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Inferring interactions in complex microbial communities from nucleotide sequence data and environmental parameters


Shang, Yu; Sikorski, Johannes; Bonkowski, Michael; Fiore-Donno, Anna-Maria; Kandeler, Ellen; Marhan, Sven; Boeddinghaus, Runa S; Solly, Emily F; Schrumpf, Marion; Schöning, Ingo; Wubet, Tesfaye; Buscot, François; Overmann, Jörg (2017). Inferring interactions in complex microbial communities from nucleotide sequence data and environmental parameters. PLoS ONE, 12(3):e0173765.

Abstract

Interactions occur between two or more organisms affecting each other. Interactions are decisive for the ecology of the organisms. Without direct experimental evidence the analysis of interactions is difficult. Correlation analyses that are based on co-occurrences are often used to approximate interaction. Here, we present a new mathematical model to estimate the interaction strengths between taxa, based on changes in their relative abundances across environmental gradients.

Abstract

Interactions occur between two or more organisms affecting each other. Interactions are decisive for the ecology of the organisms. Without direct experimental evidence the analysis of interactions is difficult. Correlation analyses that are based on co-occurrences are often used to approximate interaction. Here, we present a new mathematical model to estimate the interaction strengths between taxa, based on changes in their relative abundances across environmental gradients.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Geography
Dewey Decimal Classification:910 Geography & travel
Language:English
Date:2017
Deposited On:26 Feb 2018 16:33
Last Modified:30 Jun 2018 05:46
Publisher:Public Library of Science (PLoS)
ISSN:1932-6203
OA Status:Gold
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.1371/journal.pone.0173765

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