Department of Computer Science
 Rutgers University

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Analysis of fused in-situ hybridization and gene expression data

L. Opitz, A. Schliep and S. Posch

In Advances in Data Analysis, Springer, 577–584, 2007. Proceedings of the GfKl 2006.

To understand transcriptional regulation during development a detailed analysis of gene expression is needed. In-situ hybridization experiments measure the spatial distribution of mRNA-molecules and thus complement DNA-microarray experiments. This is of very high biological relevance, as co-location is a necessary condition for possible molecular interactions. We use publicly available in-situ data from embryonal development of Drosophila and derive a co-location index for pairs of genes. Our image processing pipeline for in-situ images provides a simpler alternative for the image processing part at comparable performance compared to published prior work. We formulate a mixture model which can use the pair-wise co-location indices as constraints in a mixture estimation on gene expression time-courses.