Output details
11 - Computer Science and Informatics
University of Oxford
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Article title
Predicting bacterial community assemblages using an artificial neural network approach
Type
D - Journal article
Title of journal
Nature Methods
Article number
-
Volume number
9
Issue number
6
First page of article
621
ISSN of journal
1548-7091
Year of publication
2012
URL
-
Number of additional authors
2
Additional information
<28>
This paper introduces an algorithm for predicting microbial community structure from environmental data. Based on the analysis of our world-unique, six-year metagenomics “L4 time series”, this advance made possible the prediction of microbial community structure in time and space across the English Channel. Microbes are the “invisible majority” of life on earth and deliver many essential ecosystem services, including 50% of the oxygen we breathe. This method is now being used to predict the impact of microbial communities on global ecosystem services, including CO2 metabolism, as an essential part of understanding the impacts of climate change.
Interdisciplinary
-
Cross-referral requested
-
Research group
None
Citation count
14
Proposed double-weighted
No
Double-weighted statement
-
Reserve for a double-weighted output
No
Non-English
No
English abstract
-
