Abstract
In recent years, the interest in extracting useful knowledge from gene expression data has experimented an enormous increase with the development of microarray technique. Biclustering is a recent technique that aims at extracting a subset of genes that show a similar behaviour for a subset conditions. It is important, therefore, to measure the quality of a bicluster, and a way to do that would be checking if each data submatrix follows a specific trend, represented by a pattern. In this work, we present an evolutionary algorithm for finding significant shifting patterns which depict the general behaviour within each bicluster. The empirical results we have obtained confirm the quality of our proposal, obtaining very accurate solutions for the biclusters used.
This research was supported by the Spanish Research Agency CICYT under grants TIN2004–00159 and TIN2004-06689C0303.
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Pontes, B., Giráldez, R., Aguilar–Ruiz, J.S. (2006). Shifting Patterns Discovery in Microarrays with Evolutionary Algorithms. In: Gabrys, B., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2006. Lecture Notes in Computer Science(), vol 4252. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11893004_160
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DOI: https://doi.org/10.1007/11893004_160
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