Machine learning-enabled retrobiosynthesis of molecules
Retrobiosynthesis provides an effective and sustainable approach to producing functional
molecules. The past few decades have witnessed a rapid expansion of biosynthetic …
molecules. The past few decades have witnessed a rapid expansion of biosynthetic …
Networks and graphs discovery in metabolomics data analysis and interpretation
Both targeted and untargeted mass spectrometry-based metabolomics approaches are used
to understand the metabolic processes taking place in various organisms, from prokaryotes …
to understand the metabolic processes taking place in various organisms, from prokaryotes …
Deep learning-based kcat prediction enables improved enzyme-constrained model reconstruction
Enzyme turnover numbers (k cat) are key to understanding cellular metabolism, proteome
allocation and physiological diversity, but experimentally measured k cat data are sparse …
allocation and physiological diversity, but experimentally measured k cat data are sparse …
eQuilibrator 3.0: a database solution for thermodynamic constant estimation
ME Beber, MG Gollub, D Mozaffari… - Nucleic acids …, 2022 - academic.oup.com
Abstract eQuilibrator (equilibrator. weizmann. ac. il) is a database of biochemical equilibrium
constants and Gibbs free energies, originally designed as a web-based interface. While the …
constants and Gibbs free energies, originally designed as a web-based interface. While the …
Rhea, the reaction knowledgebase in 2022
P Bansal, A Morgat, KB Axelsen… - Nucleic acids …, 2022 - academic.oup.com
Abstract Rhea (https://www. rhea-db. org) is an expert-curated knowledgebase of
biochemical reactions based on the chemical ontology ChEBI (Chemical Entities of …
biochemical reactions based on the chemical ontology ChEBI (Chemical Entities of …
Deep learning driven biosynthetic pathways navigation for natural products with BioNavi-NP
The complete biosynthetic pathways are unknown for most natural products (NPs), it is thus
valuable to make computer-aided bio-retrosynthesis predictions. Here, a navigable and user …
valuable to make computer-aided bio-retrosynthesis predictions. Here, a navigable and user …
Turnover number predictions for kinetically uncharacterized enzymes using machine and deep learning
A Kroll, Y Rousset, XP Hu, NA Liebrand… - Nature …, 2023 - nature.com
The turnover number k cat, a measure of enzyme efficiency, is central to understanding
cellular physiology and resource allocation. As experimental k cat estimates are unavailable …
cellular physiology and resource allocation. As experimental k cat estimates are unavailable …
Merging enzymatic and synthetic chemistry with computational synthesis planning
Synthesis planning programs trained on chemical reaction data can design efficient routes
to new molecules of interest, but are limited in their ability to leverage rare chemical …
to new molecules of interest, but are limited in their ability to leverage rare chemical …
Machine learning for the advancement of genome-scale metabolic modeling
Constraint-based modeling (CBM) has evolved as the core systems biology tool to map the
interrelations between genotype, phenotype, and external environment. The recent …
interrelations between genotype, phenotype, and external environment. The recent …
Mixotrophic growth of a ubiquitous marine diatom
Diatoms are major players in the global carbon cycle, and their metabolism is affected by
ocean conditions. Understanding the impact of changing inorganic nutrients in the oceans …
ocean conditions. Understanding the impact of changing inorganic nutrients in the oceans …