We will use systems biology approaches to model RNA metabolism in yeast to aid understanding of these complex cellular pathways. In order to develop kinetic models, we propose to quantify RNA precursors and directly determine their rates of production as w ell as their processing and degradation through the various post-transcriptional pathways. Starting with ab-initio models describing the processing and degradation of yeast pre-messenger RNAs and pre-ribosomal RNAs, we will produce two comparable mathemati cal representations and populate the parameters using quantitative experimental data. Manipulation of the parameters will permit predictions to be made about the behaviour of the systems. These will be tested experimentally, using yeast mutants that block specific steps, or chemical inhibitors identified in high-throughput screens. Imaging techniques will be refined to visualise individual transcripts to determine whether the population data reflect the situation in individual cells. Comparison of the perfo rmance of the two models should provide further insights and enrich our understanding of both pathways. In addition, modelling precursor RNA processing in yeast will be of great benefit for understanding of these pathways in human cells, which are less ame nable to direct experimentation, and their significance for human genetic disorders.