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Illuminating protein space with a programmable generative model

Evolution has produced a range of diverse proteins, and now a generative model called Chroma can expand that set by allowing the user to design new proteins and protein complexes with desired properties and functions.

John B. Ingraham
Max Baranov
Gevorg Grigoryan
ResearchOpen Access15 Nov 2023
Nature

Volume: 623, P: 1070-1078
Combining mechanistic and machine learning models for predictive engineering and optimization of tryptophan metabolism

In metabolic engineering, mechanistic models require prior metabolism knowledge of the chassis strain, whereas machine learning models need ample training data. Here, the authors combine the mechanistic and machine learning models to improve prediction performance of tryptophan metabolism in baker’s yeast.

Jie Zhang
Søren D. Petersen
Michael K. Jensen
ResearchOpen Access25 Sept 2020
Nature Communications

Volume: 11, P: 1-13
A machine learning Automated Recommendation Tool for synthetic biology

Synthetic Biology often lacks the predictive power needed for efficient bioengineering. Here the authors present ART, a machine learning and probabilistic predictive tool to guide synthetic biology design in a systematic fashion.

Tijana Radivojević
Zak Costello
Hector Garcia Martin
ResearchOpen Access25 Sept 2020
Nature Communications

Volume: 11, P: 1-14
Industrial brewing yeast engineered for the production of primary flavor determinants in hopped beer

Production of aromatic monoterpene molecules in hop flowers is affected by genetic, environmental, and processing factors. Here, the authors engineer brewer’s yeast for the production of linalool and geraniol, and show pilot-scale beer produced by engineered strains reconstitutes some qualities of hop flavor.

Charles M. Denby
Rachel A. Li
Jay D. Keasling
ResearchOpen Access20 Mar 2018
Nature Communications

Volume: 9, P: 1-10
Author Correction: Machine learning-led semi-automated medium optimization reveals salt as key for flaviolin production in Pseudomonas putida

Apostolos Zournas
Matthew R. Incha
Hector Garcia Martin
Amendments and CorrectionsOpen Access13 May 2025
Communications Biology

Volume: 8, P: 1
Machine learning-led semi-automated medium optimization reveals salt as key for flaviolin production in Pseudomonas putida

Media optimization using machine learning increased flaviolin production in Pseudomonas putida, generating counter-intuitive media recipes.

Apostolos Zournas
Matthew R. Incha
Hector Garcia Martin
ResearchOpen Access18 Apr 2025
Communications Biology

Volume: 8, P: 1-14
A machine learning approach to predict metabolic pathway dynamics from time-series multiomics data

Zak Costello
Hector Garcia Martin
ResearchOpen Access29 May 2018
npj Systems Biology and Applications

Volume: 4, P: 1-14

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Illuminating protein space with a programmable generative model

Combining mechanistic and machine learning models for predictive engineering and optimization of tryptophan metabolism

A machine learning Automated Recommendation Tool for synthetic biology

Industrial brewing yeast engineered for the production of primary flavor determinants in hopped beer

Author Correction: Machine learning-led semi-automated medium optimization reveals salt as key for flaviolin production in Pseudomonas putida

Machine learning-led semi-automated medium optimization reveals salt as key for flaviolin production in Pseudomonas putida

A machine learning approach to predict metabolic pathway dynamics from time-series multiomics data

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Illuminating protein space with a programmable generative model

Combining mechanistic and machine learning models for predictive engineering and optimization of tryptophan metabolism

A machine learning Automated Recommendation Tool for synthetic biology

Industrial brewing yeast engineered for the production of primary flavor determinants in hopped beer

Author Correction: Machine learning-led semi-automated medium optimization reveals salt as key for flaviolin production in Pseudomonas putida

Machine learning-led semi-automated medium optimization reveals salt as key for flaviolin production in Pseudomonas putida

A machine learning approach to predict metabolic pathway dynamics from time-series multiomics data

Search

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