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Cited by 351

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

Detection and Identification of Microorganisms by Gene Amplification and Sequencing

Reller, L. B., Weinstein, M. P., Petti, C. A.·2007·Clinical Infectious Diseases

Abstract

Gene amplification and sequencing have led to the discovery of new pathogens as agents of disease and have enabled us to better classify microorganisms from culture. Sequence-based identification of bacteria and fungi using culture is more objective and accurate than conventional methods, especially for classifying unusual microorganisms that are emerging pathogens in immunocompromised hosts. Although a powerful tool, the interpretation of sequence-based classification can be challenging as microbial taxonomy grows more complex, without known clinical correlatives. Additionally, broad-range gene polymerase chain reaction and sequencing have emerged as alternative, culture-independent methods for detecting pathogens from clinical material. The promise of this technique has remained strong, limited mainly by contamination and inadequate sensitivity issues. This review explains sequence-based microbial classification, with emphasis on relating the complex world of microbial taxonomy to a clinical context. Additionally, this review discusses a rational approach to broad-range bacterial polymerase chain reaction and gene sequencing when applied directly to clinical samples.

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Crossref · 10.1086/512818

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Metadata

Authors
Reller, L. B., Weinstein, M. P., & Petti, C. A.
Venue
Clinical Infectious Diseases
Published
2007-04-15
Volume
44
Issue
8
Pages
1108-1114
ISSN
  • 1058-4838 (ISSN-L)
  • 1537-6591
OpenAlex
W2111691512
Cited by
351
References
3
FWCI
8.01
Type
journal article
Language
en
Open access
closed

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

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.