Here we provide a tutorial of how to use ART to guide metabolic engineering to increase the production of isoprenol, using synthetic data. This tutorial will show you how to use together ART, the Inventory of Composable Elements (ICE) and the Experiment Data Depot to recommend new designs, predict their production and test these predictions. 

This tutorial is published here. 

ART 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.

You can find all relevant information in the ART site.

This Python Jupyter notebook on Google Colab cleans and formats raw Biolector One and Biolector Pro data for upload into the Experimental Data Depot (EDD).

Please contact stan@lbl.gov for any questions or issues.