We apply deep learning models to harness the complex sequence to function relation in proteins.
By interfacing our trained models with a genetic algorithm we developed an in silico evolution tool.
To perform self-checks, and prevent misuse of directed evolution techniques, we developed SafetyNet a sensitive tool for the detection of harmful traits in sequences.
Deploying GAIA, we fully in silico evolved a beta lactamase and reprogrammed the E. Coli beta glucuronidase towards beta galactosidase function.
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iGEM-Heidelberg2017@bioquant.uni-heidelberg.de Im Neuenheimer Feld 267 69120 Heidelberg