In situ staining of a target mRNA at several time points during the development of a D. melanogaster embryo gives one a detailed spatio-temporal view of the expression pattern of a given gene. We have developed algorithms and software for analyzing a database of such images with the goal of being able to identify coordinately expressed genes and further our understanding of cisregulatory control during embryogenesis. Our approach combines measures of similarity at both the global and local levels, based on Gaussian Mixture Model (GMM) decompositions. At the global level, the observed distribution of pixel values is quantized using an adaptive GMM decomposition and then quantized images are compared using mutual information. At the local level, we decompose quantized images into 2-dimensional Gaussian kernels or "blobs" and then develop a blob-set matching method to search for the best matching traits in different pattern-images. A hybrid scoring method is proposed to combine...
Hanchuan Peng, Eugene W. Myers