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Related Concept Videos

Proteomics01:33

Proteomics

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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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Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...
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Tandem mass spectrometry is a technique that uses multiple mass analyzers in series to obtain a higher selectivity and signal-to-noise ratio for the analyte. Instruments with multiple analyzers separated by an interaction cell enable secondary fragmentation and selected study of the fragment ions.
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Updated: Oct 17, 2025

TMT Sample Preparation for Proteomics Facility Submission and Subsequent Data Analysis
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TMT Sample Preparation for Proteomics Facility Submission and Subsequent Data Analysis

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A proteomics sample metadata representation for multiomics integration and big data analysis.

Chengxin Dai1, Anja Füllgrabe2, Julianus Pfeuffer3,4

  • 1Chongqing Key Laboratory of Big Data for Bio Intelligence, Chongqing University of Posts and Telecommunications, Chongqing, China.

Nature Communications
|October 7, 2021
PubMed
Summary
This summary is machine-generated.

A new standard, MAGE-TAB-Proteomics, is proposed to organize public proteomics data. This aims to improve data understanding, reproducibility, and reanalysis of valuable scientific findings.

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Area of Science:

  • Proteomics
  • Bioinformatics
  • Data Standardization

Background:

  • Public proteomics data is growing rapidly.
  • Lack of standardized metadata hinders data understanding and reanalysis.
  • Existing formats do not fully support proteomics data integration.

Purpose of the Study:

  • To adapt the transcriptomics data format MAGE-TAB for proteomics sample metadata.
  • To establish a standardized representation for proteomics metadata.
  • To enhance the usability and accessibility of public proteomics datasets.

Main Methods:

  • Development of MAGE-TAB-Proteomics.
  • Implementation via a crowdsourcing project for manual curation.
  • Curation of over 200 public proteomics datasets.
  • Description of tools and libraries for metadata validation and submission to PRIDE.

Main Results:

  • Successful adaptation of MAGE-TAB for proteomics metadata.
  • Manual curation of a substantial number of public datasets.
  • Availability of tools for metadata management and submission.
  • Establishment of a crowdsourced approach for data curation.

Conclusions:

  • MAGE-TAB-Proteomics provides a standardized format for proteomics metadata.
  • The developed tools facilitate data validation and submission to repositories like PRIDE.
  • These advancements are expected to improve reproducibility and reanalysis of public proteomics data.