Multiple-Microarray Analysis and Internet Gathering Information with Application for Aiding Medical Diagnosis in Cancer Research

  • Daniel Glez-Peña
  • Manuel Glez-Bedia
  • Fernando Díaz
  • Florentino Fdez-Riverola
Part of the Advances in Soft Computing book series (AINSC, volume 49)

Abstract

In light of the fast growth in DNA technology there is a compelling demand for tools able to perform efficient, exhaustive and integrative analyses of multiple microarray datasets. Specifically, what is particularly evident is the need to link the results obtained from these new tools with the wealth of clinical information. The final goal is to bridge the gap existing between biomedical researchers and pathologists or oncologists providing them with a common framework of interaction. To overcome such difficulty we have developed geneCBR, a freely available software tool that allows the use of combined techniques that can be applied to gene selection, clustering, knowledge extraction and prediction. In diagnostic mode, geneCBR employs a case-based reasoning model that incorporates a set of fuzzy prototypes for the retrieval of relevant genes, a growing cell structure network for the clustering of similar patients and a proportional weighted voting algorithm to provide an accurate diagnosis.

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References

  1. 1.
    Ochs, M.F., Godwin, A.K.: Microarrays in Cancer: Research and Applications. BioTechniques 34, s4–s15 (2003)Google Scholar
  2. 2.
    Xiang, Z.Y., Yang, Y., Ma, X., Ding, W.: Microarray expression profiling: Analysis and applications. Current Opinion in Drug Discovery & Development 6(3), 384–395 (2003)Google Scholar
  3. 3.
    Golub, T.: Genome-Wide Views of Cancer. The New England Journal of Medicine 344, 601–602 (2001)CrossRefGoogle Scholar
  4. 4.
    Jurisica, I., Glasgow, J.: Applications of case-based reasoning in molecular biology. Artificial Intelligence Magazine, Special issue on Bioinformatics 25(1), 5–95 (2004)Google Scholar
  5. 5.
    Aaronson, J.S., Juergen, H., Overton, G.C.: Knowledge Discovery in GENBANK. In: Proc. of the First International Conference on Intelligent Systems for Molecular Biology, pp. 3–11 (1993)Google Scholar
  6. 6.
    Arshadi, N., Jurisica, I.: Data Mining for Case-Based Reasoning in High-Dimensional Biological Domains. IEEE Transactions on Knowledge and Data Engineering 17(8), 1127–1137 (2005)CrossRefGoogle Scholar
  7. 7.
    Costello, E., Wilson, D.C.: A Case-Based Approach to Gene Finding. In: Proc. of the Fifth International Conference on Case-Based Reasoning Workshop on CBR in the Health Sciences, pp. 19–28 (2003)Google Scholar
  8. 8.
    Shavlik, J.: Finding Genes by Case-Based Reasoning in the Presence of Noisy Case Boundaries. In: Proc. of the DARPA Workshop on Case-Based Reasoning, pp. 327–338 (1991)Google Scholar
  9. 9.
    Lieber, J., Bresson, B.: Case-Based Reasoning for Breast Cancer Treatment Decision Helping. In: Proc. of the 5th European Workshop on Case-Based Reasoning, pp. 173–185 (2000)Google Scholar
  10. 10.
    Fdez-Riverola, F., Díaz, F., Borrajo, M.L., Yáñez, J.C., Corchado, J.M.: Improving Gene Selection in Microarray Data Analysis using fuzzy Patterns inside a CBR System. In: Proc. of the 6th International Conference on Case-Based Reasoning, pp. 191–205 (2005)Google Scholar
  11. 11.
    Díaz, F., Fdez-Riverola, F., Glez-Peña, D., Corchado, J.M.: Using Fuzzy Patterns for Gene Selection and Data Reduction on Microarray Data. In: Proc. of the 7th International Conference on Intelligent Data Engineering and Automated Learning, pp. 1087–1094 (2006)Google Scholar
  12. 12.
    Díaz, F., Fdez-Riverola, F., Glez-Peña, D., Corchado, J.M., Applying, G.C.S.: Networks to Fuzzy Discretized Microarray Data for Tumour Diagnosis. In: Proc. of the 7th International Conference on Intelligent Data Engineering and Automated Learning, pp. 1095–1102 (2006)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Daniel Glez-Peña
    • 1
  • Manuel Glez-Bedia
    • 2
  • Fernando Díaz
    • 3
  • Florentino Fdez-Riverola
    • 1
  1. 1.Dept. InformáticaUniversity of Vigo, Escuela Superior de Ingeniería Informática, Edificio PolitécnicoOurenseSpain
  2. 2.Dept. de Informática e Ingeniería de SistemasUniversity of Zaragoza, Edificio Ada ByronZaragozaSpain
  3. 3.Dept. InformáticaUniversity of Valladolid, Escuela Universitaria de InformáticaSegoviaSpain

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