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Cited by 1,129

The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.

Metagenomics: Genomic Analysis of Microbial Communities

Riesenfeld, Christian S., Schloss, Patrick D., Handelsman, Jo·2004·Annual Review of Genetics

Abstract

▪ Abstract Uncultured microorganisms comprise the majority of the planet's biological diversity. Microorganisms represent two of the three domains of life and contain vast diversity that is the product of an estimated 3.8 billion years of evolution. In many environments, as many as 99% of the microorganisms cannot be cultured by standard techniques, and the uncultured fraction includes diverse organisms that are only distantly related to the cultured ones. Therefore, culture-independent methods are essential to understand the genetic diversity, population structure, and ecological roles of the majority of microorganisms. Metagenomics, or the culture-independent genomic analysis of an assemblage of microorganisms, has potential to answer fundamental questions in microbial ecology. This review describes progress toward understanding the biology of uncultured Bacteria, Archaea, and viruses through metagenomic analyses.

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Crossref · 10.1146/annurev.genet.38.072902.091216

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Metadata

Authors
Riesenfeld, C. S., Schloss, P. D., & Handelsman, J.
Venue
Annual Review of Genetics
Published
2004-12-01
Volume
38
Issue
1
Pages
525-552
ISSN
  • 0066-4197 (ISSN-L)
  • 1545-2948
OpenAlex
W2115026474
Cited by
1,129
References
6
FWCI
1.69
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Metagenomics: Genomic Analysis of Microbial Communities. https://app.cochat.ai/papers/10.1146/annurev.genet.38.072902.091216
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Riesenfeld, C. S., Schloss, P. D., & Handelsman, J. (2004). Metagenomics: Genomic Analysis of Microbial Communities. Annual Review of Genetics. https://doi.org/10.1146/annurev.genet.38.072902.091216

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.