Analysis of gene expression patterns within an organism plays a critical role in associating genes
with biological processes in both health and disease. During embryonic development the analysis and
comparison of different gene expression patterns allows biologists to identify candidate genes that may
regulate the formation of normal tissues and organs and to search for genes associated with congenital
diseases. No two individual embryos, or organs, are exactly the same shape or size so comparing spatial
gene expression in one embryo to that in another is difficult. We will present our efforts in comparing
gene expression data collected using both volumetric and projection approaches. Volumetric data is
highly accurate but difficult to process and compare. Projection methods use UV mapping to align texture
maps to standardized spatial frameworks. This approach is less accurate but is very rapid and requires
very little processing. We have built a database of over 180 3D models depicting gene expression
patterns mapped onto the surface of spline based embryo models. Gene expression data in different
models can easily be compared to determine common regions of activity. Visualization software, both
Java and OpenGL optimized for viewing 3D gene expression data will also be demonstrated.
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