Abstract
We investigate a system of delay partial differential equations that models the growth of human tumor cells and their responses to therapy. The model includes unknown parameters that need to be estimated according to experimental data. We introduce a numerical algorithm, which shortens the computational time for solving the model equations and estimating their parameters. Numerical results demonstrate the efficiency of our algorithm and show correspondence between predicted and experimental data.
Original language | American English |
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Journal | Mathematics Faculty Publications and Presentations |
State | Published - 1 Mar 2014 |
Keywords
- delay partial differential equations
- human cell cycle dynamics
- integro-delay term with nonlinear kernel
- number densities of cells
- relative DNA content
EGS Disciplines
- Mathematics