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

Authors :
Shang, Y.
Sikorski, J.
Bonkowski, M.
Fiore-Donno, A.-M.
Kandeler, E.
Marhan, S.
Boeddinghaus, R.S.
Solly, E.F.
Schrumpf, M.
Schöning, I.
Wubet, Tesfaye
Buscot, Francois
Overmann, J.
Shang, Y.
Sikorski, J.
Bonkowski, M.
Fiore-Donno, A.-M.
Kandeler, E.
Marhan, S.
Boeddinghaus, R.S.
Solly, E.F.
Schrumpf, M.
Schöning, I.
Wubet, Tesfaye
Buscot, Francois
Overmann, J.
Source :
ISSN: 1932-6203
Publication Year :
2017

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.

Details

Database :
OAIster
Journal :
ISSN: 1932-6203
Notes :
ISSN: 1932-6203, PLOS ONE 12 (3);; e0173765, English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1406008535
Document Type :
Electronic Resource