Most research aiming at understanding the molecular foundations of life and disease has
focused on a limited set of increasingly well-known proteins while the biological functions of …

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 …

Microbial communities are composed of cells of varying metabolic capacity, and regularly
include auxotrophs that lack essential metabolic pathways. Through analysis of auxotrophs …

Schizophrenia is a severe neuropsychiatric disorder with a longstanding history of
neurobiological investigation. Although the underlying causal mechanisms remain …

Although artificial neural networks are powerful classifiers, their internal structures are hard
to interpret. In the life sciences, extensive knowledge of cell biology provides an opportunity …

The spread of antimicrobial resistance has become a serious public health concern, making
once-treatable diseases deadly again and undermining the achievements of modern …

Constraint-based reconstruction and analysis (COBRA) methods at the genome scale have
been under development since the first whole-genome sequences appeared in the mid …

Omic data analysis is steadily growing as a driver of basic and applied molecular biology
research. Core to the interpretation of complex and heterogeneous biological phenotypes …

The prediction of cellular function from a genotype is a fundamental goal in biology. For
metabolism, constraint-based modelling methods systematize biochemical, genetic and …

The role of epistasis in the genetic architecture of quantitative traits is controversial, despite
the biological plausibility that nonlinear molecular interactions underpin the genotype …