e-learning

Clinical Metaproteomics 4: Quantitation

Abstract

The next step of the clinical metaproteomics workflow is the quantification workflow. Running a quantification workflow in proteomics is essential for several critical purposes. It allows researchers to measure and compare the abundance of proteins or peptides in biological samples, offering valuable insights into biomarker discovery, comparative analysis, and differential expression studies. Quantitative proteomics helps reveal the functional roles of proteins, the stoichiometry of protein complexes, and the effects of drugs on protein expression in pharmacological studies. Additionally, it serves as a quality control measure, validating initial protein identifications, and providing data normalization for increased accuracy. Quantitative data are indispensable for hypothesis testing, systems biology, and their clinical relevance in areas such as disease diagnosis, prognosis, and therapeutic decision-making. In summary, the quantitation workflow in proteomics is a cornerstone for deciphering the complexities of protein expression and regulation, facilitating a wide array of biological and clinical applications.

About This Material

This is a Hands-on Tutorial from the GTN which is usable either for individual self-study, or as a teaching material in a classroom.

Questions this will address

  • How to perform quantitation?

Learning Objectives

  • Perform quantitation using MaxQuant and extract microbial and human proteins and peptides.

Licence: Creative Commons Attribution 4.0 International

Keywords: Microbiome, label-TMT11

Target audience: Students

Resource type: e-learning

Version: 0

Status: Active

Prerequisites:

  • Introduction to Galaxy Analyses
  • Proteomics

Learning objectives:

  • Perform quantitation using MaxQuant and extract microbial and human proteins and peptides.

Date modified: 2025-08-30

Date published: 2025-08-30

Authors: Dechen Bhuming, Katherine Do, Subina Mehta

Contributors: Pratik Jagtap, Timothy J. Griffin

Scientific topics: Metagenomics, Microbial ecology


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