The modeling of cellular metabolism has always been a popular topic among researchers. The existing examples are usually confined to a particular pathway or cellular process. However, the massive research efforts in genetic annotation of the last decade have expanded the field to incorporate genome scale models (GSMs), which include the entire cellular metabolism.

Due to the lack of metabolic kinetic information, GSMs were largely implemented with the flux balance analysis (FBA) strategy, a steady-state based methodology absent of kinetic parameters. Although instrumental in predicting a number of experimental observations, FBA models have severe limitations.

In my work, I sought to develop the necessary tools and methodologies to construct full kinetic GSMs. I have demonstrated that the metabolic modeling field has progressed in a way that a kinetic GSM can finally be developed. A number of experimental observations in both mammalian and algae cell lines have been correctly predicted by this methodology and kinetic-based GSMs can further expand the metabolic modeling field.