PhysiCell training apps: A case study for creating interactive training materials for scientific software packages

Sundus, Aneequa; Kurtoglu, Furkan; Konstantinopoulos, Kali; Chen, Mary; Willis, Drew; Heiland, Randy; Macklin, Paul

doi:10.1101/2022.06.24.497566

Cited by 3 publications

(4 citation statements)

References 26 publications

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“…We plan to synchronize their code bases in the future. In addition, there are interactive PhysiCell training modules that can be run in the browser [ 45 ] . …”

Section: Discussionmentioning

confidence: 99%

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

Heiland,

Bergman,

Lyons

et al. 2024

Gigabyte

Self Cite

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Defining a multicellular model can be challenging. There may be hundreds of parameters that specify the attributes and behaviors of objects. In the best case, the model will be defined using some format specification – a markup language – that will provide easy model sharing (and a minimal step toward reproducibility). PhysiCell is an open-source, physics-based multicellular simulation framework with an active and growing user community. It uses XML to define a model and, traditionally, users needed to manually edit the XML to modify the model. PhysiCell Studio is a tool to make this task easier. It provides a GUI that allows editing the XML model definition, including the creation and deletion of fundamental objects: cell types and substrates in the microenvironment. It also lets users build their model by defining initial conditions and biological rules, run simulations, and view results interactively. PhysiCell Studio has evolved over multiple workshops and academic courses in recent years, which has led to many improvements. There is both a desktop and cloud version. Its design and development has benefited from an active undergraduate and graduate research program. Like PhysiCell, the Studio is open-source software and contributions from the community are encouraged.

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“…We plan to synchronize their code bases in the future. In addition, there are interactive PhysiCell training modules that can be run in the browser [ 45 ] . …”

Section: Discussionmentioning

confidence: 99%

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

Heiland,

Bergman,

Lyons

et al. 2024

Gigabyte

Self Cite

View full text Add to dashboard Cite

show abstract

“…We plan to synchronize their code bases in the future. In addition, there are interactive PhysiCell training modules that can be run in the browser [18].…”

Section: Discussionmentioning

confidence: 99%

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

Heiland,

Bergman,

Lyons

et al. 2023

Preprint

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Defining a multicellular model can be challenging. There may be hundreds of parameters that specify the attributes and behaviors of objects. Hopefully the model will be defined using some format specification, e.g., a markup language, that will provide easy model sharing (and a minimal step toward reproducibility). PhysiCell is an open source, physics-based multicellular simulation framework with an active and growing user community. It uses XML to define a model and, traditionally, users needed to manually edit the XML to modify the model. PhysiCell Studio is a tool to make this task easier. It provides a graphical user interface that allows editing the XML model definition, including the creation and deletion of fundamental objects, e.g., cell types and substrates in the microenvironment. It also lets users build their model by defining initial conditions and biological rules, run simulations, and view results interactively. PhysiCell Studio has evolved over multiple workshops and academic courses in recent years which has led to many improvements. Its design and development has benefited from an active undergraduate and graduate research program. Like PhysiCell, the Studio is open source software and contributions from the community are encouraged.

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“…In particular, this work defined a behavioral cell phenotype that collects of biophysical characterizations of a cell's behavior, organized hierarchically by function: cycling, death, volume, mechanics, secretion (including uptake), and motility. Since releasing MultiCellDS as a preprint, we have tested this approach to cell behavior through a variety of agent-based simulation and modeling projects 42,57,58,90,91,[95][96][97][98][99][100] . Based upon recent immunologic modeling work [96][97][98][99] , we extended phenotype to include cell-cell interactions (phagocytosis, effector attack, and fusion), as well as transformations between cell types (e.g., differentiation, transdifferentiation, and other state changes that persist even when exogenous signals are removed).…”

Section: Cell Behaviorsmentioning

confidence: 99%

“…Similar to our prior work to create cloud-based training materials 98 and cloud-based model dissemination 95 , and inspired by other recent advances on “zero-install” models 137 , we have created a cloud-based version 94,138 of PhysiCell based on the nanoHUB platform 139 . This cloud implementation allows scientists to create, execute, visualize, and explore grammar-based models interactively in a web browser, without need for programming expertise or software setup.…”

Section: Code Availabilitymentioning

confidence: 99%

Digitize your Biology! Modeling multicellular systems through interpretable cell behavior

Johnson,

Stein-O’Brien,

Booth

et al. 2023

Preprint

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Cells are fundamental units of life. Recent technical advances have revolutionized our ability to quantify the state and identity of individual cells, and intercellular regulatory programs. However, these static measurements alone are limited in their ability to predict the complex collective behaviors that emerge from populations of many interacting cells over time. Mathematical models have a proven record of successfully predicting the behaviors of dynamic biological systems, e.g., therapeutic responses in cancer. Simulations from these models enable in silico visualization, examination, and refinement of biological models and can be used to generate new hypotheses about cells and their collective behavior. Agent-based modeling is particularly well-suited to studying communities of interacting cells, as it is intuitive to map a single cell to a single agent. Thus, we have developed a conceptual framing (with a reference implementation in the widely-used PhysiCell agent-based modeling framework) that can be initialized directly from single cell and spatial transcriptomic data, and that can be easily populated with interactive rules. Because the expert mathematical and computational knowledge required to build agent-based models has limited their widespread adoption in the biomedical research community, we engineered this framework to specify complex cellular responses to signals (or stimuli) using a single line of human readable text. This plain language text encodes cellular phenotypes and regulatory mechanisms from high throughput data and published literature, using a novel concept of hypothesis grammar. We motivate and fully describe this grammar and its philosophy, and then present a series of five example reference models of tumor growth and response to immunotherapy. Biologically, these examples demonstrate how mathematical models can predict from single cell and spatial transcriptomic data the cellular phenotypes responsible for tumor cell invasion and the simulation of immunotherapy treatment to overcome tumor cell growth. Computationally, these examples are designed to demonstrate how this conceptual framing and software implementation empower interdisciplinary teams to build an agent-based model of their experimental system, levering prior biological knowledge alone or in combination with information from spatial multi-omics technologies. Altogether, this approach provides an interface to bridge biological, clinical, and systems biology researchers for mathematical modeling of biological systems at scale, allowing the community to extrapolate from single-cell characterization to emergent multicellular behavior.

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PhysiCell training apps: A case study for creating interactive training materials for scientific software packages

Cited by 3 publications

References 26 publications

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

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

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

Digitize your Biology! Modeling multicellular systems through interpretable cell behavior

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