Mining Discriminant Sequential Patterns for Aging Brain

Authors:
Paola Salle;Sandra Bringay;Maguelonne Teisseire
Affiliations:
LIRMM, Montpellier 2 University, CNRS, Montpellier, France 34392;LIRMM, Montpellier 2 University, CNRS, Montpellier, France 34392 and MIAP Dpt., Montpellier 3 University, Montpellier, France 34199;Cemagref, UMR TETIS, Montpellier, France F-34093
Venue:
AIME '09 Proceedings of the 12th Conference on Artificial Intelligence in Medicine: Artificial Intelligence in Medicine
Year:
2009

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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.