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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)...
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...
piRNA - Piwi-interacting RNAs02:57

piRNA - Piwi-interacting RNAs

PIWI-interacting RNAs, or piRNAs, are the most abundant short non-coding RNAs. More than 20,000 genes have been found in humans that code for piRNAs while only 2000 genes have been found for miRNAs. piRNAs can act at the transcriptional and post-transcriptional levels and have a vital role in silencing transposable elements present in germ cells. They are also involved in epigenetic silencing and activation. Previously, they were thought to function only in germ cells but new evidence suggests...
Small interfering RNAs (siRNA)02:30

Small interfering RNAs (siRNA)

Small interfering RNAs, or siRNAs, are short regulatory RNA molecules that can silence genes post-transcriptionally, as well as the transcriptional level in some cases. siRNAs are important for protecting cells against viral infections and silencing transposable genetic elements.
In the cytoplasm, siRNA is processed from a double-stranded RNA, which comes from either endogenous DNA transcription or exogenous sources like a virus. This double-stranded RNA is then cleaved by the ATP-dependent...

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Updated: May 11, 2026

Computational Analysis Tutorial for Chimeric Small Noncoding RNA: Target RNA Sequencing Libraries
07:35

Computational Analysis Tutorial for Chimeric Small Noncoding RNA: Target RNA Sequencing Libraries

Published on: December 1, 2023

CoRAL: predicting non-coding RNAs from small RNA-sequencing data.

Yuk Yee Leung1, Paul Ryvkin, Lyle H Ungar

  • 1Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.

Nucleic Acids Research
|May 24, 2013
PubMed
Summary
This summary is machine-generated.

We developed Classification of RNAs by Analysis of Length (CoRAL), a machine learning tool to classify RNA molecules. CoRAL accurately distinguishes RNA types using features like length, aiding ncRNA research.

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Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations
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Last Updated: May 11, 2026

Computational Analysis Tutorial for Chimeric Small Noncoding RNA: Target RNA Sequencing Libraries
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Computational Analysis Tutorial for Chimeric Small Noncoding RNA: Target RNA Sequencing Libraries

Published on: December 1, 2023

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

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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:

  • The human genome is extensively transcribed, yielding diverse RNA molecules with largely unknown functions.
  • Existing methods for RNA function prediction, relying on sequence or alignment, struggle to classify non-coding RNAs (ncRNAs).

Purpose of the Study:

  • To develop a novel machine learning approach, Classification of RNAs by Analysis of Length (CoRAL), for classifying RNA molecules.
  • To utilize biologically interpretable features for distinguishing between different ncRNA populations.

Main Methods:

  • CoRAL employs machine learning algorithms to classify RNA molecules.
  • Key features used include fragment length and cleavage specificity.
  • The approach was validated using genome-wide small RNA sequencing data from four human tissue types.

Main Results:

  • CoRAL achieved approximately 80% cross-validation accuracy in classifying six different RNA types.
  • MicroRNAs, small nucleolar RNAs, and transposon-derived RNAs were consistently discernible across tissues.
  • Long intergenic ncRNAs, small cytoplasmic RNAs, and small nuclear RNAs exhibited less consistent patterns.

Conclusions:

  • CoRAL provides a reliable method for annotating RNA loci across different tissue types.
  • This tool has the potential to characterize ncRNAs using small RNA sequencing data, particularly in understudied organisms.