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

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 inter...

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Autores principales: 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, Francois, Overmann, Jörg
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2017
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5348048/
https://www.ncbi.nlm.nih.gov/pubmed/28288199
http://dx.doi.org/10.1371/journal.pone.0173765
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author 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, Francois
Overmann, Jörg
author_facet 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, Francois
Overmann, Jörg
author_sort Shang, Yu
collection PubMed
description 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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spelling pubmed-53480482017-03-30 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, Francois Overmann, Jörg PLoS One Research Article 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. Public Library of Science 2017-03-13 /pmc/articles/PMC5348048/ /pubmed/28288199 http://dx.doi.org/10.1371/journal.pone.0173765 Text en © 2017 Shang et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
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, Francois
Overmann, Jörg
Inferring interactions in complex microbial communities from nucleotide sequence data and environmental parameters
title Inferring interactions in complex microbial communities from nucleotide sequence data and environmental parameters
title_full Inferring interactions in complex microbial communities from nucleotide sequence data and environmental parameters
title_fullStr Inferring interactions in complex microbial communities from nucleotide sequence data and environmental parameters
title_full_unstemmed Inferring interactions in complex microbial communities from nucleotide sequence data and environmental parameters
title_short Inferring interactions in complex microbial communities from nucleotide sequence data and environmental parameters
title_sort inferring interactions in complex microbial communities from nucleotide sequence data and environmental parameters
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5348048/
https://www.ncbi.nlm.nih.gov/pubmed/28288199
http://dx.doi.org/10.1371/journal.pone.0173765
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