Title :
Bayesian modelling of microarray images
Author :
Ridgway, Gerard ; Godsill, Simon
Author_Institution :
Dept. of Eng., Cambridge Univ., Cambridge
Abstract :
We examine the use of Bayesian signal processing to improve the modelling of microarray images, and ultimately the estimation of gene expression ratios. A novel elliptical spot shape model is presented, with a Bayesian image modelling method. Prior knowledge from neighbouring 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.
Keywords :
Bayes methods; biology computing; cellular biophysics; genetics; image processing; molecular biophysics; Bayesian modelling; Bayesian signal processing; Markov random field; elliptical spot shape model; gene expression; microarray images; Bayesian methods; Gene expression; Histograms; Image analysis; Image segmentation; Markov random fields; Parametric statistics; Principal component analysis; Shape; Signal processing;
Conference_Titel :
Genomic Signal Processing and Statistics, 2006. GENSIPS '06. IEEE International Workshop on
Conference_Location :
College Station, TX
Print_ISBN :
1-4244-0384-7
Electronic_ISBN :
1-4244-0385-5
DOI :
10.1109/GENSIPS.2006.353146
