Escherichia coli is considered to be the best-known microorganism given the large number
of published studies detailing its genes, its genome and the biochemical functions of its …

Genome-scale metabolic models (GEMs) computationally describe gene-protein-reaction
associations for entire metabolic genes in an organism, and can be simulated to predict …

The human microbiome influences the efficacy and safety of a wide variety of commonly
prescribed drugs. Designing precision medicine approaches that incorporate microbial …

Through advanced mechanistic modeling and the generation of large high-quality datasets,
machine learning is becoming an integral part of understanding and engineering living …

The sustainable production of chemicals from renewable, nonedible biomass has emerged
as an essential alternative to address pressing environmental issues arising from our heavy …

Natural products are widely employed in our daily lives as food additives, pharmaceuticals,
nutraceuticals, and cosmetic ingredients, among others. However, their supply has often …

Genome-scale metabolic models (GEMs) represent extensive knowledgebases that provide
a platform for model simulations and integrative analysis of omics data. This study …

Genome-scale metabolic models are instrumental in uncovering operating principles of
cellular metabolism, for model-guided re-engineering, and unraveling cross-feeding in …

Current machine learning techniques enable robust association of biological signals with
measured phenotypes, but these approaches are incapable of identifying causal …

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 …