Quantification of proteins from proteomic analysis

Research output: Chapter in Book/Report/Conference proceedingEntry for encyclopedia/dictionary/reference book

Abstract

After protein identification, the quantification of proteins is one of the fundamental applications of proteomics. Accurate quantification has the potential to yield insights of the biology of organisms and most especially the reaction to changes in the internal or external environment. Mass spectrometry and subsequent informatics has also played a significant role in revolutionising, allowing thousands of proteins to be quantified in a single experiment. This article briefly discusses the most commonly used protein quantification methodologies in proteomics and provides a worked case study of protein quantification analysis using freely available tools of publicly available Data Independent Acquisition mass spectrometry (DIA-MS) data.
Original languageEnglish
Title of host publicationEncyclopedia of bioinformatics and computational biology
Subtitle of host publicationABC of Bioinformatics
EditorsMario Cannataro, Bruno Gaeta, Mohammad Asif Khan
Place of PublicationAmsterdam; Oxford; Cambridge
PublisherElsevier
Pages871-890
Number of pages20
Volume3
ISBN (Electronic)9780128114322
ISBN (Print)9780128114148
DOIs
Publication statusPublished - 2019

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Bibliographical note

Editors-in-chief: Shoba Ranganathan, Kenta Nakai, Christian Schönbach, Michael Gribskov.

Keywords

  • Bioinformatics
  • Protein quantification
  • Data-independent acquisition
  • Bioinformatics analysis
  • Expression analysis
  • Quantitative proteomics
  • Statistical analysis
  • Reaction monitoring
  • Mass spectrometry
  • Label-free quantification
  • Up/down regulation

Cite this

Noor, Z., Adhikari, S., Ranganathan, S., & Mohamedali, A. (2019). Quantification of proteins from proteomic analysis. In M. Cannataro, B. Gaeta, & M. Asif Khan (Eds.), Encyclopedia of bioinformatics and computational biology: ABC of Bioinformatics (Vol. 3, pp. 871-890). Amsterdam; Oxford; Cambridge: Elsevier. https://doi.org/10.1016/B978-0-12-809633-8.20677-8