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Proceedings Paper

Visualization and analysis of 3D gene expression patterns in zebrafish using web services
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Paper Abstract

The analysis of patterns of gene expression patterns analysis plays an important role in developmental biology and molecular genetics. Visualizing both quantitative and spatio-temporal aspects of gene expression patterns together with referenced anatomical structures of a model-organism in 3D can help identifying how a group of genes are expressed at a certain location at a particular developmental stage of an organism. In this paper, we present an approach to provide an online visualization of gene expression data in zebrafish (Danio rerio) within 3D reconstruction model of zebrafish in different developmental stages. We developed web services that provide programmable access to the 3D reconstruction data and spatial-temporal gene expression data maintained in our local repositories. To demonstrate this work, we develop a web application that uses these web services to retrieve data from our local information systems. The web application also retrieve relevant analysis of microarray gene expression data from an external community resource; i.e. the ArrayExpress Atlas. All the relevant gene expression patterns data are subsequently integrated with the reconstruction data of the zebrafish atlas using ontology based mapping. The resulting visualization provides quantitative and spatial information on patterns of gene expression in a 3D graphical representation of the zebrafish atlas in a certain developmental stage. To deliver the visualization to the user, we developed a Java based 3D viewer client that can be integrated in a web interface allowing the user to visualize the integrated information over the Internet.

Paper Details

Date Published: 24 January 2012
PDF: 11 pages
Proc. SPIE 8294, Visualization and Data Analysis 2012, 829412 (24 January 2012); doi: 10.1117/12.909810
Show Author Affiliations
D. Potikanond, Leiden Univ. (Netherlands)
F. J. Verbeek, Leiden Univ. (Netherlands)


Published in SPIE Proceedings Vol. 8294:
Visualization and Data Analysis 2012
Pak Chung Wong; David L. Kao; Ming C. Hao; Chaomei Chen; Robert Kosara; Mark A. Livingston; Jinah Park; Ian Roberts, Editor(s)

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