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Related Concept Videos

DNA Microarrays02:34

DNA Microarrays

Microarrays are high-throughput and relatively inexpensive assays that can be automated to analyze large quantities of data at a time. They are used in genome-wide studies to compare gene or protein expression under two varied conditions, such as healthy and diseased states. Microarrays consist of glass or silica slides on which probe molecules are covalently attached through surface functionalization. Most commonly, the slides are prepared through the chemisorption of silanes to silica...
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. 
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Ribosome Profiling02:24

Ribosome Profiling

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Ribosome profiling has many applications, including in vivo monitoring of translation inside a particular organ or tissue type and quantifying new protein synthesis levels.
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Related Experiment Video

Updated: Jun 8, 2026

A Rapid High-throughput Method for Mapping Ribonucleoproteins (RNPs) on Human pre-mRNA
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A Rapid High-throughput Method for Mapping Ribonucleoproteins (RNPs) on Human pre-mRNA

Published on: December 2, 2009

High-confidence coding and noncoding transcriptome maps.

Bo-Hyun You1, Sang-Ho Yoon1, Jin-Wu Nam1,2,3

  • 1Department of Life Science, College of Natural Sciences, Hanyang University, Seoul 133791, Republic of Korea.

Genome Research
|April 12, 2017
PubMed
Summary
This summary is machine-generated.

This study introduces CAFE, a new pipeline that improves transcriptome maps by orienting unstranded RNA sequencing (RNA-seq) reads. CAFE enhances transcript assembly accuracy and aids in discovering novel long noncoding RNAs (lncRNAs).

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Rup (RNA-seq Usability Assessment Pipeline) - Quality Control for Bulk RNA-seq Experiments in Eukaryotes

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Area of Science:

  • Genomics
  • Transcriptomics
  • Bioinformatics

Background:

  • High-throughput RNA sequencing (RNA-seq) has revealed vast eukaryotic transcriptomes.
  • Transcriptome maps remain incomplete due to unstranded reads and missing boundary information.
  • Improving RNA-seq data usability is crucial for accurate transcriptome assembly.

Purpose of the Study:

  • To develop a high-performing transcriptome assembly pipeline (CAFE).
  • To enhance transcriptome maps by orienting unstranded RNA-seq reads and integrating boundary information.
  • To expand the discovery of novel long noncoding RNAs (lncRNAs).

Main Methods:

  • Developed the CAFE pipeline for transcriptome assembly.
  • Utilized maximum likelihood estimation to orient unstranded RNA-seq reads.
  • Integrated transcription start site and cleavage/polyadenylation site information.

Main Results:

  • CAFE significantly improved transcriptome assemblies from both stranded and unstranded RNA-seq data.
  • Successfully oriented approximately 220 billion unstranded reads from large-scale datasets.
  • Generated more accurate transcriptome maps and a comprehensive lncRNA catalog with thousands of novel lncRNAs.

Conclusions:

  • CAFE pipeline enhances the accuracy and completeness of transcriptome maps.
  • The method effectively leverages unstranded RNA-seq data for improved transcript assembly.
  • Facilitates comprehensive analysis of noncoding genomes and discovery of novel lncRNAs.