Utilize este identificador para referenciar este registo: https://hdl.handle.net/1822/84436

TítuloEcological modelling approaches for predicting emergent properties in microbial communities
Autor(es)Berg, Naomi Iris van den
Machado, Daniel
Santos, Sophia Torres
Rocha, I.
Chacón, Jeremy
Harcombe, William
Mitri, Sara
Patil, Kiran R.
Palavras-chaveComputational biology and bioinformatics
Ecology
Microbiology
Data16-Mai-2022
EditoraNature Research
RevistaNature Ecology & Evolution
CitaçãoBerg, Naomi Iris van den; Machado, Daniel; Santos, Sophia T.; Rocha, Isabel; Chacón, Jeremy; Harcombe, William; Mitri, Sara; Patil, Kiran R., Ecological modelling approaches for predicting emergent properties in microbial communities. Nature Ecology & Evolution, 2022
Resumo(s)Recent studies have brought forward the critical role of emergent properties in shaping microbial communities and the ecosystems of which they are a part. Emergent properties---patterns or functions that cannot be deduced linearly from the properties of the constituent parts---underlie important ecological characteristics such as resilience, niche expansion and spatial self-organization. While it is clear that emergent properties are a consequence of interactions within the community, their non-linear nature makes mathematical modelling imperative for establishing the quantitative link between community structure and function. As the need for conservation and rational modulation of microbial ecosystems is increasingly apparent, so is the consideration of the benefits and limitations of the approaches to model emergent properties. Here we review ecosystem modelling approaches from the viewpoint of emergent properties. We consider the scope, advantages and limitations of Lotka--Volterra, consumer--resource, trait-based, individual-based and genome-scale metabolic models. Future efforts in this research area would benefit from capitalizing on the complementarity between these approaches towards enabling rational modulation of complex microbial ecosystems.
TipoArtigo
URIhttps://hdl.handle.net/1822/84436
DOI10.1038/s41559-022-01746-7
ISSN2397-334X
Versão da editorahttps://www.nature.com/articles/s41559-022-01746-7
Arbitragem científicayes
AcessoAcesso aberto
Aparece nas coleções:CEB - Publicações em Revistas/Séries Internacionais / Publications in International Journals/Series

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