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Metabolic Engineering

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Metabolic perceptrons for neural computing in biological systems.

Nature communications
Synthetic biological circuits are promising tools for developing sophisticated systems for medical, industrial, and environmental applications. So far, circuit implementations commonly rely on gene expression regulation for information processing usi...

Reinforcement Learning for Bioretrosynthesis.

ACS synthetic biology
Metabolic engineering aims to produce chemicals of interest from living organisms, to advance toward greener chemistry. Despite efforts, the research and development process is still long and costly, and efficient computational design tools are requi...

Biosystems Design by Machine Learning.

ACS synthetic biology
Biosystems such as enzymes, pathways, and whole cells have been increasingly explored for biotechnological applications. However, the intricate connectivity and resulting complexity of biosystems poses a major hurdle in designing biosystems with desi...

A machine learning Automated Recommendation Tool for synthetic biology.

Nature communications
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...

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

Nature communications
Through advanced mechanistic modeling and the generation of large high-quality datasets, machine learning is becoming an integral part of understanding and engineering living systems. Here we show that mechanistic and machine learning models can be c...

Machine learning for metabolic engineering: A review.

Metabolic engineering
Machine learning provides researchers a unique opportunity to make metabolic engineering more predictable. In this review, we offer an introduction to this discipline in terms that are relatable to metabolic engineers, as well as providing in-depth i...

A deep learning approach to evaluate the feasibility of enzymatic reactions generated by retrobiosynthesis.

Biotechnology journal
Retrobiosynthesis allows the designing of novel biosynthetic pathways for the production of chemicals and materials through metabolic engineering, but generates a large number of reactions beyond the experimental feasibility. Thus, an effective metho...

Digitalization and Bioprocessing: Promises and Challenges.

Advances in biochemical engineering/biotechnology
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...

[Preface for special issue on industrial microorganisms: innovation and breakthrough (2021)].

Sheng wu gong cheng xue bao = Chinese journal of biotechnology
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 ...

[Construction of Escherichia coli cell factories].

Sheng wu gong cheng xue bao = Chinese journal of biotechnology
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...