Towards automatic analysis of DNA microarrays

C. Uehara, I. Kakadiaris

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Scopus citations


In this paper we present a computational framework that provides the automatic analysis of spotted DNA microarray image data. The challenges are in providing an accurate representation of microarray hybridization observations while minimizing user interaction. To obtain this, we need to segment the observation data and subsequent correction for true hybridization level measurements must be accomplished against the backdrop of signal noise, background signal variation, and spatial non-uniformity in the array layout. With the requirements of automation and accuracy, an approach based on data-driven denoising, array addressing, background estimation, and spot segmentation was developed We proceeded to validate our approach on synthetic data as well as the publicly available raw and analyzed microarray data from the published Stanford yeast cell cycle analysis project. Spot mean and total intensities were examined as well as spot background estimates. By minimizing the user role, a main bottleneck in microarray data analysis is removed, allowing for more immediate analysis of large observation data sets. Our implementation has proven to be relatively fast, and the results of our approach have been encouraging.

Original languageEnglish (US)
Title of host publicationProceedings - 6th IEEE Workshop on Applications of Computer Vision, WACV 2002
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages6
ISBN (Electronic)0769518583
StatePublished - 2002
Event6th IEEE Workshop on Applications of Computer Vision, WACV 2002 - Orlando, United States
Duration: Dec 3 2002Dec 4 2002

Publication series

NameProceedings of IEEE Workshop on Applications of Computer Vision
ISSN (Print)2158-3978
ISSN (Electronic)2158-3986


Conference6th IEEE Workshop on Applications of Computer Vision, WACV 2002
Country/TerritoryUnited States


  • Automation
  • Background noise
  • Data analysis
  • DNA computing
  • Fungi
  • Image analysis
  • Image segmentation
  • Level measurement
  • Noise level
  • Noise reduction

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Computer Science Applications


Dive into the research topics of 'Towards automatic analysis of DNA microarrays'. Together they form a unique fingerprint.

Cite this