New York University School of Medicine, New York, NY, 10016, USA.

BMC Genomics
|June 7, 2017
PubMed
Summary

lncRNA-screen is a new pipeline that simplifies the computational discovery of long non-coding RNAs (lncRNAs) from complex genomic data. This tool aids researchers in identifying potential lncRNA candidates for further experimental validation.

Keywords:
Comprehensive pipelineData integrationFully automatedInteractive reportlncRNA

More Related Videos

Author Spotlight: Cost-Effective Transcriptomic Drug Screening - Unlocking New Targets
06:40

Author Spotlight: Cost-Effective Transcriptomic Drug Screening - Unlocking New Targets

Published on: February 23, 2024

1.8K
Author Spotlight: A Computational Pipeline for Analyzing Chimeric Noncoding RNA-Target RNA Interactions in High-Throughput Sequencing Data
07:35

Author Spotlight: A Computational Pipeline for Analyzing Chimeric Noncoding RNA-Target RNA Interactions in High-Throughput Sequencing Data

Published on: December 1, 2023

1.2K

Related Experiment Videos

Last Updated: Mar 1, 2026

Genome-wide RNAi Screening to Identify Host Factors That Modulate Oncolytic Virus Therapy
08:51

Genome-wide RNAi Screening to Identify Host Factors That Modulate Oncolytic Virus Therapy

Published on: April 3, 2018

9.5K
Author Spotlight: Cost-Effective Transcriptomic Drug Screening - Unlocking New Targets
06:40

Author Spotlight: Cost-Effective Transcriptomic Drug Screening - Unlocking New Targets

Published on: February 23, 2024

1.8K
Author Spotlight: A Computational Pipeline for Analyzing Chimeric Noncoding RNA-Target RNA Interactions in High-Throughput Sequencing Data
07:35

Author Spotlight: A Computational Pipeline for Analyzing Chimeric Noncoding RNA-Target RNA Interactions in High-Throughput Sequencing Data

Published on: December 1, 2023

1.2K

Area of Science:

  • Genomics
  • Bioinformatics
  • Molecular Biology

Background:

  • Long non-coding RNAs (lncRNAs) play crucial roles in biological development and cancer.
  • Computational methods for lncRNA prediction are effective but require significant genomics expertise.
  • Handling and integrating diverse genomic datasets presents a challenge for many research labs.

Purpose of the Study:

  • To develop a user-friendly computational pipeline for screening long non-coding RNA transcripts.
  • To facilitate the discovery of novel lncRNA candidates for experimental validation.
  • To simplify the analysis of large, multimodal genomic datasets for lncRNA research.

Main Methods:

  • Developed lncRNA-screen, a comprehensive, automated pipeline for lncRNA discovery.
  • Integrated data download, RNA-seq alignment, assembly, and quality assessment.
  • Incorporated transcript filtration, coding potential estimation, and expression analysis.
  • Included histone mark enrichment, differential expression analysis, and annotation with genomic data (CNVs, SNPs, Hi-C).
  • Generated an interactive report with genome browser snapshots and lncRNA-mRNA interactions.

Main Results:

  • lncRNA-screen successfully screens putative lncRNA transcripts from large multimodal datasets.
  • The pipeline automates complex data handling, including novel lncRNA identification and functional feature analysis.
  • An interactive report highlights key lncRNA features and potential interactions, aiding candidate selection.

Conclusions:

  • lncRNA-screen offers a comprehensive and accessible solution for lncRNA discovery.
  • The pipeline simplifies the identification of promising lncRNA candidates for functional studies.
  • lncRNA-screen is available as open-source software, promoting wider accessibility and adoption.