Tin Pang receives APBC 2026 Best Paper Award
October 29, 2026
We congratulate Tin Pang, the recipient of the APBC 2026 Best Paper Award!
This prestigious award recognizes Tin Pang’s innovative workflow for integrating dynamic DMI data with genome-scale metabolic modeling (GEM).
Bridging noninvasive tracer imaging with network-level metabolic inference, his work advances our ability to investigate tissue-specific metabolic activity through adequately identified signals.
The workflow incorporates shared plasma input, tissue-specific kinetics, voxel-level fluxes, isotope effects, and measurement uncertainty, providing a comprehensive framework for connecting imaging data with metabolic modeling.
Congratulations to Tin Pang on this great achievement
