A wide variety of genome-scale tools, such as global transcriptional analysis, systematic genetic screens, genetic interaction studies, and mass spectrometry based determination of global protein levels and modifications, have provided a comprehensive itemization of the components and interactions within signaling networks, particularly in the yeast Saccharomyces.Moreover, new computational tools have allowed us to integrate these genome-wide observations and organize them in an accessible and intuitive manner. Additional computational approaches are beginning to provide the means of developing predictive,in silico models of biological processes. Here, we describe the recent results from these genome-wide approaches as applied to the TOR signaling network in yeast. Furthermore, we attempt to integrate and reconcile genome-wide studies from multiple groups. As evident from our discussion, investigators have made substantial strides in applying these genomic tools as a means of developing a comprehensive description of the organization of the rapamycin-sensitive signaling network in yeast. However, we are clearly just on the forefront of developing predictive models of the network. Finally, we discuss future outlooks for TOR with an emphasis on the application of systems-level understanding to personalized treatment in cancer.
All Science Journal Classification (ASJC) codes
- Molecular Biology