Grant: Canada Research Chairs

Signatures are a modern type of biomarker arising from systems biology where high-throughput technologies provide genome-wide measurements of samples. They have many advantages over single biomarker approaches, and have already found utility in clinical and research contexts. This computational biology proposal will improve methodology related to signatures. Our approach uses probabilistic graphical models to build ¿transcriptional signature networks¿ that capture the fact that molecular processes are tightly inter-connected and dependent on many cellular signals. Using our high-throughput robotics facility, we will build a network for C albicans, an organism that can be commensal or pathogenic for humans.