In:
mSystems, American Society for Microbiology, Vol. 8, No. 3 ( 2023-06-29)
Abstract:
The increase in data availability of bacterial communities highlights the need for conceptual frameworks to advance our understanding of these complex and diverse communities alongside the production of such data. To understand the dynamics of these tremendously diverse communities, we need tools to identify overarching strategies and describe their role and function in the ecosystem in a comprehensive way. Here, we show that a manifold learning approach can coarse grain bacterial communities in terms of their metabolic strategies and that we can thereby quantitatively organize genomic information in terms of potentially occupied niches over time. This approach, therefore, advances our understanding of how fluctuations in bacterial abundances and species composition can relate to ecosystem functions and it can facilitate the analysis, monitoring, and future predictions of the development of microbial communities.
Type of Medium:
Online Resource
ISSN:
2379-5077
DOI:
10.1128/msystems.00028-23
Language:
English
Publisher:
American Society for Microbiology
Publication Date:
2023
detail.hit.zdb_id:
2844333-0
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