Discovery of causal relationships in a gene-regulation pathway from a mixture of experimental and observational DNA microarray data.
This paper reports the methods and results of a computer-based search for causal relationships in the gene-regulation pathway of galactose metabolism in the yeast Saccharomyces cerevisiae. The search uses recently published data from cDNA microarray experiments. A Bayesian method was applied to learn causal networks from a mixture of observational and experimental gene-expression data. The observational data were gene-expression levels obtained from unmanipulated "wild-type" cells. The experimental data were produced by deleting ("knocking out") genes and observing the expression levels of other genes. Causal relations predicted from the analysis on 36 galactose gene pairs are reported and compared with the known galactose pathway. Additional exploratory analyses are also reported.
Yoo
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Center for Biomedical Informatics, University of Pittsburgh, 8084 Forbes Tower, 200 Lothrop St., Pittsburgh, PA 15213, USA.
Thorsson
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Cooper
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D000818:Animals; D001499:Bayes Theorem; D005690:Galactose / Q000235:genetics* / Q000378:metabolism; D017353:Gene Deletion; D015966:Gene Expression Regulation, Fungal; D016681:Genome, Fungal; D008957:Models, Genetic; D020411:Oligonucleotide Array Sequence Analysis; D012441:Saccharomyces cerevisiae / Q000201:enzymology / Q000235:genetics*
D005690:Galactose