Paul Macklin

PhysiCelldFBA links single-cell metabolism to multicellular spatial dynamics by integrating genome-scale metabolic models with agent-based simulations.

UQ-PhysiCell provides a Python framework for uncertainty quantification, calibration, and model analysis in PhysiCell simulations, enabling scalable and reproducible uncertainty-aware analysis of agent-based models.

This paper introduces a trajectory-centric framework to model dynamic tumor-immune interactions, showing that treatment-phase TME states predict immunotherapy response better than pre-treatment states.

This study develops a multicellular agent-based model to simulate nanoparticle interactions in cancer therapy and evaluates how pharmacokinetic parameters and therapeutic strategies affect tumor dynamics.

PhysiGym integrates PhysiCell with Gymnasium to enable reinforcement learning control of in silico biological processes, demonstrating tumor elimination in a case study.

This paper develops a computational model to study how cancer cells interact with and remodel the extracellular matrix, revealing how structural and chemical cues influence invasion.

The paper introduces a framework for mathematical modeling of multicellular systems using interpretable cell behavior rules derived from biological knowledge and multi-omics data.

This paper presents a community-driven benchmarking initiative for cell-based multiscale models, highlighting variations in tool implementations and advocating for standardized benchmarks and interoperability.

The paper uses AI and citizen science data to show that a 2024 solar eclipse caused significant behavioral changes in North American birds due to disrupted light cycles.

The paper introduces a simplified agent-based framework for modeling cell-ECM interactions using PhysiCell, demonstrating its utility in various biological processes.

The paper integrates computational metabolic modeling with experimental validation to identify hexokinase as a therapeutic target in colorectal cancer by analyzing CAF-conditioned tumor organoids.

The paper develops a multiscale mathematical model of immune surveillance in micrometastases to simulate patient trajectories and identify key parameters affecting immunosurveillance outcomes.

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.

The paper introduces cloud-hosted open-source tools to help researchers learn cell-based simulation software through modular exploration of key components.

This study investigates tumor-stromal metabolic interactions in colorectal cancer by integrating constraint-based models with metabolomics data, revealing how cancer-associated fibroblasts reprogram tumor cell metabolism.

This study uses multi-model simulations to show how liver parenchyma biomechanics influence metastatic tumor growth and dormancy.

Open-source agent-based PhysiCell model of SARS-CoV-2 infection in lung epithelium; version 5 clears virus in about 6 days in simulation, and delayed T cell arrival increases epithelial loss.

xml2jupyter maps XML configuration files to Jupyter widgets, enabling interactive simulation parameter tuning.

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

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 introduces an experimental-computational pipeline to quantify cancer cell migration, showing that blocking sAGR2 reduces migration of MDA-MB-231 cells.

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 reviews open source software and data standards in multicellular systems biology and highlights areas for growth to enable community-driven frameworks.

This paper develops a mathematical model to account for biological and technical variability in cell proliferation assays and shows how these factors affect growth rate measurements.

The paper introduces MultiCellDS, a standard and community-driven initiative for sharing multicellular data to enhance research in cell biology.

The paper introduces MultiCellDS, a standard for multicellular data curation, and presents MultiCellDB as a database to store associated data, enhancing data sharing and utility in biological and clinical research.

The paper describes a method to estimate cell cycle model parameters using optimization tools with flow cytometry and synthetic viability data, demonstrated on simulated data.

The paper introduces PhysiCell, an agent-based model for simulating tumor growth in 3-D microenvironments, and reports its scalability to large cell systems.

The paper introduces BioFVM, a reaction-diffusion solver for simulating chemical transport in 3-D tissues, supporting multiple compounds and demonstrating efficient computational scaling.