Samuel Kaski, Janne Nikkilä, Eerika Savia, and Christophe Roos. Discriminative clustering of yeast stress response. In Udo Seiffert, Lakhmi Jain, and Patric Schweizer, editors, Bioinformatics using Computational Intelligence Paradigms, pages 75-92. Springer, Berlin, 2005. (preprint pdf)

When a yeast cell is challenged by a rapid change in the conditions, be it temperature, osmolarity, pH, nutrient or other, it starts a genome stress response program. Survival of especially single-cell organisms depends on their ability to adapt to the environmental changes and therefore stress response has received much attention. In the budding yeast Saccharomyces cerevisiae several hundred genes out of about 6500 present in the genome have previously been found involved in a stereotyped stress response pattern. Hierarchical clustering techniques applied to gene expression measurements have also previously identified a subset of genes termed common environmental stress response (CESR) or common environmental response (CER) genes, that respond in the same way in a variety of environmental conditions. There is evidence from two different sets of experiments that many of these genes are regulated by the same Msn2p and Msn4p transcription factor pair. We have extended the study by in silico data mining using a new supervised discriminative clustering (DC) technique, which directly searches for responses potentially regulated by the Msn2/4p factors. We observed a cluster of CESR/CER genes, comparable to those previously found and potentially regulated by Msn2/4p. The results of discriminative clustering both support the viability of the technique in supervised gene expression clustering and yield new insights into genomic stress response.

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Sami Kaski

Last modified: Wed Mar 9 08:15:00 EET 2005