Background: Rubisco is an enzyme that converts CO2 to O2 in the process of photosynthesis in nature. Red Algae specifically have high levels of Rubisco. Synthetic biology experiments in the near future can exploit this concentration of Rubisco in red Algae to produce a more efficient variant of red algae for converting CO2 to O2. Our project is a predictive algorithm which lays down basic predictions of the level of Rubisco in a red algae cell, given variables of time and the daylight driven fluctuations of the reagents needed to produce Rubisco. Our team is composed of students both in highshcool and from U of Toronto with interest in software engineering and bioengineering.

Resources: The resources that we used include using different tools and programs such as Jupyter Notebook and Anaconda in order to create interactive plots/graphs that we used to show the concentrations of Rubisco and its necessary reagents as a function of time in days.

Challenges Faced: The development time and the lack of information regarding the biological aspects of Rubisco. Furthermore, we had challenges finding the two genes of the red algae cbbX.