Noise factor analysis for cDNA microarrays

Yoganand Balagurunathan, Naisyin Wang, Edward R. Dougherty, Danh Nguyen, Yidong Chen, Michael L. Bittner, Jeffrey Trent, Raymond Carroll

Research output: Contribution to journalArticlepeer-review

21 Scopus citations


A microarray-image model is used that takes into account many factors, including spot morphology, signal strength, background fluorescent noise, and shape and surface degradation. The model yields synthetic images whose appearance and quality reflect that of real microarray images. The model is used to link noise factors to the fidelity of signal extraction with respect to a standard image-extraction algorithm. Of particular interest is the identification of the noise factors and their interactions that significantly degrade the ability to accurately detect the true gene-expression signal. This study uses statistical criteria in conjunction with the simulation of various noise conditions to better understand the noise influence on signal extraction for cDNA microarray images. It proposes a paradigm that is implemented in software. It specifically considers certain kinds of noise in the noise model and sets these at certain levels; however, one can choose other types of noise or use different noise levels. In sum, it develops a statistical package that can work in conjunction with the existing image simulation toolbox.

Original languageEnglish (US)
Pages (from-to)663-678
Number of pages16
JournalJournal of biomedical optics
Issue number4
StatePublished - Jul 2004
Externally publishedYes


  • Experimental design
  • Factorial experiment
  • Image simulation
  • Signal detection
  • cDNA microarray

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Atomic and Molecular Physics, and Optics
  • Biomedical Engineering
  • Biomaterials


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