AIMC Topic: Metabolic Engineering

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Machine learning framework for assessment of microbial factory performance.

PloS one Jan 15, 2019
Metabolic models can estimate intrinsic product yields for microbial factories, but such frameworks struggle to predict cell performance (including product titer or rate) under suboptimal metabolism and complex bioprocess conditions. On the other han...
Metabolic Engineering Reproducibility of Results Computer Simulation Escherichia coli Databases, Factual Algorithms Models, Biological Machine Learning
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Leveraging knowledge engineering and machine learning for microbial bio-manufacturing.

Biotechnology advances May 3, 2018
Genome scale modeling (GSM) predicts the performance of microbial workhorses and helps identify beneficial gene targets. GSM integrated with intracellular flux dynamics, omics, and thermodynamics have shown remarkable progress in both elucidating com...
Models, Biological Metabolic Engineering Machine Learning Synthetic Biology Bioreactors
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MiYA, an efficient machine-learning workflow in conjunction with the YeastFab assembly strategy for combinatorial optimization of heterologous metabolic pathways in Saccharomyces cerevisiae.

Metabolic engineering Apr 5, 2018
Facing boosting ability to construct combinatorial metabolic pathways, how to search the metabolic sweet spot has become the rate-limiting step. We here reported an efficient Machine-learning workflow in conjunction with YeastFab Assembly strategy (M...
Metabolic Engineering Neural Networks, Computer Machine Learning Indoles Models, Biological Saccharomyces cerevisiae
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Machine learning reveals novel compound for the improved production of chitooligosaccharides in Escherichia coli.

New biotechnology May 25, 2025
In order to improve predictability of outcome and reduce costly rounds of trial-and-error, machine learning models have been of increasing importance in the field of synthetic biology. Besides applications in predicting genome annotation, process par...
Machine Learning Escherichia coli Metabolic Engineering Chitin Oligosaccharides Chitosan
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Applications of artificial intelligence and machine learning in dynamic pathway engineering.

Biochemical Society transactions Oct 31, 2023
Dynamic pathway engineering aims to build metabolic production systems embedded with intracellular control mechanisms for improved performance. These control systems enable host cells to self-regulate the temporal activity of a production pathway in ...
Artificial Intelligence Metabolic Engineering Biosensing Techniques Machine Learning
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[Construction of Escherichia coli cell factories].

Sheng wu gong cheng xue bao = Chinese journal of biotechnology May 25, 2021
As an important model industrial microorganism, Escherichia coli has been widely used in pharmaceutical, chemical industry and agriculture. In the past 30 years, a variety of new strategies and techniques, including artificial intelligence, gene edit...
Artificial Intelligence Escherichia coli Gene Editing Metabolic Engineering Metabolic Networks and Pathways
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[Preface for special issue on industrial microorganisms: innovation and breakthrough (2021)].

Sheng wu gong cheng xue bao = Chinese journal of biotechnology Mar 25, 2021
Industrial microorganisms and their products are widely used in various fields such as industry, agriculture, and medicine, which play a pivotal role in economy. Efficient industrial strains are the key to improve production efficiency, and advanced ...
Synthetic Biology Industrial Microbiology Fermentation Metabolic Engineering Industry Artificial Intelligence
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Digitalization and Bioprocessing: Promises and Challenges.

Advances in biochemical engineering/biotechnology Jan 1, 2021
The production of pharmaceuticals, industrial chemicals, and food ingredients from biotechnological processes is a vast and rapidly growing industry. While advances in synthetic biology and metabolic engineering have made it possible to produce thous...
Biotechnology Metabolic Engineering Artificial Intelligence Machine Learning
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Meeting Report for Synthetic Biology for Natural Products 2017: The Interface of (Meta)Genomics, Machine Learning, and Natural Product Discovery.

ACS synthetic biology May 19, 2017
Genomics Drug Discovery Synthetic Biology Biological Products Metabolic Engineering Machine Learning Protein Interaction Maps
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