The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.
Supervised classification of human microbiota
Abstract
Recent advances in DNA sequencing technology have allowed the collection of high-dimensional data from human-associated microbial communities on an unprecedented scale. A major goal of these studies is the identification of important groups of microorganisms that vary according to physiological or disease states in the host, but the incidence of rare taxa and the large numbers of taxa observed make that goal difficult to obtain using traditional approaches. Fortunately, similar problems have been addressed by the machine learning community in other fields of study such as microarray analysis and text classification. In this review, we demonstrate that several existing supervised classifiers can be applied effectively to microbiota classification, both for selecting subsets of taxa that are highly discriminative of the type of community, and for building models that can accurately classify unlabeled data. To encourage the development of new approaches to supervised classification of microbiota, we discuss several structures inherent in microbial community data that may be available for exploitation in novel approaches, and we include as supplemental information several benchmark classification tasks for use by the community.
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Cites
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Self-citationRandom forests for classification in ecology
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Self-citationThe Effect of Diet on the Human Gut Microbiome: A Metagenomic Analysis in Humanized Gnotobiotic Mice
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Cited by
Human gut microbiome viewed across age and geography
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Self-citationGut Microbiota from Twins Discordant for Obesity Modulate Metabolism in Mice
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Gut metagenome in European women with normal, impaired and diabetic glucose control
Karlsson, F. H., Tremaroli, V., Nookaew, I., Bergström, G., Behre, C. J., Fagerberg, B., Nielsen, J., & Bäckhed, F. (2013) · Nature · doi:10.1038/nature12198 · Cited by 3,115
Metadata
- Authors
- Knights, D., Costello, E. K., & Knight, R.
- Venue
- FEMS Microbiology Reviews
- Publisher
- Oxford University Press (OUP)
- Published
- 2011-03
- Volume
- 35
- Issue
- 2
- Pages
- 343-359
- ISSN
- 0168-6445 (ISSN-L)
- 1574-6976
- OpenAlex
- W1811186957
- Cited by
- 482
- References
- 11
- FWCI
- 5.79
- Type
- journal article
- Language
- en
- Open access
- closed
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