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Related Concept Videos

Proteomics01:33

Proteomics

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 proteomics...

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Related Experiment Video

Updated: Jul 17, 2026

Mass Spectrometry-Based Proteomics Analyses Using the OpenProt Database to Unveil Novel Proteins Translated from Non-Canonical Open Reading Frames
07:38

Mass Spectrometry-Based Proteomics Analyses Using the OpenProt Database to Unveil Novel Proteins Translated from Non-Canonical Open Reading Frames

Published on: April 11, 2019

Automated reporting from gel-based proteomics experiments using the open source Proteios database application.

Fredrik Levander1, Morten Krogh, Kristofer Wårell

  • 1Protein Technology, Lund University, BMC D13, Lund, Sweden. Fredrik.Levander@elmat.lth.se

Proteomics
|February 14, 2007
PubMed
Summary

This study introduces automated data assembly for gel-based proteomics workflows using Proteios software. It enhances protein identification reporting to meet journal standards and manage false discovery rates effectively.

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Last Updated: Jul 17, 2026

Mass Spectrometry-Based Proteomics Analyses Using the OpenProt Database to Unveil Novel Proteins Translated from Non-Canonical Open Reading Frames
07:38

Mass Spectrometry-Based Proteomics Analyses Using the OpenProt Database to Unveil Novel Proteins Translated from Non-Canonical Open Reading Frames

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Resolving Affinity Purified Protein Complexes by Blue Native PAGE and Protein Correlation Profiling
09:35

Resolving Affinity Purified Protein Complexes by Blue Native PAGE and Protein Correlation Profiling

Published on: April 1, 2017

Area of Science:

  • Proteomics
  • Bioinformatics
  • Computational Biology

Background:

  • Data assembly in proteomics workflows presents significant challenges, often acting as a bottleneck.
  • Accurate protein identification is crucial, yet complicated by false-positive and false-negative results.
  • Increasing demand exists for detailed reporting of protein identification data in publications.

Purpose of the Study:

  • To automate the assembly of data from gel-based proteomics workflows.
  • To enhance Proteios software for improved protein identification reporting.
  • To address the need for transparent and reliable protein identification data.

Main Methods:

  • Expansion of the open-source Proteios software.
  • Implementation of automated data assembly for proteomics workflows.
  • Development of customizable protein identification reports with user-defined false positive ratios.

Main Results:

  • Proteios software now automates the integration of data from various stages of gel-based proteomics.
  • Generated reports include all necessary information for publication in proteomics journals.
  • Automatic calculation of score cut-offs based on user-specified false positive ratios is now possible.
  • For multi-engine searches, score thresholds correlating to error rates are calculated for overlapping protein identifications.

Conclusions:

  • The enhanced Proteios software effectively automates proteomics data assembly and reporting.
  • The software facilitates compliance with journal requirements for protein identification data.
  • Proteios provides robust tools for managing and reporting protein identification accuracy, including false discovery rates.