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Pleiotropy, the ability of a single mutant gene to cause multiple mutant phenotypes, is a relatively common but poorly understood phenomenon in biology. Perhaps the greatest challenge in the analysis of pleiotropic genes is determining whether phenotypes associated with a mutation result from the loss of a single function or of multiple functions encoded by(More)
Genome-wide RNA expression data provide a detailed view of an organism's biological state; hence, a dataset measuring expression variation between genetically diverse individuals (eQTL data) may provide important insights into the genetics of complex traits. However, with data from a relatively small number of individuals, it is difficult to distinguish(More)
Sequence polymorphisms affect gene expression by perturbing the complex network of regulatory interactions. We propose a probabilistic method, called Geronemo, which directly aims to identify the mechanism by which genetic changes perturb the regulatory network. Geronemo automatically constructs a set of coregulated genes (modules), whose regulation can(More)
Gene expression ratios derived from spotted-glass microarray experiments have become invaluable to researchers by providing sensitive and comprehensive indicators of the molecular underpinnings of cell behaviors and states. However, several drawbacks to this form of data have been noted, including the inability to relate ratios to absolute expression levels(More)
Modern transportation networks have facilitated the migration and mingling of previously isolated populations of plants, animals, and insects. Human activities can also influence the global distribution of microorganisms. The best-understood example is yeasts associated with winemaking. Humans began making wine in the Middle East over 9,000 years ago [1,(More)
BACKGROUND Understanding the response of complex biochemical networks to genetic perturbations and environmental variability is a fundamental challenge in biology. Integration of high-throughput experimental assays and genome-scale computational methods is likely to produce insight otherwise unreachable, but specific examples of such integration have only(More)
MOTIVATION Predicting the outcome of specific experiments (such as the growth of a particular mutant strain in a particular medium) has the potential to allow researchers to devote resources to experiments with higher expected numbers of 'hits'. RESULTS We use decision trees to predict phenotypes associated with Saccharomyces cerevisiae genes on the basis(More)
BACKGROUND Several algorithms have been proposed for detecting fluorescently labeled subcellular objects in microscope images. Many of these algorithms have been designed for specific tasks and validated with limited image data. But despite the potential of using extensive comparisons between algorithms to provide useful information to guide method(More)
The budding yeast Saccharomyces cerevisiae is important for human food production and as a model organism for biological research. The genetic diversity contained in the global population of yeast strains represents a valuable resource for a number of fields, including genetics, bioengineering, and studies of evolution and population structure. Here, we(More)