Genome-scale modeling of cancer metabolism: from in-silico simulations to in-vivo experiments and back
Metabolic reprogramming is one of the earliest described hallmarks of cancer cells transformation. For this reason the study of cancer metabolism is key to discover cancer specific metabolic vulnerabilities that could be therapeutically exploited. With the increasing availability of large collections of omic data, such as the Cancer Cell Line Encyclopaedia or the Cancer Genome Atlas, genome-scale models have become a powerful tool to integrate heterogeneous source of data, as well as to run computer simulations used to generate experimentally testable hypotheses. In this seminar I will introduce the constraint-based modeling framework and its application to the study of cancer. Finally, I will show how wrong predictions can be exploited to refine our current model of cell metabolism.
Researcher - Computational Biology Life Science Group
BSC Barcelona Supercomputing Center
Domain 3 - U900 - CBIO - Bioinformatics, Biostatistics Epidemiology and Computational Systems
Researcher SysBio group - E. Barillot