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Nucleic Acids Research 2004 32(13):3807-3814; doi:10.1093/nar/gkh718
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Published online 20 July 2004

Nucleic Acids Research, Vol. 32 No. 13 © Oxford University Press 2004; all rights reserved

Mathematical algorithm for discovering states of expression from direct genetic comparison by microarrays

Hassan M. Fathallah-Shaykh*, Bin He, Li-Juan Zhao and Aamir Badruddin

Department of Neurological Sciences, Section of Neuro-Oncology, Rush University Medical Center, 1725 West Harrison Street, Chicago, IL 60612, USA

* To whom correspondence should be addressed. Tel: +1 312 563 3563; Fax: +1 312 563 3562; Email: hfathall{at}rush.edu

Received May 11, 2004; Revised June 12, 2004; Accepted July 2, 2004

Highly specific direct genome-scale expression discovery from two biological samples facilitates functional discovery of molecular systems. Here, expression data from cDNA arrays are ranked and curve-fitted. The algorithm uses filters based on the derivatives (slopes) of the curve fits. The rules are set to (i) filter the largest number of artifactual ratios from same-to-same datasets and (ii) maximize discovery from direct comparisons of different samples. The unsupervised discovery is optimized without lowering specificity. The false discovery rates are significantly lower than other methods. The discovered states of genetic expression facilitate functional discovery and are validated by real-time RT–PCR. Better quality improves sensitivity.


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