A Concentration-Dependent Analysis Method for High Density Protein Microarrays

Ovidiu Marina, Melinda A. Biernacki, Vladimir Brusic, Catherine J. Wu

Research output: Contribution to journalArticle

14 Citations (Scopus)

Abstract

Protein microarray technology is rapidly growing and has the potential to accelerate the discovery of targets of serum antibody responses in cancer, autoimmunity and infectious disease. Analytical tools for interpreting this high-throughput array data, however, are not well-established. We developed a concentration-dependent analysis (CDA) method which normalizes protein microarray data based on the concentration of spotted probes. We show that this analysis samples a data space that is complementary to other commonly employed analyses, and demonstrate experimental validation of 92% of hits identified by the intersection of CDA with other tools. These data support the use of CDA either as a preprocessing step for a more complete proteomic microarray data analysis or as a standalone analysis method.

Original languageEnglish
Pages (from-to)2059-2068
Number of pages10
JournalJournal of Proteome Research
Volume7
Issue number5
DOIs
Publication statusPublished - May 1 2008

Keywords

  • Antigen identification
  • Immune responses
  • Protein microarray
  • Proteomic
  • Protoarray

ASJC Scopus subject areas

  • Biochemistry
  • Chemistry(all)

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