ArticlePLoS computational biology2022
McComedy: A user-friendly tool for next-generation individual-based modeling of microbial consumer-resource systems.
Article in PLoS computational biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed.
- Disentangling the feedback loops driving spatial patterning in microbial communities.NPJ biofilms and microbiomes · 2025Review
- Is it selfish to be filamentous in biofilms? Individual-based modeling links microbial growth strategies with morphology using the new and modular iDynoMiCS 2.0.PLoS computational biology · 2024Article
- A new era of synthetic biology-microbial community design.Synthetic biology (Oxford, England) · 2024Review
- Calibrating spatiotemporal models of microbial communities to microscopy data: A review.PLoS computational biology · 2022Review
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Authors and funding
5 authors.
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Abstract
Individual-based modeling is widely applied to investigate the ecological mechanisms driving microbial community dynamics. In such models, the population or community dynamics emerge from the behavior and interplay of individual entities, which are simulated according to a predefined set of rules. If the rules that govern the behavior of individuals are based on generic and mechanistically sound principles, the models are referred to as next-generation individual-based models. These models perform particularly well in recapitulating actual ecological dynamics. However, implementation of such models is time-consuming and requires proficiency in programming or in using specific software, which likely hinders a broader application of this powerful method. Here we present McComedy, a modeling tool designed to facilitate the development of next-generation individual-based models of microbial consumer-resource systems. This tool allows flexibly combining pre-implemented building blocks that represent physical and biological processes. The ability of McComedy to capture the essential dynamics of microbial consumer-resource systems is demonstrated by reproducing and furthermore adding to the results of two distinct studies from the literature. With this article, we provide a versatile tool for developing next-generation individual-based models that can foster understanding of microbial ecology in both research and education.
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Registered trials
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