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Automating Gene Expression Annotation for Mouse Embryo

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Book cover Advanced Data Mining and Applications (ADMA 2009)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5678))

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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.

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References

  1. EURexpress II project, http://www.eurexpress.org/ee_new/project/index.html (retrieved March 08, 2009)

  2. Lecuyer, E., Yoshida, H., Parthasarathy, N., Alm, C., Babak, T., Cerovina, T., Hughes, T.R., Tomancak, P., Krause, H.M.: Global Analysis of mRNA Localization Reveals a Prominent Role in Organizing Cellular Architecture and Function. Cell 131, 174–187 (2007)

    Article  Google Scholar 

  3. Drysdale, R.: FlyBase: a database for the Drosophila research community. Methods Molec. Biol. 420, 45–59 (2008)

    Article  Google Scholar 

  4. Lein, E.S., Hawrylycz, M.J., et al.: Genome-wide atlas of gene expression in the adult mouse brain. Nature 445, 168–176 (2006)

    Article  Google Scholar 

  5. Grumbling, G., Strelets, V., Consortium, T.F.: FlyBase: anatomical data, images and queries. Nucleic Acids Research 34, D485–D488 (2006)

    Article  Google Scholar 

  6. Harmon, C.L., Ahammad, P., Hammonds, A., Weiszmann, R., Celniker, S.E., Sastry, S.S., Rubin, G.M.: Comparative Analysis of Spatial Patterns of Gene Expression in Drosophila melanogaster Imaginal Discs. In: Speed, T., Huang, H. (eds.) RECOMB 2007. LNCS (LNBI), vol. 4453, pp. 533–547. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  7. Pan, J.Y., Balan, A.G.R., Xing, E.P., Traina, A.J.M., Faloutsos, C.: Automatic Mining of Fruit Fly Embryo Images. In: Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining, pp. 693–698. ACM, New York (2006)

    Chapter  Google Scholar 

  8. Zhou, J., Peng, H.: Automatic recognition and annotation of gene expression patterns of y embryos. Bioinformatics 23(5), 589–596 (2007)

    Article  Google Scholar 

  9. Carson, J.P., Ju, T., Lu, H.-C., Thaller, C., Pallas, S.L., Crair, M.C., Warren, J., Chiu, W., Eichele, G.: A Digital Atlas to Characterize the Mouse Brain Transcriptome. PLoS Comput. Biology 1, 290–296 (2005)

    Article  Google Scholar 

  10. Jawerth, B., Sweldens, W.: An Overview of Wavelet Based Multiresolution Analyses. SIAM Review 36(2), 377–412

    Google Scholar 

  11. Stollnitz, E., DeRose, T., Salesin, D.: Wavelets for Computer Graphics. Morgan Kaufmann Publishers, Inc., San Francisco (1996)

    Google Scholar 

  12. Mallat, S.G.: A Wavelet Tour of Signal Processing. Academic Press, London (1999)

    MATH  Google Scholar 

  13. Daubechies, I.: Ten Lectures on Wavelets. SIAM, Philadelphia (1992)

    Book  MATH  Google Scholar 

  14. Duda, R.O., Hart, P.E.: Pattern Classification and Scene Analysis. Wiley, Chichester (1973)

    MATH  Google Scholar 

  15. Baldock, R., Bard, J., Burger, A., et al.: EMAP and EMAGE: A Framework for Understanding Spatially Organised Data. Neuroinformatics 1(4), 309–325 (2003)

    Article  Google Scholar 

  16. Christiansen, J.H., Yang, Y., Venkataraman, S., et al.: EMAGE: A Spatial Database of Gene Expression Patterns during Mouse Embryo Development. Nucleic Acids Research 34, D637 (2006)

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. National eScience Centre, School of Informatics, University of Edinburgh, UK

    Liangxiu Han, Jano van Hemert & Malcolm Atkinson

  2. MRC Human Genetics Unit, Institute of Genetic and Molecular Medicine, Edinburgh, UK

    Richard Baldock

Authors
  1. Liangxiu Han
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  2. Jano van Hemert
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  3. Richard Baldock
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  4. Malcolm Atkinson
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Editor information

Editors and Affiliations

  1. Knowledge Science & Engineering Institute, School of Education Technology, Beijing Normal University, Xinjiekouwai Ave. 19, 100875, Beijing, China

    Ronghuai Huang

  2. The Hong Kong University of Science and Technology, Clear Water Bay,, Hong Kong, Hong Kong

    Qiang Yang

  3. School of Computing Science, Simon Fraser University, 8888 University Drive, V5A 1S6, Burnaby, BC, Canada

    Jian Pei

  4. Faculty of Economics, University of Porto, Rua Dr. Roberto Frias, 4200-465, Porto, Portugal

    João Gama

  5. School of Information, Zhongguancum, Renmin University, 100872, Beijing, China

    Xiaofeng Meng

  6. School of Information Technology and Electrical Engineering, The University of Queensland, 4072, St. Lucia, Queensland, Australia

    Xue Li

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© 2009 Springer-Verlag Berlin Heidelberg

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Han, L., van Hemert, J., Baldock, R., Atkinson, M. (2009). Automating Gene Expression Annotation for Mouse Embryo. In: Huang, R., Yang, Q., Pei, J., Gama, J., Meng, X., Li, X. (eds) Advanced Data Mining and Applications. ADMA 2009. Lecture Notes in Computer Science(), vol 5678. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03348-3_46

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  • DOI: https://doi.org/10.1007/978-3-642-03348-3_46

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-03347-6

  • Online ISBN: 978-3-642-03348-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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