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

2.8K
2.8K
RNA-seq03:21

RNA-seq

10.0K
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...
10.0K

You might also read

Related Articles

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

Sort by
Same author

Exploratory study of electroencephalogram markers of responsiveness to surgical noxious stimuli under propofol anaesthesia.

BMC anesthesiology·2026
Same author

A neural mass modelling framework for evaluating EEG source localisation of seizure activity.

Journal of neural engineering·2026
Same author

Automated Eosinophil Quantification Using Deep Learning to Predict Therapy Escalation in Pediatric Ulcerative Colitis.

Clinical and translational gastroenterology·2026
Same author

Interictal Epileptiform Discharge Detection Through Probabilistic Diffusion Models with Maximization of Precision Recall Metrics.

International journal of neural systems·2026
Same author

Multi-omics applications in health and diseases.

Progress in molecular biology and translational science·2026
Same author

Structural Eigenmodes of the Brain to Improve the Source Localization of EEG: Application to Epileptiform Activity.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)·2026

Related Experiment Video

Updated: Jul 15, 2025

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

8.4K

Linc2function: A Comprehensive Pipeline and Webserver for Long Non-Coding RNA (lncRNA) Identification and Functional

Yashpal Ramakrishnaiah1,2, Adam P Morris3, Jasbir Dhaliwal2

  • 1Central Clinical School, Monash University, Melbourne, VIC 3000, Australia.

Epigenomes
|September 27, 2023
PubMed
Summary

This study introduces a new pipeline for annotating long non-coding RNAs (lncRNAs) at the transcript level. It integrates structural and interaction data for comprehensive functional analysis, aiding disease research.

Keywords:
deep learningfunctional annotationlncRNAmachine learningnon-coding RNA

More Related Videos

RNA Next-Generation Sequencing and a Bioinformatics Pipeline to Identify Expressed LINE-1s at the Locus-Specific Level
11:04

RNA Next-Generation Sequencing and a Bioinformatics Pipeline to Identify Expressed LINE-1s at the Locus-Specific Level

Published on: May 19, 2019

10.0K
Identification of RNAs Engaged in Direct RNA-RNA Interaction with a Long Non-Coding RNA
07:24

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

Published on: July 9, 2021

2.5K

Related Experiment Videos

Last Updated: Jul 15, 2025

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

8.4K
RNA Next-Generation Sequencing and a Bioinformatics Pipeline to Identify Expressed LINE-1s at the Locus-Specific Level
11:04

RNA Next-Generation Sequencing and a Bioinformatics Pipeline to Identify Expressed LINE-1s at the Locus-Specific Level

Published on: May 19, 2019

10.0K
Identification of RNAs Engaged in Direct RNA-RNA Interaction with a Long Non-Coding RNA
07:24

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

Published on: July 9, 2021

2.5K

Area of Science:

  • Genomics
  • Bioinformatics
  • Molecular Biology

Background:

  • Long non-coding RNAs (lncRNAs) are crucial regulators of cellular functions and potential disease biomarkers, yet their specific roles and transcript isoforms are largely uncharacterized.
  • Current methods for lncRNA analysis primarily focus on gene-level investigations and sequence-based discrimination, limiting comprehensive functional annotation and cross-species applicability.

Purpose of the Study:

  • To develop and validate a novel computational pipeline for high-throughput, isoform-level annotation of long non-coding RNAs (lncRNAs).
  • To enhance the understanding of lncRNA mechanisms in pathological processes by integrating secondary structure and interactome information.
  • To address challenges in annotating lncRNAs for new species and improve the generalizability of in silico prediction methods.

Main Methods:

  • Developed a computational pipeline integrating transcript sequence, secondary structure, and interactome information for lncRNA annotation.
  • Employed transcript-level analysis to discriminate lncRNAs from coding RNAs and predict functional motifs and target biomolecules.
  • Validated the pipeline's effectiveness through comprehensive annotation of lncRNAs associated with two specific disease groups.

Main Results:

  • The proposed pipeline enables comprehensive functional annotation of lncRNAs by incorporating diverse data types beyond primary sequence.
  • Successfully demonstrated the pipeline's capability in annotating lncRNAs related to specific disease cohorts.
  • The developed pipeline overcomes limitations of reference-based and sequence-only methods, improving accuracy and generalizability.

Conclusions:

  • Integrating transcript sequence, secondary structure, and interactome data is essential for accurate and comprehensive lncRNA functional annotation.
  • The developed pipeline provides a robust tool for isoform-level lncRNA identification and annotation, advancing our understanding of lncRNA roles in disease.
  • The pipeline's open-source availability and web server interface promote accessibility for researchers and non-technical users alike.