title: The Saccharomyces Genome Database: Exploring Biochemical Pathways and Mutant Phenotypes.
abstract: Many biochemical processes, and the proteins and cofactors involved, have been defined for the eukaryote Saccharomyces cerevisiae. This understanding has been largely derived through the awesome power of yeast genetics. The proteins responsible for the reactions that build complex molecules and generate energy for the cell have been integrated into web-based tools that provide classical views of pathways. The Yeast Pathways in the Saccharomyces Genome Database (SGD) is, however, the only database created from manually curated literature annotations. In this protocol, gene function is explored using phenotype annotations to enable hypotheses to be formulated about a gene's action. A common use of the SGD is to understand more about a gene that was identified via a phenotypic screen or found to interact with a gene/protein of interest. There are still many genes that do not yet have an experimentally defined function and so the information currently available can be used to speculate about their potential function. Typically, computational annotations based on sequence similarity are used to predict gene function. In addition, annotations are sometimes available for phenotypes of mutations in the gene of interest. Integrated results for a few example genes will be explored in this protocol. This will be instructive for the exploration of details that aid the analysis of experimental results and the establishment of connections within the yeast literature.
authors.affiliation: Department of Genetics, Stanford University School of Medicine, Stanford, California 94305-5120.
authors.forename: J Michael
authors.initials: JM
authors.lastname: Cherry
mesh_terms: D022126:Access to Information; D057225:Data Mining; D030541:Databases, Genetic; D016681:Genome, Fungal; D020407:Internet; D053858:Metabolic Networks and Pathways / Q000235:genetics*; D009154:Mutation; D010641:Phenotype; D012441:Saccharomyces cerevisiae / Q000235:genetics*