Predicting microbial distributions in space and time. (Q51560590)

7 April 2018

title

Predicting microbial distributions in space and time. (English)

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7 April 2018

Noah Fierer

1

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author name string

Joshua Ladau

series ordinal

2

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7 April 2018

publication date

30 May 2012

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7 April 2018

published in

Nature Methods

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7 April 2018

volume

9

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issue

6

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page(s)

549-551

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7 April 2018

Predicting bacterial community assemblages using an artificial neural network approach

cites work

1 reference

https://api.crossref.org/works/10.1038%2FNMETH.2041

A molecular view of microbial diversity and the biosphere

21 January 2018

1 reference

https://api.crossref.org/works/10.1038%2FNMETH.2041

Emergent biogeography of microbial communities in a model ocean

21 January 2018

1 reference

https://api.crossref.org/works/10.1038%2FNMETH.2041

Pyrosequencing-based assessment of soil pH as a predictor of soil bacterial community structure at the continental scale

21 January 2018

1 reference

https://api.crossref.org/works/10.1038%2FNMETH.2041

Global patterns of bacterial beta-diversity in seafloor and seawater ecosystems

21 January 2018

1 reference

https://api.crossref.org/works/10.1038%2FNMETH.2041

Composition, variability, and temporal stability of the intestinal microbiota of the elderly

21 January 2018

1 reference

https://api.crossref.org/works/10.1038%2FNMETH.2041

Ultra-high-throughput microbial community analysis on the Illumina HiSeq and MiSeq platforms

21 January 2018

1 reference

PubMed

https://pubmed.ncbi.nlm.nih.gov/22669651

inferred from PubMed ID database lookup

12 December 2020

based on heuristic

Identifiers

DOI

10.1038/NMETH.2041

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7 April 2018

1 reference

7 April 2018