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
Ochs, M.F., Godwin, A.K.: Microarrays in Cancer: Research and Applications. BioTechniques 34, s4–s15 (2003)
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)
Golub, T.: Genome-Wide Views of Cancer. The New England Journal of Medicine 344, 601–602 (2001)
Jurisica, I., Glasgow, J.: Applications of case-based reasoning in molecular biology. Artificial Intelligence Magazine, Special issue on Bioinformatics 25(1), 5–95 (2004)
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)
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)
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)
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)
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)
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)
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)
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)
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Glez-Peña, D., Glez-Bedia, M., Díaz, F., Fdez-Riverola, F. (2009). Multiple-Microarray Analysis and Internet Gathering Information with Application for Aiding Medical Diagnosis in Cancer Research. In: Corchado, J.M., De Paz, J.F., Rocha, M.P., Fernández Riverola, F. (eds) 2nd International Workshop on Practical Applications of Computational Biology and Bioinformatics (IWPACBB 2008). Advances in Soft Computing, vol 49. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85861-4_14
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DOI: https://doi.org/10.1007/978-3-540-85861-4_14
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