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Vivarium: an interface and engine for integrative multiscale modeling in computational biology

View ORCID ProfileEran Agmon, View ORCID ProfileRyan K. Spangler, Christopher J. Skalnik, William Poole, View ORCID ProfileShayn M. Peirce, Jerry H. Morrison, View ORCID ProfileMarkus W. Covert
doi: https://doi.org/10.1101/2021.04.27.441657
Eran Agmon
1Department of Bioengineering Stanford University Stanford, CA, USA
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  • For correspondence: agmon.eran@gmail.com mcovert@stanford.edu
Ryan K. Spangler
2Allen Institute for Cell Science Seattle, WA, USA
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Christopher J. Skalnik
1Department of Bioengineering Stanford University Stanford, CA, USA
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  • For correspondence: mcovert@stanford.edu
William Poole
3Computation and Neural Systems California Institute of Technology Pasadena, CA, USA
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Shayn M. Peirce
4Department of Biomedical Engineering University of Virginia Charlottesville, VA, USA
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Jerry H. Morrison
1Department of Bioengineering Stanford University Stanford, CA, USA
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  • For correspondence: mcovert@stanford.edu
Markus W. Covert
1Department of Bioengineering Stanford University Stanford, CA, USA
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Abstract

Motivation This paper introduces Vivarium – software born of the idea that it should be as easy as possible for computational biologists to define any imaginable mechanistic model, combine it with existing models, and execute them together as an integrated multiscale model. Integrative multiscale modeling confronts the complexity of molecular and cellular biology by combining heterogeneous datasets and diverse mechanistic modeling strategies into unified representations. These integrated models are then run to simulate how the hypothesized mechanisms operate as a whole. But building such models has been a labor-intensive process that requires many contributors, and they are still primarily developed on a case-by-case basis with each project starting anew. New software tools that streamline the integrative modeling effort and facilitate collaboration are therefore essential for future computational biologists.

Results Vivarium is a software tool for building integrative multiscale models. It provides an interface that can make any mechanistic model into a module that can be wired together into larger composite models and then parallelized and run across multiple CPUs with Vivarium’s simulation engine. The utility of this software is demonstrated by building multi-paradigm composite models that combine several popular modeling frameworks: agent based models, ordinary differential equations, stochastic reaction systems, constraint-based models, solid-body physics, and spatial diffusion. This demonstration shows just the beginning of what is possible – future efforts can integrate many more types of models and at many more biological scales.

Availability The simulations and output used for this paper are available as Jupyter notebooks at https://github.com/vivarium-collective/vivarium-notebooks. The vivarium-core multiscale engine has been released as a PyPI library and can be installed with pip install vivarium-core. Additionally, vivarium-core is open-sourced for development at https://github.com/vivarium-collective/vivarium-core. Vivarium libraries used for this paper are listed in the Supplementary materials.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • https://github.com/vivarium-collective/vivarium-core

  • https://github.com/vivarium-collective/vivarium-notebooks

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted April 28, 2021.
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Vivarium: an interface and engine for integrative multiscale modeling in computational biology
Eran Agmon, Ryan K. Spangler, Christopher J. Skalnik, William Poole, Shayn M. Peirce, Jerry H. Morrison, Markus W. Covert
bioRxiv 2021.04.27.441657; doi: https://doi.org/10.1101/2021.04.27.441657
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Vivarium: an interface and engine for integrative multiscale modeling in computational biology
Eran Agmon, Ryan K. Spangler, Christopher J. Skalnik, William Poole, Shayn M. Peirce, Jerry H. Morrison, Markus W. Covert
bioRxiv 2021.04.27.441657; doi: https://doi.org/10.1101/2021.04.27.441657

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