Computational analysis of 3D mouse embryo images

Invited Talk presented on April 19, 2010 by Ruben Schilling at Department of Computer Science & BioMaPS Institute for Quantitative Biology Rutgers, The State University of New Jersey, Piscataway, NJ, USA.

Abstract: Classically the spatially resolved analysis of genetic transcription rates is performed on textual annotations. The annotations are prepared from observations based on photographs or physical slices of in-situ stained subjects. Contrary to this approach is the quantitative analysis of expression patterns directly on 3D image data, that fits important categories of patterns better. We are working on an instrumentarium for the inter-subject registration and quantitative analysis of staged 3D mouse embryo images. The amount of variability in this interesting data is high. The registration is the basis for the direct, quantitative analysis of expression patterns. Our goal is an atlas of fused in-situ patterns, such that the latter can be clustered into functional groups and co-expression network structure could be proposed.

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