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EXPLORATORY MODELING OF YEAST STRESS RESPONSE AND ITS REGULATION WITH gCCA AND ASSOCIATIVE CLUSTERING

JANNE NIKKILÄ

Laboratory of Computer and Information Science, Helsinki University of Technology, P.O. Box 5400, FI-02015 HUT, Finland

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CHRISTOPHE ROOS

Medicel Oy, Huopalahdentie 24, FI-00350 Helsinki, Finland

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EERIKA SAVIA

Laboratory of Computer and Information Science, Helsinki University of Technology, P.O. Box 5400, FI-02015 HUT, Finland

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, and

SAMUEL KASKI

Department of Computer Science, University of Helsinki, P.O. Box 68, FI-00014 University of Helsinki, Finland

Laboratory of Computer and Information Science, Helsinki University of Technology, P.O. Box 5400, FI-02015 HUT, Finland

Corresponding author.

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https://doi.org/10.1142/S0129065705000220Cited by:5 (Source: Crossref)

Abstract

We model dependencies between m multivariate continuous-valued information sources by a combination of (i) a generalized canonical correlations analysis (gCCA) to reduce dimensionality while preserving dependencies in m - 1 of them, and (ii) summarizing dependencies with the remaining one by associative clustering. This new combination of methods avoids multiway associative clustering which would require a multiway contingency table and hence suffer from curse of dimensionality of the table. The method is applied to summarizing properties of yeast stress by searching for dependencies (commonalities) between expression of genes of baker's yeast Saccharomyces cerevisiae in various stressful treatments, and summarizing stress regulation by finally adding data about transcription factor binding sites.

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