Name
Abstract | ||
|---|---|---|
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 cis-regulatory 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 both global and local matching results. We further develop a voting scheme to search for genes with similar spatial staining patterns over the time course of embryo development. To evaluate the effectiveness of our approach, we compare it with several global image matching schemes and a controlled vocabulary method. We then apply our method to 4400 images of 136 genes to detect potentially co-regulated genes that have similar spatio-temporal patterns, using expert-annotation to evaluate our results. |
Year | DOI | Venue |
|---|---|---|
2004 | 10.1145/974614.974636 | RECOMB |
Keywords | DocType | ISBN |
2-dimensional Gaussian kernel,quantized image,hybrid scoring method,local matching result,controlled vocabulary method,global level,global image,local level,matching trait,blob-set matching method,drosophila embryo,situ mRNA expression pattern | Conference | 1-58113-755-9 |
Citations | PageRank | References |
9 | 0.74 | 5 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hanchuan Peng | 1 | 9 | 0.74 |
| Eugene Myers | 2 | 3164 | 496.92 |