Which Distance for the Identification and the Differentiation of Cell-Cycle Expressed Genes?

Authors:
Alpha Diallo;Ahlame Douzal-Chouakria;Francoise Giroud
Affiliations:
Laboratory TIMC-IMAG, CNRS UMR 5525, Faculté de Médecine, Université Joseph Fourier Grenoble 1, LA TRONCHE Cedex, France 38706;Laboratory TIMC-IMAG, CNRS UMR 5525, Faculté de Médecine, Université Joseph Fourier Grenoble 1, LA TRONCHE Cedex, France 38706;Laboratory TIMC-IMAG, CNRS UMR 5525, Faculté de Médecine, Université Joseph Fourier Grenoble 1, LA TRONCHE Cedex, France 38706
Venue:
IDA '09 Proceedings of the 8th International Symposium on Intelligent Data Analysis: Advances in Intelligent Data Analysis VIII
Year:
2009

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Abstract

This paper addresses the clustering and classification of active genes during the process of cell division. Cell division ensures the proliferation of cells, but becomes drastically aberrant in cancer cells. The studied genes are described by their expression profiles (i.e. time series) during the cell division cycle. This work focuses on evaluating the efficiency of four major metrics for clustering and classifying gene expression profiles. The study is based on a random-periods model for the expression of cell-cycle genes. The model accounts for the observed attenuation in cycle amplitude or duration, variations in the initial amplitude, and drift in the expression profiles.