AIMC Topic: Dodecanol

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A machine learning Automated Recommendation Tool for synthetic biology.

Nature communications Sep 25, 2020
Synthetic biology allows us to bioengineer cells to synthesize novel valuable molecules such as renewable biofuels or anticancer drugs. However, traditional synthetic biology approaches involve ad-hoc engineering practices, which lead to long develop...
Machine Learning Escherichia coli Bayes Theorem Fatty Acids Synthetic Biology Biofuels Saccharomyces cerevisiae Metabolic Engineering Beer Dodecanol
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Lessons from Two Design-Build-Test-Learn Cycles of Dodecanol Production in Escherichia coli Aided by Machine Learning.

ACS synthetic biology May 24, 2019
The Design-Build-Test-Learn (DBTL) cycle, facilitated by exponentially improving capabilities in synthetic biology, is an increasingly adopted metabolic engineering framework that represents a more systematic and efficient approach to strain developm...
Machine Learning Algorithms Escherichia coli Metabolic Networks and Pathways Synthetic Biology Metabolic Engineering Dodecanol
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