Metabolic engineering: methodologies and applications
Metabolic engineering aims to improve the production of economically valuable molecules
through the genetic manipulation of microbial metabolism. While the discipline is a little over …
through the genetic manipulation of microbial metabolism. While the discipline is a little over …
Microbial production of advanced biofuels
Concerns over climate change have necessitated a rethinking of our transportation
infrastructure. One possible alternative to carbon-polluting fossil fuels is biofuels produced …
infrastructure. One possible alternative to carbon-polluting fossil fuels is biofuels produced …
Integrating machine learning and multiscale modeling—perspectives, challenges, and opportunities in the biological, biomedical, and behavioral sciences
Fueled by breakthrough technology developments, the biological, biomedical, and
behavioral sciences are now collecting more data than ever before. There is a critical need …
behavioral sciences are now collecting more data than ever before. There is a critical need …
Common principles and best practices for engineering microbiomes
Despite broad scientific interest in harnessing the power of Earth's microbiomes, knowledge
gaps hinder their efficient use for addressing urgent societal and environmental challenges …
gaps hinder their efficient use for addressing urgent societal and environmental challenges …
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 …
Design of synthetic human gut microbiome assembly and butyrate production
RL Clark, BM Connors, DM Stevenson… - Nature …, 2021 - nature.com
The capability to design microbiomes with predictable functions would enable new
technologies for applications in health, agriculture, and bioprocessing. Towards this goal …
technologies for applications in health, agriculture, and bioprocessing. Towards this goal …
Machine learning meets omics: applications and perspectives
The innovation of biotechnologies has allowed the accumulation of omics data at an
alarming rate, thus introducing the era of 'big data'. Extracting inherent valuable knowledge …
alarming rate, thus introducing the era of 'big data'. Extracting inherent valuable knowledge …
Machine learning applications for mass spectrometry-based metabolomics
The metabolome of an organism depends on environmental factors and intracellular
regulation and provides information about the physiological conditions. Metabolomics helps …
regulation and provides information about the physiological conditions. Metabolomics helps …
Multiscale modeling meets machine learning: What can we learn?
Abstract Machine learning is increasingly recognized as a promising technology in the
biological, biomedical, and behavioral sciences. There can be no argument that this …
biological, biomedical, and behavioral sciences. There can be no argument that this …
A machine learning Automated Recommendation Tool for synthetic biology
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 …