Mathematical Biology Tumor Growth

Integrating mechanism-based T cell phenotypes into a model of tumor-immune cell interactions

The paper develops an integrated Boolean-ABM framework to study how CD8+ T cell properties affect tumor composition, spatial organization, and immune checkpoint blockade efficacy.

Mathematical Modelling of Microtube-Driven Regrowth ofGlioma After Local Resection

This study develops a mathematical model to simulate glioma regrowth after resection, showing that tumor microtubes drive rapid regrowth and spread through wound healing mechanisms.

Modeling tumors as species-rich ecological communities

The paper models tumors as ecological communities using the Generalized Lotka-Volterra model to understand intra-tumor heterogeneity and its implications for cancer progression and treatment resistance.

Design of two-stage multi-drug chemotherapy schedules using replicator game dynamics

This paper designs a two-stage multi-drug chemotherapy schedule using replicator game dynamics to maintain tumor cell populations in a high-entropy coexistence state and prevent chemoresistance.

PhysiCell Studio: a graphical tool to make agent-based modeling more accessible

PhysiCell Studio is a graphical tool that simplifies the creation and editing of multicellular models by providing a user-friendly interface for XML-based model definition.

Optimal control of Multiple Myeloma assuming drug evasion and off-target effects

This paper models Multiple Myeloma treatment with Daratumumab, incorporating drug evasion and off-target effects, and uses optimal control to show increased treatment duration and costs.

An agent-based modelling framework for tumour growth incorporating mechanical and evolutionary aspects of cell dynamics

This paper develops an agent-based model of tumor growth that integrates mechanical and evolutionary dynamics, showing phenotypic heterogeneity arises from oxygen distribution inhomogeneities.

The role of noise in the tumour-immune interactions reveals memoryless shifting response

The paper analyzes how randomness affects immune-cancer cell interactions, showing a bistable response with memoryless switching between stable states.

Examination of the role of mutualism in immune evasion

This study uses a computational simulation to show that mutualism enhances immune evasion in slow-growing tumors, increasing their survival chances compared to tumors without mutualism.

A Comprehensive Model to Differentiate Spontaneous, Drug-induced, and CSCs-related Drug Resistance

This study develops a mathematical model to differentiate types of drug resistance and evaluates treatment strategies, finding that bolus injection can extend survival at equivalent cumulative dosages.

Simple data-driven agent-based model of scratch assays on healthy and keloid fibroblasts

The paper develops a simple agent-based model to simulate cell migration and interactions in scratch assays, showing good agreement with experimental data and providing insights into keloid fibroblast behavior.

Visualizing the Spatio-Temporal Dynamics of Clonal Evolution with LinG3D software

The paper introduces LinG3D software to visualize spatio-temporal clonal evolution in tumors, demonstrating its use in simulations and experimental assays.

Incorporating temporal information during featureengineering bolsters emulation of spatio-temporalemergence

The paper improves machine learning emulation of a tumor microenvironment model by incorporating temporal information from intermediate simulation states, enhancing predictive performance.

Enhanced perfusion following exposure to radiotherapy: a theoretical investigation

This paper identifies vascular features that enhance perfusion after radiotherapy and develops a computational model to explore their impact on tumour response.

Calibration of Agent Based Models for Monophasic and Biphasic Tumour Growth using Approximate Bayesian Computation

This paper calibrates agent-based models of tumour growth using approximate Bayesian computation to estimate parameters and quantify uncertainty in biphasic growth models.

An adaptive numerical method for multi-cellular simulations of tissue development

This paper reviews numerical methods for multi-cellular tissue simulations and introduces an adaptive time-stepping algorithm that improves efficiency and accuracy.

Challenging age-structured and first order transition cell cycle models of cell proliferation

The paper challenges age-structured and first order transition models of cell proliferation by testing their fit to time course data from cancer cell line experiments.

A calibration and uncertainty quantification analysis of classical, fractional and multiscale logistic models of tumour growth

This study evaluates classical, fractional, and multiscale logistic models of tumour growth using Bayesian inference and uncertainty quantification to assess their fit under different treatment conditions.

PhysiBoSS 2.0: a sustainable integration of stochastic Boolean and agent-based modelling frameworks

PhysiBoSS 2.0 integrates stochastic Boolean and agent-based models for multiscale cancer simulations, improving modularity and functionality.

Spatial heterogeneity in tumor adhesion qualifies collective cell migration

This paper uses a computational model to show how spatial heterogeneity in cell adhesion affects collective cell migration in tumors.

Agent-based modeling of tumor-immune interactions reveals determinants of final tumor states

The paper uses an agent-based model to simulate tumor-immune interactions and identifies how macrophages and T cells influence tumor progression and final states.

Empirical methods for the validation of Time-To-Event mathematical models taking into account uncertainty and variability: Application to EGFR+ Lung Adenocarcinoma.

The paper introduces four empirical methods to validate time-to-event models in EGFR+ lung adenocarcinoma, considering uncertainty and variability, and shows their context-dependent effectiveness.

The interplay between lumen pressure and cell proliferation determines organoid morphology in a multicellular phase field model

This paper develops a multicellular phase field model to simulate organoid morphology by integrating lumen pressure and cell proliferation, revealing how these factors determine organoid shapes and phenotypes.

Gell: A GPU-powered 3D hybrid simulator for large-scale multicellular system

Gell is a GPU-based hybrid simulator for large-scale multicellular systems that achieves 150X speedup and 10X lower memory use compared to CPU-based methods.

Collective cell migration due to guidance-by-followers is robust to multiple stimuli

The paper investigates how collective cell migration is robust to different integration strategies of guidance stimuli using an individual-based model.

Exploring the onset and progression of prostate cancer through a multicellular agent-based model

This study develops an agent-based model of prostate cancer progression, showing that stochastic interactions and systematic factors influence tumor development and clinical outcomes.

Unified Tumor Growth Mechanisms from Multimodel Inference and Dataset Integration

The paper uses Bayesian multimodel inference to analyze tumor growth mechanisms in SCLC, finding that high lineage plasticity, not rare stem-like populations, drives tumor evolution.

Statistical inference of the rates of cell proliferation and phenotypic switching in cancer

This paper develops a statistical framework to estimate cell proliferation and phenotypic switching rates in cancer using cell line experiment data and applies it to a public dataset.

Multiscale model of the different modes of cancer cell invasion

The paper presents a multiscale model of cancer cell invasion using PhysiBoSS, integrating spatial and intracellular processes to study migration modes and validate against experimental data.

Adaptive therapy in cancer: the role of restrictions in the accumulation of mutations

This paper develops a spatially explicit agent-based model to simulate tumor growth and adaptive therapy, showing that mutation order restrictions affect genotype predictions and therapy outcomes.