Mathematical Modeling

Research Statement

To eliminate ambiguity in understanding the molecular, genetic, and biochemical mechanisms that govern cellular responses to their environment, we employ mathematical modeling, such as ordinary differential equations (ODEs). ODEs enable us to predict a system’s behavior over time. When a mechanism is misunderstood, discrepancies arise between our mathematical predictions and observed cellular behaviors. 

1.  Mathematical Modeling of Protein Behaviors

Publications

(3)

Dale, R.; Ohmuro-Matsuyama, Y.; Ueda, H.; Kato, N. Non-Steady State Analysis of Enzyme Kinetics in Real Time Elucidates Substrate Association and Dissociation Rates: Demonstration with Analysis of Firefly Luciferase Mutants. Biochemistry 2019, 58 (23), 2695–2702. https://doi.org/10.1021/acs.biochem.9b00272.

(2)

Dale, R.; Kato, N. Truly Quantitative Analysis of the Firefly Luciferase Complementation Assay. Current Plant Biology 2016, 5, 57–64. https://doi.org/10.1016/j.cpb.2016.02.002.

(1) 

Dale, R.; Ohmuro-Matsuyama, Y.; Ueda, H.; Kato, N. Mathematical Model of the Firefly Luciferase Complementation Assay Reveals a Non-Linear Relationship between the Detected Luminescence and the Affinity of the Protein Pair Being Analyzed. PLoS ONE 2016, 11 (2).https://doi.org/10.1371/journal.pone.0148256

2.  Mathematical Modeling of Cell Behaviors

Publications

(3) 

Ndathe, R.; Dale, R.; Kato, N. Dynamic Modeling of ABA-Dependent Expression of the Arabidopsis RD29A Gene. Frontiers in Plant Science 2022, 13. https://doi.org/10.3389/fpls.2022.928718.

(2) 

He, H.; Kato, N. Equilibrium Submanifold for a Biological System. Discrete and Continuous Dynamical Systems - Series S 2011, 4 (6), 1429–1441. https://doi.org/10.3934/dcdss.2011.4.1429.

(1) 

Kato, N.; He, H.; Steger, A. P. A Systems Model of Vesicle Trafficking in Arabidopsis Pollen Tubes. Plant Physiology 2010, 152 (2), 590–601. https://doi.org/10.1104/pp.109.148700.