2nd International Conference on Metabolomics, Genomics and Proteomics
University of British Columbia & PROOF Centre of Excellence, Canada
Title: Integration of metabolomic and other OMIC datasets to gain insights in human health and disease
Biography: Scott J. Tebbutt
Systems biology combines information from different molecular layers to provide a holistic view of a biological system and unravel its complexities. Integration of data across these layers requires methods that include multivariate approaches, Bayesian methods and network analyses. Although metabolomic analysis can provide a valuable ‘snapshot’ of biochemical processes at a high level, it is the functional relationships among various additional elements including genes, proteins and cells that will provide a deeper understanding of the biology. Indeed, any single OMICs approach is unlikely to suffice to characterize the complexity of biological processes in health and disease. We are developing innovative OMIC integration via functional bioinformatics and data-driven statistical approaches and computational modeling to identify signals in complex OMICs datasets regarding mechanisms that drive biological processes in a variety of human health and disease conditions.