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DOI / URL link
Title (Primary) Inferring interactions in complex microbial communities from nucleotide sequence data and environmental parameters
Author 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, T.; Buscot, F.; Overmann, J.;
Journal PLOS ONE
Year 2017
Department BOOEK; iDiv;
Volume 12
Issue 3
Language englisch;
POF III (all) T23;
UFZ wide themes RU1
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.
ID 18581
Persistent UFZ Identifier https://www.ufz.de/index.php?en=20939&ufzPublicationIdentifier=18581
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, T., Buscot, F., Overmann, J. (2017):
Inferring interactions in complex microbial communities from nucleotide sequence data and environmental parameters
PLOS One 12 (3), e0173765