24 Bioinformatic Prediction of Yeast Gene Function

Publisher Summary A wide variety of approaches have been developed to predict gene function, ranging from sequence analyses for assigning genes into functional families to structural analyses for assigning protein folds and active sites and to phylogenetic analyses for subdividing gene families into functional subgroups or predicting interacting partners. Because gene function takes such a wide variety of forms, from the corresponding protein's biochemical activity to its physical interaction partners to membership in a given pathway, the chapter only discusses the latter network aspects of gene function: a protein's interaction and pathway partners and the inferences of the function that derive from these. One of the most effective strategies for inferring pathway-type functional information has turned out to be the general strategy of guilt by association. The chapter discusses the inference of yeast gene function via guilt-by-association approaches, along with illustrating a variety of relevant functional and comparative genomics approaches and their integration to predict gene function more accurately. It describes the way these approaches can be made quantitative by estimating the error rates in data and in the predicted gene functions.