Mathematical Biology Tumor Growth

The paper presents a framework combining agent-based simulation and active learning to discover optimal cancer regression regions in immunotherapy models.

The paper develops a free boundary model to describe epithelial dynamics by deriving a continuum-limit PDE that accurately predicts cell-based model behavior with a mass-conserving boundary condition.

This paper introduces a high-throughput framework integrating PhysiCell and EMEWS to test cancer hypotheses through mechanistic simulations and optimize therapeutic strategies.

PhysiBoSS integrates multi-scale agent-based modelling with Boolean networks to study cell population dynamics and treatment responses in 2D and 3D environments.

This paper develops a multi-state model to analyze chemoresistance dynamics in breast cancer using experimental and mathematical modeling approaches.

The paper uses a computational model to identify tumor growth kinetic parameters as prognostic biomarkers for anti-angiogenic treatment outcomes.

The paper develops an agent-based model to predict tumor spheroid growth under mechanical stress across different conditions and cell lines.

Open source off-lattice agent-based C++ simulator PhysiCell, coupled to the BioFVM diffusion solver, simulates 3-D multicellular tissues with cost linear in cell number, reaching roughly 10^6 cells.

The paper models clonal dominance in tumor cells by showing that varying division rates, not stem cell properties or random growth, lead to clonal dominance in vitro.

This paper introduces a simulation-based metric, Days Gained, to assess glioblastoma response to therapy using MRI-derived growth models.

This study uses computational modeling to show that tumor growth kinetics influence the response to anti-VEGF treatment, with nonlinear dependence on VEGF receptor expression.

The paper introduces a hybrid method to estimate parameters in agent-based models using glioblastoma data to improve model calibration.

The paper studies radially-symmetric anisotropic diffusion to model aggregation phenomena in biological systems without relying on chemotaxis or adhesion.

This paper derives non-local models of cell-cell adhesion and chemotaxis from a space-jump process and validates them with random walk simulations.

This review discusses mathematical and computational models addressing challenges in cancer immunotherapy, including tumor classification, treatment scheduling, and combination therapy design.

The paper develops a hierarchical Bayesian framework to model spatiotemporal dynamics of intestinal epithelium proliferation and migration under different conditions, concluding a proliferation-driven model is sufficient for most time-scales.

Microvessel Chaste provides an open-source library for building and simulating 3D spatial models of vascularized tissue growth, integrating with experimental data and Python tools.