Abstract
Algorithms for performing feature extraction and normalization on high-density oligonucleotide gene expression arrays, have not been fully explored, and the impact these algorithms have on the downstream analysis is not well understood. Advances in such low-level analysis methods are essential to increase the sensitivity and specificity of detecting whether genes are present and/or differentially expressed. We have developed and implemented a number of algorithms for the analysis of expression array data in a software application, the DNA-Chip Analyzer (dChip). In this report, we describe the algorithms for feature extraction and normalization, and present validation data and comparison results with some of the algorithms currently in use.
Keywords
Normalization (sociology)Database normalizationComputer scienceFeature extractionOligonucleotideAlgorithmPattern recognition (psychology)Data miningArtificial intelligenceGeneBiologyGenetics
Affiliated Institutions
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Publication Info
- Year
- 2001
- Type
- article
- Volume
- 84
- Issue
- S37
- Pages
- 120-125
- Citations
- 285
- Access
- Closed
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Cite This
Eric E. Schadt,
Li Cheng,
Byron Ellis
et al.
(2001).
Feature extraction and normalization algorithms for high-density oligonucleotide gene expression array data.
Journal of Cellular Biochemistry
, 84
(S37)
, 120-125.
https://doi.org/10.1002/jcb.10073
Identifiers
- DOI
- 10.1002/jcb.10073