CompuCell3D (CC3D) on nanoHUB

General Info

NanoHub is a shared, open, online computing platform for students, teachers and researchers. User can learn modeling, develop, run and share research models and learn from models developed by others. NanoHUB covers a range of applications from Artificial Intelligence, to electronics to biological modeling.

Click here --> CompuCell3D is available for online use on nanoHUB.
Note that if you are not already logged into nanoHUB this link will go to the login page. If you are logged in it will go directly to the CC3D page. The easiest way to get there is to click this link once (it will open a new browser tab) and log into nanoHUB, then click the link again to go to CC3D.

Some CompuCell3D simulations are already available as demos, for example: a macrophage hunting a bacterium, Cell Sorting, and the Covid-19 model described in more detail below.

• If you have a request or suggestion for a new simulation to be deployed in nanoHUB please go to our suggestion thread in our support forums.

• If you have a CompuCell3D simulation that you want to deploy on nanoHUB please see this github repository.

• The list of CompuCell3D models that have been implemented at nanoHUB is available here.

Call to Contribute: Collaborative Tissue Model Development to Mitigate the Coronavirus Pandemic

We have deployed a preliminary Covid-19 model in CompuCell3D on nanoHUB.

You can run our model online without any installations at https://nanohub.org/tools/cc3dcovid19

The rapidly evolving social and medical impact of COVID-19 requires equally rapid development of tools to predict, and ultimately ameliorate, the future course of the pandemic. Tools are needed to predict patient outcomes, to optimize the deployment of resources by medical providers, and to optimize therapy for infected individuals. Predictive computational simulations of the spread of the disease, and of the underlying biology that makes COVID-19 unique, are both essential. Our aim is to build cooperatively-developed, open-source multiscale model components that can predict various aspects of infection at molecular and tissue scales and inform higher-level models, and a framework to allow others to do so efficiently.

You can run our model online without any installations in https://nanohub.org/tools/cc3dcovid19.

COVID-19 Model Repository: Because of the urgency of the crisis, software development must be done in parallel and not sequentially as in normal scientific model development. As such, we are developing a model repository for the cooperative development of public, open-source molecular- and tissue-scale models and simulations of various infection events and health states associated with COVID-19. To support rapid parallel development, integration, and sharing of models and simulations, we are developing modeling and simulation tools specific to this project, as well as documentation tools and standards for rapid and consistent dissemination of repository contents. Please join us in our efforts to collectively mitigate the ongoing pandemic and future pandemics alike on GitHub. For more information, please contact us at <tjsego AT iu DOT edu>.

Model of Viral Tissue Infection: In support of parallel model development of tissue infection, the members of the Biocomplexity Institute are developing a multiscale computational model of viral tissue infection using CC3D. The model describes select interactions between generalized epithelial and immune cells and their extracellular environment associated with viral infection and immune response at the cellular and intracellular levels, and in the context of spatiotemporal dynamics. The model is a generic viral infection model, and our hope is to collaboratively develop it into a model of SARS-CoV-2 tissue infection and Covid-19 progression. As such, it is intended to serve as a base model for constructing and implementing more advanced models of targeted cellular- and intracellular-level phenomena in tissue after initial exposure. In its current state, it has not been formally peer-reviewed, and should not be used for patient diagnostics or predicting clinical outcomes. Rather, the model and its implementation can be used to develop and interrogate mechanistic hypotheses about the spread of a virus and how the interplay between viral spreading and immune response determine the outcome of the disease, such as:

• Why does the progression of the disease seem to be dependent on the initial viral exposure level?
• Why is the start time of symptoms and immune response so variable?
• What is the role of cytokine signaling in explaining immune response variability?

Model documentation and simulation files can be found in the project folder of our COVID-19 Model Repository. Please be advised that this is a rapidly evolving project, so model and simulation features are subject to change (even daily). For more information about how to contribute to, modify, or reuse the model and simulation, please contact us at <tjsego AT iu DOT edu>.

For information on recent modeling and repository developments, current development plans, and opportunities to contribute to current modeling and repository projects, please see our project page.