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Inferring interactions in complex microbial communities from nucleotide sequence data and environmental parameters.
- Source :
- PLoS ONE, Vol 12, Iss 3, p e0173765 (2017)
- Publication Year :
- 2017
- Publisher :
- Public Library of Science (PLoS), 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
- Language :
- English
- ISSN :
- 19326203
- Volume :
- 12
- Issue :
- 3
- Database :
- Directory of Open Access Journals
- Journal :
- PLoS ONE
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.85c80e3adb2f4409aebd0ece9cdd7540
- Document Type :
- article
- Full Text :
- https://doi.org/10.1371/journal.pone.0173765