Evidence map›Paper›PMID 42853869›Full record

ArticlePLoS computational biology2026

Process bigraphs and the architecture of compositional systems biology.

Eran Agmon, Ryan K Spangler

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Article in PLoS computational biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Eran AgmonCenter for Cell Analysis and Modeling, University of Connecticut Health, Farmington, Connecticut, United States of America.ORCID https://orcid.org/0000-0003-1279-2474
Ryan K SpanglerCenter for Cell Analysis and Modeling, University of Connecticut Health, Farmington, Connecticut, United States of America.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Building multiscale biological models requires the integration of independently developed submodels, which means moving shared variables between them and coordinating when each submodel runs. Existing tools typically address isolated biological mechanisms with specific numerical methods, rarely specify which variables each model reads and writes, how those variables are translated, and how model updates are synchronized. We present Process Bigraph, a framework for composing and simulating multiscale models. Process Bigraph generalizes the architectural ideas previously used in the Vivarium software into a shared specification that describes process interfaces, hierarchical data structures, composition patterns, and orchestration patterns. The paper explains how the framework is organized and why it makes biological models easier to understand, reuse, and build on; S1 Text provides the formal specification. We introduce Vivarium 2.0 as an open-source implementation of the process bigraph framework. We demonstrate its utility with Spatio-Flux, a standalone library of microbial ecosystem simulations that combine kinetic equations, dynamic flux balance analysis, and different spatial processes. These simulations illustrated how the framework effectively integrates diverse biological processes, leading to emergent spatially organized population dynamics. Finally, we discuss implications for emerging multiscale modeling standards. Availability and implementation: Vivarium 2.0 is a suite of software libraries that include: (1) bigraph-schema, for defining and operating on data types within a hierarchical JSON-based format; (2) process-bigraph, for defining process interfaces, composite simulations, and executing them; and (3) viva-superpowers, for AI-assisted construction and composition of process bigraphs. Spatio-Flux is a reference application used in this paper to demonstrate the framework's utility. S1 Text provides detailed descriptions of these software libraries. All software is open-source and available at: https://github.com/vivarium-collective.

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Models, BiologicalSoftwareSystems BiologyAlgorithmsComputer SimulationEcosystem

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.