Abstract
Discovering new information about groups of genes implied in a disease is still challenging. Microarrays are a powerful tool to analyse gene expression. In this paper, we propose a new approach outlining relationships between genes based on their ordered expressions. Our contribution is twofold. First, we propose to use a new material, called sequential patterns, to be investigated by biologists. Secondly, due to the expression matrice density, extracting sequential patterns from microarray datasets is far away from being easy. The aim of our proposal is to provide the biological experts with an efficient approach based on discriminant sequential patterns. Results of various experiments on real biological data highlight the relevance of our proposal.
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Salle, P., Bringay, S., Teisseire, M. (2009). Mining Discriminant Sequential Patterns for Aging Brain. In: Combi, C., Shahar, Y., Abu-Hanna, A. (eds) Artificial Intelligence in Medicine. AIME 2009. Lecture Notes in Computer Science(), vol 5651. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02976-9_50
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DOI: https://doi.org/10.1007/978-3-642-02976-9_50
Publisher Name: Springer, Berlin, Heidelberg
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