One goal of GLIMPRINT is to create web-based resource where models relevant to immunology and digital twins can be hosted. Easy access to models in a runnable form is critical for education and for communicating the capabilities (and limitations) of computational models. The model should include a clear description of what is included, and should allow the user to run the model easily with the capability of modifying parameters and exploring outputs. We are particularly interested in the educational power of basic models that can be run interactively in a web browser.
Models will cover a range of complexities, from simple viral infection SIR (susceptible - infected - recovered) models in JavaScript or SBML running in a browser or Jupyter Notebook (or as a NetLogo model), to complex multiscale models that include discreet cells, subcellular processes, immune response, etc.
We list here three types of models:
- Ones that can be run directly here on GLIMPRINT web pages
- Ones the can be run in a web browser at other online sites
- Models that require download of the model and needed software
Models that can be directly run on GLIMPRINT web pages.
- A simple infection SIR (susceptible - infected - recovered) model in JavaScript that will run directly in your browser.
This model was created by Lorenzo Felletti whom we thank for sharing.
Models that can be run in a web browser at a site other then GLIMPRINT.
Models hosted at nanoHUB
- nanoHUB is funded by the NSF and others, and is an online computing host for a range of computational models in nanotechnology, physics and biology. NanoHUB supports a wide range of computing languages and has been used to tech both scientific and computing techniques. Running a model requires a user account, which is free. See https://nanohub.org/, to register visit https://nanohub.org/register/. Note that you must be a registered user and logged in to nanoHUB with your browser before the links to models given below will work properly.
- Sego et al: Multiscale, multicellular, spatiotemporal modeling of acute primary viral infection and immune response in epithelial tissues. (Click the link to go to the GLIMPRINT page with more info.)
Models runnable on NetLogo
NetLogo (https://ccl.northwestern.edu/netlogo is is a modeling language for agent-based models (ABMs). It can be run as either a local application on your computer or remotely via a web browser.
- Cockrell and An, Comparative Computational Modeling of the Bat and Human Immune Response to Viral Infection with the Comparative Biology Immune Agent Based Model (Click the link to go to the GLIMPRINT info page.)
Models that must be downloaded along with the suitable program to run the model.
We will limit to only software packages that are free and open source.
Models using Morpheus 
: A modeling and simulation environment for the study of multi-scale and multicellular systems
- Infection of Human Airway Epithelium by Raach et al., The spread of viral infections within tissues depends on several factors including the spatial distribution and turnover dynamics of target cells. In Raach et al. (2023), a Cellular Potts model was developed to investigate the influence of target cell heterogeneity within the human airway epithelium on SARS-CoV-2 infection dynamics. The study aims to understand how different tissue compositions and regenerative turnover throughout the respiratory tree affect the progression of SARS-CoV-2 infections. The model incorporates cell-type specific infection kinetics, tissue regeneration, and accounts for both global and local spread of infections through cell-free and cell-associated viral transmission mechanisms.
Parameterization of the model is achieved by integrating published experimental data on differentiating primary human bronchial epithelial cells within air-liquid interface cultures through approximate Bayesian computation (de Borja Callejas et al., 2014, Schamberger et al., 2015). By simulating SARS-CoV-2 infections given various tissue compositions and regenerative capacities, the model provides insights into cell-type specific infection dynamics and the impact of tissue composition on disease progression and pathology. PLOS Comp. Biol. 2023: https://identifiers.org/morpheus/M6296
- Viral dynamics in monkey and bat cell lines by Brook et al., Brook et al. assumed the cells to have either of the following five states:
- Susceptible (S)
- Antiviral (A)
- Exposed (E)
- Infectious (I)
- Dead (D)
- Kupffer Cell and Macrophage Dynamics, Detoxification and Liver Injury from Acetaminophen (APAP) by Heldring et al., The CPM is used to model the interacting cell types hepatocytes, residential Kupffer cells and macrophages. PDEs and ODEs are used to model APAP distribution and hepatocellular metabolism, necrotic cell death and macrophage recruitment, DNA damage response activation and the regulation of senescence and proliferation. NPJ Syst. Biol. 2022: https://identifiers.org/morpheus/M9496
- Spatial Effects on Killing Kinetics of Cytotoxic T Lymphocytes by Beck et al., An agent based cellular Potts model (CPM) was employed to generate 2D simulations of CTLs interacting with and killing targets over a period of 12 hours (StopTime = 43200 s). For all CPM simulations the same underlying gamma model of CTL hit generation was maintained as was used for the Monte-Carlo simulations, however several modifications were made that would lead to different (yet not predictable a priori) distributions of hits amongst targets. PLOS Comp. Biol. 2020: https://identifiers.org/morpheus/M9495
- Immunological/chemical synapse by Müller. A cell in Morpheus can act in an anisotropic manner by using a heterogeneously patterned MembraneProperty - here called m. These are Properties with a spatial resolution (a 1D or 2D array, defined under Space/MembraneLattice) that are mapped to the cell’s membrane in polar coordinates in 2D or 3D, respectively. One can use this to represent cell polarity and give directionality to processes. Morpheus model repository 2023: https://identifiers.org/morpheus/M1175
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Mass-conserving secretion and uptake of a diffusible signal/pathogen/virus by Brusch. The mass-conserving secretion and uptake of (signaling) molecules by cells can in Morpheus be achieved with Mappers and scaling fluxes by cell.volume. The intracellular amount of signal may trigger a change in a state variable that could downstream change cell behaviors. This model, motivated by the user forum, shall demonstrate how such signaling processes can be coupled via a global field of diffusible molecules and how conservation of mass can be monitored over populations of cells. Morpheus model repository 2023: https://identifiers.org/morpheus/M5491
Models using CompuCell3D 
: A modeling system based on the Potts Model for modeling multicellualr systems.
- A multiscale multicellular spatiotemporal model of local influenza infection and immune response, Sego et al.
In this work, we develop a multiscale, multicellular spatiotemporal model of influenza infection and immune response by combining non-spatial ODE modeling and spatial, cell-based modeling. We employ cellularization, a recently developed method for generating spatial, cell-based, stochastic models from non-spatial ODE models, to generate much of our model from a calibrated ODE model that describes infection, death and recovery of susceptible cells and innate and adaptive responses during influenza infection, and develop models of cell migration and other mechanisms not explicitly described by the ODE model. We can also combine our model with available experimental data and modeling of exposure scenarios and spatiotemporal aspects of mechanisms like mucociliary clearance that are only implicitly described by the ODE model. J Theor Biol. 2022 Jan 7;532:110918. doi: 10.1016/j.jtbi.2021.110918. Epub 2021 Sep 27. PMID: 34592264; PMCID: PMC8478073. Source code.