Targeted protein-omic methods are bridging the gap between proteomic and hypothesis-driven protein analysis approaches

Expert Rev Proteomics. 2011 Oct;8(5):565-75. doi: 10.1586/epr.11.49.


While proteomic methods have illuminated many areas of biological protein space, many fundamental questions remain with regard to systems-level relationships between mRNAs, proteins and cell behaviors. While mass spectrometric methods offer a panoramic picture of the relative expression and modification of large numbers of proteins, they are neither optimal for the analysis of predefined targets across large numbers of samples nor for assessing differences in proteins between individual cells or cell compartments. Conversely, traditional antibody-based methods are effective at sensitively analyzing small numbers of proteins across small numbers of conditions, and can be used to analyze relative differences in protein abundance and modification between cells and cell compartments. However, traditional antibody-based approaches are not optimal for analyzing large numbers of protein abundances and modifications across many samples. In this article, we will review recent advances in methodologies and philosophies behind several microarray-based, intermediate-level, 'protein-omic' methods, including a focus on reverse-phase lysate arrays and micro-western arrays, which have been helpful for bridging gaps between large- and small-scale protein analysis approaches and have provided insight into the roles that protein systems play in several biological processes.

Publication types

  • Research Support, N.I.H., Extramural
  • Review

MeSH terms

  • Animals
  • Cell Physiological Phenomena
  • Computational Biology
  • Genome-Wide Association Study / methods
  • Humans
  • Mass Spectrometry / methods*
  • Protein Array Analysis / methods
  • Proteins / analysis*
  • Proteins / immunology
  • Proteomics / methods*
  • Quantitative Trait Loci
  • RNA, Messenger / analysis*
  • Systems Biology / methods


  • Proteins
  • RNA, Messenger