In:
PLOS Computational Biology, Public Library of Science (PLoS), Vol. 18, No. 1 ( 2022-1-24), p. e1009777-
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.
Type of Medium:
Online Resource
ISSN:
1553-7358
DOI:
10.1371/journal.pcbi.1009777
DOI:
10.1371/journal.pcbi.1009777.g001
DOI:
10.1371/journal.pcbi.1009777.g002
DOI:
10.1371/journal.pcbi.1009777.g003
DOI:
10.1371/journal.pcbi.1009777.g004
DOI:
10.1371/journal.pcbi.1009777.g005
DOI:
10.1371/journal.pcbi.1009777.g006
DOI:
10.1371/journal.pcbi.1009777.t001
DOI:
10.1371/journal.pcbi.1009777.s001
DOI:
10.1371/journal.pcbi.1009777.s002
DOI:
10.1371/journal.pcbi.1009777.s003
DOI:
10.1371/journal.pcbi.1009777.s004
DOI:
10.1371/journal.pcbi.1009777.s005
Language:
English
Publisher:
Public Library of Science (PLoS)
Publication Date:
2022
detail.hit.zdb_id:
2193340-6
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