Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

lncRNA - Long Non-coding RNAs

lncRNA - Long Non-coding RNAs

RNA-seq

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...

Nonsense-mediated mRNA Decay

Nonsense-mediated mRNA Decay

The Upf proteins that carry out nonsense-mediated decay (NMD) are found in all eukaryotic organisms, including humans. Each protein has an individual role, but they need to work in collaboration. Upf1 is an ATP-dependent RNA helicase that unwinds the RNA helix. Because Upf1 can unwind any RNA, Upf2 and Upf3 are required to help Upf1 discriminate between nonsense and normal mRNAs.
Usually, Upf3 binds to an Exon Junction Complex (EJC) at mRNA splice sites. If a ribosome fully translates the mRNA,...

You might also read

Related Articles

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

Sort by

Same author

Epicardial muscle bundles in persistent atrial fibrillation: from overlooked bystanders to arrhythmogenic modulators.

Journal of interventional cardiac electrophysiology : an international journal of arrhythmias and pacing·2026

Same author

A Fully Potentiometric Electronic Tongue Enabling Comprehensive Physical and Chemical Sensations.

ACS applied materials & interfaces·2026

Same author

Associations between the C-reactive protein-triglyceride glucose index and the incidence and progression trajectory of cardiometabolic multimorbidity: a multi-state model study.

Cardiovascular diabetology·2026

Same author

Efficacy and safety of Shexiang Tongxin pill for coronary slow flow in angina patients.

NPJ cardiovascular health·2026

Same author

IRF7 orchestrates maladaptive smooth muscle cell phenotype switching in atherosclerosis.

Precision clinical medicine·2026

Same author

Analysis of the Chief Complaints at Consultation in 278 Patients With Submucous Cleft Palate.

The Journal of craniofacial surgery·2026

Same journal

Correction: A method for supervoxel-wise association studies of age and other non-imaging variables from coronary computed tomography angiograms.

Scientific reports·2026

Same journal

Poly(bromophenol blue)/CoSn(OH)<sub>6</sub> cubic particles modified pencil graphite electrode for electrochemical determination of diphenhydramine.

Scientific reports·2026

Same journal

Dietary Chlorella, Spirulina, and acidifier modulate jejunal cytokine-related gene expression in broiler chickens.

Scientific reports·2026

Same journal

Perceived physical activity barriers in university students: associations with fatigue and eating behaviours.

Scientific reports·2026

Same journal

Refuge limitation structures habitat use in agricultural landscapes: evidence from Sunda pangolins.

Scientific reports·2026

Same journal

Lightweight stateless transaction verification with outsourced witness updates for UTXO blockchains.

Scientific reports·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Aug 22, 2025

Identification of RNAs Engaged in Direct RNA-RNA Interaction with a Long Non-Coding RNA

Identification of RNAs Engaged in Direct RNA-RNA Interaction with a Long Non-Coding RNA

Published on: July 9, 2021

LncDC: a machine learning-based tool for long non-coding RNA detection from RNA-Seq data.

Minghua Li¹, Chun Liang²

¹Department of Biology, Miami University, Oxford, OH, 45056, USA. lim74@miamioh.edu.

Scientific Reports

|November 9, 2022

Summary

This summary is machine-generated.

We developed LncDC, a novel tool for accurately distinguishing long non-coding RNAs (lncRNAs) from messenger RNAs (mRNAs). LncDC aids in discovering novel disease-specific lncRNAs by improving classification accuracy.

More Related Videos

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

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

Published on: April 10, 2018

Identification of Circular RNAs using RNA Sequencing

Identification of Circular RNAs using RNA Sequencing

Published on: November 14, 2019

Related Experiment Videos

Last Updated: Aug 22, 2025

Identification of RNAs Engaged in Direct RNA-RNA Interaction with a Long Non-Coding RNA

Identification of RNAs Engaged in Direct RNA-RNA Interaction with a Long Non-Coding RNA

Published on: July 9, 2021

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

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

Published on: April 10, 2018

Identification of Circular RNAs using RNA Sequencing

Identification of Circular RNAs using RNA Sequencing

Published on: November 14, 2019

Area of Science:

Genomics
Bioinformatics
Molecular Biology

Background:

Long non-coding RNAs (lncRNAs) are crucial in biological processes and disease.
Accurate classification of lncRNAs and messenger RNAs (mRNAs) is vital for identifying tissue- or disease-specific lncRNAs.

Purpose of the Study:

To develop and present LncDC, a computational tool for accurate lncRNA prediction.
To enhance the identification of disease-specific lncRNAs.

Main Methods:

Utilized an XGBoost model for classification.
Extracted features from RNA sequences, secondary structures, and translated proteins.
Incorporated sequence and secondary structure (SASS) k-mer score and flexible ORF features.

Main Results:

LncDC demonstrated superior performance in distinguishing lncRNAs from mRNAs compared to six existing tools.
The inclusion of SASS k-mer and flexible ORF features significantly improved LncDC's classification accuracy.

Conclusions:

LncDC provides a highly accurate method for lncRNA prediction.
The tool is expected to accelerate the discovery of novel disease-specific lncRNAs.
LncDC is freely available as an open-source Python implementation.