Machine learning for metabolic engineering: A review
Abstract Machine learning provides researchers a unique opportunity to make metabolic
engineering more predictable. In this review, we offer an introduction to this discipline in …
engineering more predictable. In this review, we offer an introduction to this discipline in …
Mass spectrometry‐based high‐throughput proteomics and its role in biomedical studies and systems biology
There are multiple reasons why the next generation of biological and medical studies
require increasing numbers of samples. Biological systems are dynamic, and the effect of a …
require increasing numbers of samples. Biological systems are dynamic, and the effect of a …
A machine learning Automated Recommendation Tool for synthetic biology
T Radivojević, Z Costello, K Workman… - Nature …, 2020 - nature.com
Synthetic biology allows us to bioengineer cells to synthesize novel valuable molecules
such as renewable biofuels or anticancer drugs. However, traditional synthetic biology …
such as renewable biofuels or anticancer drugs. However, traditional synthetic biology …
Functional genetics of human gut commensal Bacteroides thetaiotaomicron reveals metabolic requirements for growth across environments
Harnessing the microbiota for beneficial outcomes is limited by our poor understanding of
the constituent bacteria, as the functions of most of their genes are unknown. Here, we …
the constituent bacteria, as the functions of most of their genes are unknown. Here, we …
Biological research and self-driving labs in deep space supported by artificial intelligence
Abstract Space biology research aims to understand fundamental spaceflight effects on
organisms, develop foundational knowledge to support deep space exploration and …
organisms, develop foundational knowledge to support deep space exploration and …
Growth-coupled selection of synthetic modules to accelerate cell factory development
Synthetic biology has brought about a conceptual shift in our ability to redesign microbial
metabolic networks. Combining metabolic pathway-modularization with growth-coupled …
metabolic networks. Combining metabolic pathway-modularization with growth-coupled …
In vitro continuous protein evolution empowered by machine learning and automation
Directed evolution has become one of the most successful and powerful tools for protein
engineering. However, the efforts required for designing, constructing, and screening a large …
engineering. However, the efforts required for designing, constructing, and screening a large …
Omics-driven biotechnology for industrial applications
B Amer, EEK Baidoo - Frontiers in Bioengineering and Biotechnology, 2021 - frontiersin.org
Biomanufacturing is a key component of biotechnology that uses biological systems to
produce bioproducts of commercial relevance, which are of great interest to the energy …
produce bioproducts of commercial relevance, which are of great interest to the energy …
Machine learning and deep learning in synthetic biology: Key architectures, applications, and challenges
MK Goshisht - ACS omega, 2024 - ACS Publications
Machine learning (ML), particularly deep learning (DL), has made rapid and substantial
progress in synthetic biology in recent years. Biotechnological applications of biosystems …
progress in synthetic biology in recent years. Biotechnological applications of biosystems …
Artificial intelligence for synthetic biology
Artificial intelligence for synthetic biology Page 1 88 COMMUNICATIONS OF THE ACM | MAY
2022 | VOL. 65 | NO. 5 review articles IMA GE B YW A COMKA BIOLOGY HAS DRAMATICALLY …
2022 | VOL. 65 | NO. 5 review articles IMA GE B YW A COMKA BIOLOGY HAS DRAMATICALLY …