Yinjie Tang

NEKO is an AI workflow using LLMs to extract and organize scientific knowledge from literature, providing more specific and actionable insights than existing models.

BayFlux quantifies metabolic fluxes and their uncertainty using Bayesian inference, showing genome-scale models reduce flux uncertainty compared to core models and improve knockout predictions.

The paper optimizes a P. putida strain for indigoidine production using 13C-MFA and metabolomics, identifying key metabolic bottlenecks and engineering improvements.