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Related Concept Videos

Ribosome Profiling02:24

Ribosome Profiling

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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...
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Proteomics01:33

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A proteome is the entire set of proteins that a cell type produces. We can study proteomes using the knowledge of genomes because genes code for mRNAs, and the mRNAs encode proteins. Although mRNA analysis is a step in the right direction, not all mRNAs are translated into proteins.
Proteomics is the study of proteomes' function. It involves the large-scale systematic study of the proteome to denote the protein complement expressed by a genome. Scientist Mark Wilkins coined the term...
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Related Experiment Video

Updated: Apr 19, 2026

Deep Proteome Profiling by Isobaric Labeling, Extensive Liquid Chromatography, Mass Spectrometry, and Software-assisted Quantification
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PROTEOFORMER: deep proteome coverage through ribosome profiling and MS integration.

Jeroen Crappé1, Elvis Ndah2, Alexander Koch1

  • 1Lab of Bioinformatics and Computational Genomics, Department of Mathematical Modeling, Statistics and Bioinformatics, Faculty of Bioscience Engineering, Ghent University, Ghent, Belgium.

Nucleic Acids Research
|December 17, 2014
PubMed
Summary
This summary is machine-generated.

We developed PROTEOFORMER to improve mass spectrometry-based proteomics by using ribosome profiling data. This tool enhances protein identification rates and detects novel translation events, advancing proteome analysis.

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Area of Science:

  • Proteomics
  • Molecular Biology
  • Bioinformatics

Background:

  • Integrating mRNA sequencing (mRNA-seq) with mass spectrometry (MS)-based proteomics is challenging due to complex mRNA translation regulation.
  • Existing methods struggle to construct comprehensive protein sequence databases from mRNA-seq data, limiting proteomic discovery.

Purpose of the Study:

  • To develop a computational tool, PROTEOFORMER, for processing ribosome profiling data.
  • To enable the construction of complete protein synthesis-based sequence databases for MS-based proteomics.
  • To enhance the identification of novel proteoforms and translation events.

Main Methods:

  • Developed PROTEOFORMER, a pipeline for analyzing ribosome profiling data.
  • Implemented a translation initiation site calling algorithm to delineate open reading frames (ORFs).
  • Generated genome-wide visualization of ribosome occupancy and protein synthesis.

Main Results:

  • Increased overall protein identification rates by 3% (improved) and 11% (new) in human and mouse, respectively.
  • Enabled proteome-wide detection of 5'-extended proteoforms.
  • Facilitated the discovery of upstream ORF translation and near-cognate translation start sites.

Conclusions:

  • PROTEOFORMER effectively processes ribosome profiling data to build comprehensive protein sequence databases.
  • This approach significantly improves protein identification in MS-based proteomics.
  • The tool facilitates the discovery of previously uncharacterized aspects of the proteome.