Abstract
We propose an approach to clustering and visualization of the DNA microarray-based gene expression data. We implement the self-organizing map (SOM) handling similarities between genes in terms of their expression characteristics. The resulting algorithmic toolkit is enriched with graphical interface enabling the user to interactively support the entire learning process.Preliminary calculations and consultations with biomedical experts positively verify applicability of our method.
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Grużdź, A., Ihnatowicz, A., Ślezak, D. (2005). Interactive SOM-Based Gene Grouping: An Approach to Gene Expression Data Analysis. In: Hacid, MS., Murray, N.V., Raś, Z.W., Tsumoto, S. (eds) Foundations of Intelligent Systems. ISMIS 2005. Lecture Notes in Computer Science(), vol 3488. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11425274_53
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DOI: https://doi.org/10.1007/11425274_53
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-25878-0
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