Automating Gene Expression Annotation for Mouse Embryo

Authors:
Liangxiu Han;Jano Hemert;Richard Baldock;Malcolm Atkinson
Affiliations:
National eScience Centre, School of Informatics, University of Edinburgh, UK;National eScience Centre, School of Informatics, University of Edinburgh, UK;MRC Human Genetics Unit, Institute of Genetic and Molecular Medicine, Edinburgh, UK;National eScience Centre, School of Informatics, University of Edinburgh, UK
Venue:
ADMA '09 Proceedings of the 5th International Conference on Advanced Data Mining and Applications
Year:
2009

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Abstract

It is of high biomedical interest to identify gene interactions and networks that are associated with developmental and physiological functions in the mouse embryo. There are now large datasets with both spatial and ontological annotation of the spatio-temporal patterns of gene-expression that provide a powerful resource to discover potential mechanisms of embryo organisation. Ontological annotation of gene expression consists of labelling images with terms from the anatomy ontology for mouse development. Current annotation is made manually by domain experts. It is both time consuming and costly. In this paper, we present a new data mining framework to automatically annotate gene expression patterns in images with anatomic terms. This framework integrates the images stored in file systems with ontology terms stored in databases, and combines pattern recognition with image processing techniques to identify the anatomical components that exhibit gene expression patterns in images. The experimental result shows the framework works well.