Shinsuke Uda

The paper develops mathematical models of insulin signaling in obese mice to show that changes in protein expression levels explain signal attenuation and identify mechanisms of selective insulin resistance.

The paper develops a mathematical model to predict an optimal glucose ingestion pattern that minimizes peak blood glucose levels in humans, validated through experimental testing.

The paper analyzes trans-omic data from healthy and obese mice to reveal that glucose-responsive liver metabolism is regulated by rapid changes in metabolites and gene expression in the healthy state, and by slow transcriptional regulation in the obese state.

The paper shows that small intracellular and large intercellular variations enhance information transmission, enabling precise tissue function control.

The paper develops a mathematical model to show that bidirectional changes in hepatic and peripheral insulin clearance explain abnormal serum insulin concentration patterns in diabetic subjects.

The paper develops a system identification method using compressed sensing to analyze signaling-decoding systems with different time scales, revealing gene expression responses to signaling activation.

The paper constructs a trans-omic network of insulin action using phosphoproteomic, transcriptomic, and metabolomic data to identify fed and fasting insulin signals.