Metabolic engineering: methodologies and applications

MJ Volk, VG Tran, SI Tan, S Mishra, Z Fatma… - Chemical …, 2022 - ACS Publications
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 …

Microbial production of advanced biofuels

J Keasling, H Garcia Martin, TS Lee… - Nature Reviews …, 2021 - nature.com
Concerns over climate change have necessitated a rethinking of our transportation
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

M Alber, A Buganza Tepole, WR Cannon, S De… - NPJ digital …, 2019 - nature.com
Fueled by breakthrough technology developments, the biological, biomedical, and
behavioral sciences are now collecting more data than ever before. There is a critical need …

Common principles and best practices for engineering microbiomes

CE Lawson, WR Harcombe, R Hatzenpichler… - Nature Reviews …, 2019 - nature.com
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 …

Machine learning for metabolic engineering: A review

CE Lawson, JM Martí, T Radivojevic… - Metabolic …, 2021 - Elsevier
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 …

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 …

Machine learning meets omics: applications and perspectives

R Li, L Li, Y Xu, J Yang - Briefings in Bioinformatics, 2022 - academic.oup.com
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 …

Machine learning applications for mass spectrometry-based metabolomics

UW Liebal, ANT Phan, M Sudhakar, K Raman… - Metabolites, 2020 - mdpi.com
The metabolome of an organism depends on environmental factors and intracellular
regulation and provides information about the physiological conditions. Metabolomics helps …

Multiscale modeling meets machine learning: What can we learn?

GCY Peng, M Alber, A Buganza Tepole… - … Methods in Engineering, 2021 - Springer
Abstract Machine learning is increasingly recognized as a promising technology in the
biological, biomedical, and behavioral sciences. There can be no argument that this …

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 …