A neural-mechanistic hybrid approach improving the predictive power of genome-scale metabolic models
Abstract Constraint-based metabolic models have been used for decades to predict the phenotype of microorganisms in different environments.However, quantitative predictions are limited unless labor-intensive measurements of media grandpas best uptake fluxes are performed.We show how hybrid neural-mechanistic models can serve as an architecture for