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 …

Machine learning-enabled retrobiosynthesis of molecules

T Yu, AG Boob, MJ Volk, X Liu, H Cui, H Zhao - Nature Catalysis, 2023 - nature.com
Retrobiosynthesis provides an effective and sustainable approach to producing functional
molecules. The past few decades have witnessed a rapid expansion of biosynthetic …

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 …

Embracing nature's catalysts: a viewpoint on the future of biocatalysis

B Hauer - Acs Catalysis, 2020 - ACS Publications
Enzymes are nature's catalysts that are designed to accelerate specific reactions up to 106
times with high selectivity. 1 The enormous potential of enzymes as catalysts for organic …

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 …

Machine learning in bioprocess development: from promise to practice

LM Helleckes, J Hemmerich, W Wiechert… - Trends in …, 2023 - cell.com
Fostered by novel analytical techniques, digitalization, and automation, modern bioprocess
development provides large amounts of heterogeneous experimental data, containing …

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 …

Recent advances in machine learning applications in metabolic engineering

P Patra, BR Disha, P Kundu, M Das, A Ghosh - Biotechnology Advances, 2023 - Elsevier
Metabolic engineering encompasses several widely-used strategies, which currently hold a
high seat in the field of biotechnology when its potential is manifesting through a plethora of …

Big data and machine learning driven bioprocessing–recent trends and critical analysis

CT Yang, E Kristiani, YK Leong, JS Chang - Bioresource technology, 2023 - Elsevier
Given the potential of machine learning algorithms in revolutionizing the bioengineering
field, this paper examined and summarized the literature related to artificial intelligence (AI) …