Abstract:

Natural systems exhibit tight gene regulation and robust cellular response in spite of inherent stochasticity and delays. However, the inherent variability of nature and our lack of understanding of the evolved regulation mechanisms makes it difficult to elicit predictable and consistent cellular response. In spite of this complexity, new technology combined with machine learning and applied mathematics can give us unprecedented control over nature. For example, synthetic biology, an engineering discipline that uses components of natural systems as building blocks, can be used to design new systems from the ground up. Knowledge of effective feedback control architectures can be used to design these networks. We show how current technology can be enhanced with mathematical methods to drive new applications such as precision medicine in the biomedical field or population control in ecology.

Bio:

Marcella Gomez is an Assistant Professor in Applied Mathematics at UCSC. Dr. Gomez completed a Ph.D in Mechanical Engineering at the California Institute of Technology in 2015. She joined UCSC faculty following a postdoctoral research fellowship at UC Berkeley. Her research focuses on mathematical modeling, analysis, and control of biological systems.