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Related Concept Videos

RNA-seq03:21

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 microarray-based...
lncRNA - Long Non-coding RNAs02:39

lncRNA - Long Non-coding RNAs

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 (lncRNA)...
Ribosome Profiling02:24

Ribosome Profiling

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 helps...

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Related Experiment Video

Updated: May 9, 2026

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

Detecting and comparing non-coding RNAs in the high-throughput era.

Giovanni Bussotti1, Cedric Notredame, Anton J Enright

  • 1European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK. giovanni.bussotti@ebi.ac.uk

International Journal of Molecular Sciences
|July 27, 2013
PubMed
Summary
This summary is machine-generated.

Discovering non-coding RNA (ncRNA) requires advanced sequence alignment methods. This review explores new techniques for comparing ncRNA sequences and analyzing high-throughput data, crucial for understanding cellular functions.

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Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations
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Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations

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Last Updated: May 9, 2026

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

Identification of Key Factors Regulating Self-renewal and Differentiation in EML Hematopoietic Precursor Cells by RNA-sequencing Analysis
12:44

Identification of Key Factors Regulating Self-renewal and Differentiation in EML Hematopoietic Precursor Cells by RNA-sequencing Analysis

Published on: November 11, 2014

Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations
11:52

Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations

Published on: August 4, 2016

Area of Science:

  • Genomics
  • Molecular Biology
  • Bioinformatics

Background:

  • Growing interest in non-coding RNA (ncRNA) due to discovery of new genes and their cellular roles.
  • Accurate detection and comparison of RNA sequences are vital for identifying homologous genes and biological patterns.
  • Comparing ncRNAs is challenging due to limited sequence conservation and evolution constrained by structure.

Purpose of the Study:

  • To review comparative genomics of non-coding RNAs.
  • To focus on new sequencing technologies and their impact on ncRNA analysis.
  • To address the need for novel methods in RNA alignment and high-throughput data analysis.

Main Methods:

  • Review of current literature on ncRNA comparative genomics.
  • Discussion of challenges in aligning RNA sequences, particularly non-coding ones.
  • Exploration of new methods for RNA sequence alignment and high-throughput data analysis.

Main Results:

  • Highlighting the limitations of traditional sequence alignment for ncRNAs.
  • Emphasizing the importance of structural conservation in ncRNA evolution.
  • Identifying the need for advanced computational tools to analyze ncRNA data.

Conclusions:

  • New methods for RNA alignment are urgently needed to fully exploit experimental data.
  • Advancements in sequencing technologies necessitate improved bioinformatics approaches for ncRNA research.
  • Effective comparative genomics of ncRNAs will enhance our understanding of their roles in cellular functions.