Contour Extraction of Drosophila Embryos
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Inferring gene interaction networks from ISH images via kernelized graphical models
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part VI
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Motivation: Microarray profiling of mRNA abundance is often ill suited for temporal–spatial analysis of gene expressions in multicellular organisms such as Drosophila. Recent progress in image-based genome-scale profiling of whole-body mRNA patterns via in situ hybridization (ISH) calls for development of accurate and automatic image analysis systems to facilitate efficient mining of complex temporal–spatial mRNA patterns, which will be essential for functional genomics and network inference in higher organisms. Results: We present SPEX2, an automatic system for embryonic ISH image processing, which can extract, transform, compare, classify and cluster spatial gene expression patterns in Drosophila embryos. Our pipeline for gene expression pattern extraction outputs the precise spatial locations and strengths of the gene expression. We performed experiments on the largest publicly available collection of Drosophila ISH images, and show that our method achieves excellent performance in automatic image annotation, and also finds clusters that are significantly enriched, both for gene ontology functional annotations, and for annotation terms from a controlled vocabulary used by human curators to describe these images. Availability: Software will be available at http://www.sailing.cs.cmu.edu/ Contact: epxing@cs.cmu.edu Supplementary information:Supplementary data are avilable at Bioinformatics online.