Cookies on this website

We use cookies to ensure that we give you the best experience on our website. If you click 'Accept all cookies' we'll assume that you are happy to receive all cookies and you won't see this message again. If you click 'Reject all non-essential cookies' only necessary cookies providing core functionality such as security, network management, and accessibility will be enabled. Click 'Find out more' for information on how to change your cookie settings.

This letter explores the potential of Bayesian signal processing for improved modeling of microarray images and enhanced estimation of gene expression ratios. Building upon our earlier work, we describe a novel elliptical spot shape model, with a Bayesian model-fitting method. The analysis of gene replicates at the image-modeling level is also briefly discussed. Prior knowledge from neighboring spots is encompassed in the framework of a Markov random field, potentially enhancing the accuracy and reliability of ratio estimates. The techniques may be particularly beneficial for irregular, overlapping, damaged, saturated, or weakly expressed spots. © 2007 IEEE.

Original publication




Journal article


IEEE Signal Processing Letters

Publication Date





653 - 656