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Guiding synthetic biology via Automated Recommendation Tool (ART)

Authors: 
Radivojevic, T. - Presenter, Joint BioEnergy Institute
One of the most important challenges in bioengineering is effectively using -omics data to guide metabolic engineering towards higher production levels. Here, we present the Automated Recommendation Tool (ART), a tool that leverages machine learning and probabilistic modeling techniques to guide synthetic biology in a systematic fashion, without the need for a full mechanistic understanding of the biological system. ART provides a set of recommendations for the next engineering cycle, alongside probabilistic predictions of their outcomes. It can be used as a python library or through a web-based graphical frontend that does not require coding expertise.