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Visual Analytics of Clinical and Genetic Datasets of Acute Lymphoblastic Leukaemia

  • Quang Vinh Nguyen
  • Andrew Gleeson
  • Nicholas Ho
  • Mao Lin Huang
  • Simeon Simoff
  • Daniel Catchpoole
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7062)

Abstract

This paper presents a novel visual analytics method that incorporates knowledge from the analysis domain so that it can extract knowledge from complex genetic and clinical data and then visualizing them in a meaningful and interpretable way. The domain experts that are both contributors to formulating the requirements for the design of the system and the actual user of the system include microbiologists, biostatisticians, clinicians and computational biologists. A comprehensive prototype has been developed to support the visual analytics process. The system consists of multiple components enabling the complete analysis process, including data mining, interactive visualization, analytical views, gene comparison. A visual highlighting method is also implemented to support the decision making process. The paper demonstrates its effectiveness on a case study of childhood cancer patients.

Keywords

Visual analytics Visualization Microarray Acute lymphoblastic leukamedia Gene expression 

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References

  1. 1.
    Goronzy, J.J., Matteson, E.L., Fulbright, J.W., et al.: Prognostic Markers of Radiographic Progression in Early Rheumatoid Arthritis. Arthritis & Rheumatism 50(1), 43–54 (2004)CrossRefGoogle Scholar
  2. 2.
    Mei, R., Galipeau, P.C., Prass, C., et al.: Genome-wide Detection of Allelic Imbalance Using Human SNPs and High-density DNA Arrays. Genome Res. 10, 1126–1137 (2000)CrossRefGoogle Scholar
  3. 3.
    Chao, S., Lihui, C.: Feature Dimension Reduction for Microarray Data Analysis Using Locally Linear Embedding. In: APBC, pp. 211–217 (2005)Google Scholar
  4. 4.
    Kaski, S., Venna, J.: Comparison of Visualization Methods for an Atlas of Gene Expression Data Sets. Information Visualization 6, 139–154 (2007)CrossRefGoogle Scholar
  5. 5.
    Prasad, T.V., Ahson, S.I.: Visualization of Microarray Gene Expression Data. Bioinformation 1, 141–145 (2006)CrossRefGoogle Scholar
  6. 6.
    Lex, A., Streit, M., Kruijff, E., Schmalstieg, D.: Caleydo: Design and Evaluation of a Visual Analysis Framework for Gene Expression Data in its Biological Context. In: 2010 IEEE Pacific Visualization Symposium, Taipeh, Taiwan, pp. 57–64 (2010)Google Scholar
  7. 7.
    Cvek, U., Rrutschl, M., Stone II, R., Syed, Z., Clifford, J.L., Sabichi, A.L.: Multidimensional Visualization Tools for Analysis of Expression Data. World Academy of Science, Engineering and Technology 54, 281–289 (2009)Google Scholar
  8. 8.
    Kilpinen, S., Autio, R., Ojala, K., et al.: Systematic Bioinformatics Analysis of Expression Levels of 17,330 Human Genes Across 9,783 Samples from 175 Types of Healthy and Pathological Tissues. Genome Biology 9(9), R139 (2008)Google Scholar
  9. 9.
    Breiman, L.: Radom Forests. Machine Learning 45, 5–32 (2001)CrossRefzbMATHGoogle Scholar
  10. 10.
    Ho, N., Morton, G., Skillicorn, D., Kennedy, P.J., Catchpoole, D.: Data-mining gene expression and genomic microarray datasets of Acute Lymphoblastic Leukaemia. In: The Lowy Symposium: Discovering Cancer Therapeutics. UNSW, Sydney (2010)Google Scholar
  11. 11.
    Golub, G.H., Van Loan, C.F.: Matrix Computations. Johns Hopkins University Press, Baltimore (1996)zbMATHGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Quang Vinh Nguyen
    • 1
  • Andrew Gleeson
    • 1
  • Nicholas Ho
    • 2
  • Mao Lin Huang
    • 3
  • Simeon Simoff
    • 1
  • Daniel Catchpoole
    • 2
  1. 1.School of Computing and MathematicsUniversity of Western SydneyAustralia
  2. 2.The Kids Research InstituteChildren’s Hospital at WestmeadAustralia
  3. 3.Faculty of Engineering & ITUniversity of TechnologySydneyAustralia

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