Research: Systems biology modeling of the transcriptional and metabolic network in trees
We integrate high-throughput experimental data from transcriptomics, metabolomics and proteomics with sequence information to computationally infer network models that describe interactions between genes, proteins and metabolites, and the underlying regulatory logics hard-wired in tree DNA. Our models based on machine learning techniques reveal general trends in the data, and also act as prediction devices that can propose new hypotheses subject to further experiments. We aim at obtaining synergy between experimental biology and computational biology by iteratively using models to guide experimentalists and new experimental results to improve models.
For more detailed information, Torgeir Hvidsten@UPSCClose