Automating Gene Expression Annotation for Mouse Embryo

L. Han, J. van Hemert, R. Baldock, M. Atkinson

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.
Original languageEnglish
Title of host publicationAdvanced Data Mining and Applications
Subtitle of host publication5th International Conference, ADMA 2009, Beijing, China, August 17-19, 2009. Proceedings
PublisherSpringer-Verlag GmbH
Pages469-478
Number of pages10
ISBN (Print)978-3-642-03347-6
DOIs
Publication statusPublished - 2009

Publication series

NameLecture Notes in Computer Science
PublisherSpringer Berlin / Heidelberg
Volume5678
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Keywords

  • Wavelet Transform
  • Pattern Recognition
  • Mouse Embryo
  • Gene Expression

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