The systems biology of cellular decision-making

Cells must make decisions in stochastic environments using stochastic biochemistry. The aim of our research is to uncover the information-processing strategies that allow cells to decide reliably.

Cells infer the current and potentially future state of the extracellular environment from local signals: those sensed at the cell membrane and intracellularly. Based on this inference, on the expected costs and benefits of each potential response, and on the possible presence of other organisms, be they either competitors or cooperators, a decision is made.

Our focus is nutrient-sensing by budding yeast. Extracellular nutrients in yeast can act analogously to hormones in mammalian cells, and we are interested in how cells determine how fast they should grow.

We use a combination of both experiment and theory: microfluidics to generate dynamically changing environments, fluorescence microscopy and machine learning to quantitatively monitor the responses of individual cells, and techniques from stochastic processes and non-linear dynamics to develop mathematical models of cellular information-processing.

Factors influencing cellular decision-making. A cell senses signals generated by a change in the environment and must decide an appropriate response (Perkins & Swain (2009)).



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