We summarized literature knowledge in order to determine the insertion location that would provide the greatest readthrough efficiency. This was then used to inform the design of our construct.

We modelled the accumulation of amyloids and the curing of the [PSI+] state as a result of Hsp104 overexpression and knockdown.

We modelled the loss rates of yeast plasmids, in order to determine whether we should use a high copy or low copy number plasmid in the lab.

We modelled the effectiveness of applying CRISPR-dCas9 to cause knockdown of Hsp104 expression.

We analysed data from 2015 about collaborations between iGEM teams in order to find patterns. We tried to identify whether there were correlations between variables like team size, success, location, and collaboration in order to make recommendations to future teams.


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