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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...
Protein Networks02:26

Protein Networks

An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...

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Updated: Jun 28, 2026

Navigating the Mass Spectrometry-Based Proteomic Data Using Free Computational Tools
07:01

Navigating the Mass Spectrometry-Based Proteomic Data Using Free Computational Tools

Published on: August 19, 2025

Information management for proteomics: a perspective.

Marc R Wilkins1, Jonathan W Arthur, F Keith Junius

  • 1Proteome Systems Ltd, North Ryde, NSW 1670, Australia. m.wilkins@unsw.edu.au

Expert Review of Proteomics
|October 22, 2008
PubMed
Summary
This summary is machine-generated.

Managing proteomics data is crucial for research. This article discusses developing a commercial proteomic information management system to address challenges in data acquisition, storage, and analysis for researchers.

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Last Updated: Jun 28, 2026

Navigating the Mass Spectrometry-Based Proteomic Data Using Free Computational Tools
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Published on: August 19, 2025

TMT Sample Preparation for Proteomics Facility Submission and Subsequent Data Analysis
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Published on: June 8, 2020

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Published on: November 13, 2021

Area of Science:

  • Proteomics
  • Bioinformatics
  • Data Science

Background:

  • Proteomics generates vast amounts of data requiring robust management.
  • Effective data storage and management are essential for proteomic research continuity and future analysis.
  • Current challenges hinder the accessibility and usability of proteomic datasets.

Purpose of the Study:

  • To detail the development of a commercial proteomic information management system.
  • To identify and address key challenges in managing proteomics data.
  • To provide insights into data management strategies for researchers.

Main Methods:

  • Development of a commercial proteomic information management system.
  • Analysis of challenges in data acquisition, workflow management, and data security.
  • Implementation of solutions for data permanence, interpretation, and analysis.

Main Results:

  • A comprehensive system for managing proteomic information was developed.
  • Solutions were identified for critical issues including data acquisition, workflow, permanence, and security.
  • The system facilitates data interpretation and analysis for researchers.

Conclusions:

  • Effective data management is vital for advancing proteomics research.
  • The developed system offers solutions to common challenges faced by researchers.
  • This work has significant implications for both academic and industry proteomics.