Utilising IPG-IEF to identify differentially-expressed proteins

David I. Cantor, Harish R. Cheruku

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

Abstract

Living organisms maintain life through a complex array of protein networks which, when disturbed, lead to disease or eventual death. The key challenge for biomedical researchers endeavouring to track and understand these biological landscapes is identifying protein markers that are unique to a disease state. This can be achieved by various tools and techniques within the field of proteomics. This article explores IPG-IEF as a means for identifying differentially expressed proteins and summarises commonly utilised fractionation methods and workflows. IPG-IEF enables researchers to drill deeper into the observable proteome to identify potential disease-specific markers which may be validated by orthogonal quantification methods such as ELISA, SRM, MRM or SWATH.

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
Pages891-910
Number of pages20
Volume3
ISBN (Electronic)9780128114322
ISBN (Print)9780128114148
DOIs
Publication statusPublished - 2019

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Keywords

  • Cancer
  • Disease
  • IPG-IEF
  • Label-free
  • Low-abundance
  • Mass spectrometry
  • Profiling
  • Proteomics
  • Strategies

Cite this

Cantor, D. I., & Cheruku, H. R. (2019). Utilising IPG-IEF to identify differentially-expressed proteins. In M. Cannataro, B. Gaeta, & M. A. Khan (Eds.), Encyclopedia of bioinformatics and computational biology: ABC of Bioinformatics (Vol. 3, pp. 891-910). Amsterdam; Oxford; Cambridge: Elsevier. https://doi.org/10.1016/B978-0-12-809633-8.20448-2