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Related Concept Videos

Proteomics01:33

Proteomics

7.3K
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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Peptide Identification Using Tandem Mass Spectrometry01:33

Peptide Identification Using Tandem Mass Spectrometry

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Tandem mass spectrometry, also known as MS/MS or MS2, is an analytical technique that employs two mass analyzers. Essentially it is a series of mass spectrometers that helps isolate a particular biomolecule and then helps study its chemical properties.
This technique helps gather information regarding the protein from which the peptide was obtained and to study the peptides’ amino acid sequence. Identifying peptides from a complex mixture is an important component of the growing field of...
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Related Experiment Video

Updated: Jun 18, 2025

Deep Proteome Profiling by Isobaric Labeling, Extensive Liquid Chromatography, Mass Spectrometry, and Software-assisted Quantification
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OmicScope unravels systems-level insights from quantitative proteomics data.

Guilherme Reis-de-Oliveira1,2, Victor Corasolla Carregari3, Gabriel Rodrigues Dos Reis de Sousa4

  • 1Laboratory of Neuroproteomics, Department of Biochemistry and Tissue Biology, Institute of Biology, University of Campinas (UNICAMP), Campinas, SP, Brazil. guioliveirareis@gmail.com.

Nature Communications
|August 2, 2024
PubMed
Summary

OmicScope offers a comprehensive solution for quantitative proteomics data analysis, simplifying complex workflows. This tool enhances data processing, differential analysis, and systems biology insights for researchers.

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Area of Science:

  • Proteomics
  • Bioinformatics
  • Systems Biology

Background:

  • Shotgun proteomics generates complex data requiring integrated tools for analysis.
  • Existing pipelines often lack comprehensive features for quantitative proteomics.
  • Researchers need efficient methods for data pre-processing, differential analysis, and pathway enrichment.

Purpose of the Study:

  • To introduce OmicScope, an integrated software solution for quantitative proteomics data analysis.
  • To provide a user-friendly platform for pre-processing, differential analysis, and systems biology approaches.
  • To enhance the accessibility and efficiency of proteomics data interpretation for researchers.

Main Methods:

  • OmicScope integrates data pre-processing (replicate joining, normalization, imputation).
  • It performs differential proteomics analysis for static and longitudinal designs.
  • Utilizes Enrichr for Over Representation Analysis (ORA) and Gene Set Enrichment Analysis (GSEA).
  • Includes a Nebula module for meta-analysis of independent datasets.
  • Offers a data visualization toolkit.

Main Results:

  • OmicScope handles diverse data formats and performs essential pre-processing steps.
  • Enables robust differential proteomics analysis for various experimental designs.
  • Facilitates pathway enrichment analysis using extensive databases.
  • The Nebula module allows for integrated meta-analysis, providing systems-level insights.
  • OmicScope is available as a Python package and web application.

Conclusions:

  • OmicScope provides an efficient, high-quality pipeline for quantitative proteomics.
  • It democratizes proteomics analysis by offering accessible tools and comprehensive functionalities.
  • The integrated approach aids in generating enriched biological insights from complex datasets.