Identification of regulatory molecules in signaling pathways is critical for understanding cellular behavior. Given the complexity of\r\nthe transcriptional gene network, the relationship between molecular expression and phenotype is difficult to determine using reductionist\r\nexperimental methods. Computational models provide the means to characterize regulatory mechanisms and predict\r\nphenotype in the context of gene networks. Integrating gene expression data with phenotypic data in transcriptional network models\r\nenables systematic identification of critical molecules in a biological network.We developed an approach based on fuzzy logic to\r\nmodel cell budding in Saccharomyces cerevisiae using time series expression microarray data of the cell cycle. Cell budding is a phenotype\r\nof viable cells undergoing division. Predicted interactions between gene expression and phenotype reflected known biological\r\nrelationships. Dynamic simulation analysis reproduced the behavior of the yeast cell cycle and accurately identified genes and\r\ninteractions which are essential for cell viability.
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