Optimal Estimation of Gene Expression Levels in Microarrays

Microarray technology relies on the hybridization process, which is stochastic in nature. However, current measurement and detection techniques do not fully exploit this stochastic nature nor do they consider it in data analysis. In this paper, we propose a probabilistic model of the DNA microarray and employ this model for optimal estimation of gene expression levels. Simulation results indicate significant improvement in the reliability of the estimates over the direct readout of the data.