Uncertainty aware integration of DMI with genome scale metabolic modeling - A presentation at the APBC 2026

Tin Pang presents a novel workflow that integrates dynamic DMI data with genome-scale metabolic modeling (GEM) wich also accounts for shared plasma input, tissue-specific kinetics, voxel-level fluxes, isotop effects and measurement uncertainty.
This framework connects noninvasive tracer imaging with network-level metabolic inference while focusing on adequately identified signals.

For more information, join us at the 24th Asia Pacific Bioinformatics Conference (APBC) on October 23rd, 2026