FitMultiCell: Simulating and parameterizing computational models of multi-scale and multi-cellular processes

Research output: Contribution to journalResearch articleContributedpeer-review



MOTIVATION: Biological tissues are dynamic and highly organized. Multi-scale models are helpful tools to analyze and understand the processes determining tissue dynamics. These models usually depend on parameters that need to be inferred from experimental data to achieve a quantitative understanding, to predict the response to perturbations, and to evaluate competing hypotheses. However, even advanced inference approaches such as Approximate Bayesian Computation (ABC) are difficult to apply due to the computational complexity of the simulation of multi-scale models. Thus, there is a need for a scalable pipeline for modeling, simulating, and parameterizing multi-scale models of multi-cellular processes.

RESULTS: Here, we present FitMultiCell, a computationally efficient and user-friendly open-source pipeline that can handle the full workflow of modeling, simulating, and parameterizing for multi-scale models of multi-cellular processes. The pipeline is modular and integrates the modeling and simulation tool Morpheus and the statistical inference tool pyABC. The easy integration of high-performance infrastructure allows to scale to computationally expensive problems. The introduction of a novel standard for the formulation of parameter inference problems for multi-scale models additionally ensures reproducibility and reusability. By applying the pipeline to multiple biological problems, we demonstrate its broad applicability, which will benefit in particular image-based systems biology.

AVAILABILITY: FitMultiCell is available open-source at

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.


Original languageEnglish
Article numberbtad674
Pages (from-to)1-10
Number of pages10
Issue number11
Publication statusPublished - 8 Nov 2023

External IDs

ORCID /0000-0003-3649-2433/work/147672048
ORCID /0000-0003-0137-5106/work/147674385
Scopus 85178605830



  • Reproducibility of Results, Models, Biological, Computer Simulation, Bayes Theorem, Workflow, Systems Biology