title: DNA microarray stochastic model.
abstract: A stochastic model of the DNA microarray image pixels is presented. The model includes spot pixel intensity distribution, interpixel correlations and the intensity distribution of background noise. The data is indicative of a small exponential additive noise process and a larger Gaussian fluctuation that scales with spot intensity. Correlations are observed among pixels in the spot and between test and control images. The correlated fluctuations may be attributed to variations across each spot in the amount of DNA placed on the spot during the array fabrication process. The model may be used in gene expression estimation algorithm development, both to test new algorithms through simulation and to develop optimum algorithms. The model should also be easily adapted to new array based technologies in proteomics.
authors.affiliation: Institute for Biomaterials and Bioengineering, Department of Electrical and Computer Engineering, University of Toronto, Toronto, ON M5S 3G9, Canada. stephen.davies@utoronto.ca
authors.forename: Stephen W
authors.initials: SW
authors.lastname: Davies
authors.forename: David A
authors.initials: DA
authors.lastname: Seale
mesh_terms: D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D020869:Gene Expression Profiling / Q000379:methods*; D017404:In Situ Hybridization, Fluorescence / Q000379:methods*; D008957:Models, Genetic; D015233:Models, Statistical; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D013269:Stochastic Processes