Computational Systems Biology of Cancer

7th edition - Spatial multimodal data analysis: when omics meet images

These are lecture and supplementary materials for the PhysiCell talk during the Computational Systems Biology of Cancer International Course 7th edition - Spatial multimodal data analysis: when omics meet images.

Lecture Slides

Introductory slides on agent-based modeling, our new modeling grammar, and key examples can be found here:

• Lecture: New Advances in intuitive agent-based modeling with PhysiCell

Mini PhysiCell Tutorial

This is a miniature, 2-hour tutorial series on building your first tumor-immune model with PhysiCell Studio, without any need to install a C++ compiler or write any code.

1. Minimal Setup for PhysiCell Studio
2. Tutorial 1: Moving around in PhyisCell Studio, and making a zombie-villager model
3. Tutorial 2: Creating a cancer-immune model

Papers

Key Papers

1. Ghaffarizadeh et al. (2018), PhysiCell Method Paper
2. Johnson et al. (2023). PhysiCell Grammar and Cancer Examples including Spatial Transcriptomics
3. Ponce-de-Leon et al. (2023) .PhysiBoSS 2.0
4. Heiland et al. (2024). PhysiCell Studio
5. Metzcar et al. (2019). Agent-Based Modeling Review for Cancer

Ecosystem Papers

coming son PhysiMeSS, PhysiBoSS, PhysiCool, others?

Some Examples of PhysiCell Modeling

1. Wang et al. (2024). Cancer nanotherapy modeling
2. Rocha et al. (2021). Cancer hypoxia modeling
3. Rocha et al. (2024). Cancer-immune interactions modeling on HPC, lessons for digital twins
4. Wang et al. (2021). Cancer-parenchyma interaction modeling.
5. Metzcar et al. (2022). Simplified ECM Modeling
6. Jenner et al. (2022). Oncolytic virus therapy for glioblastoma
7. Getz et al. (2020). COVID-19 Modeling Coalition
8. Islam et al. (2023). Fibrois modeling in COVID-19.
9. Ozik et al. (2019). Learning-accelerated model exploration on HPC.
10. Ozik et al. (2018). High-throughput model exploration on HPC.

PhysiCell Tutorials

1. Ruscone et al. (2024). PhysiBoSS modeling in PhysiCell Studio