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Cited by 2,118

The DOI matches its Crossref record; 71 of the 71 references it cites were found in a registry or an index.

PCR inhibitors - occurrence, properties and removal

Schrader, C., Schielke, A., Ellerbroek, L., Johne, R.·2012·Journal of Applied Microbiology

Abstract

The polymerase chain reaction (PCR) is increasingly used as the standard method for detection and characterization of microorganisms and genetic markers in a variety of sample types. However, the method is prone to inhibiting substances, which may be present in the analysed sample and which may affect the sensitivity of the assay or even lead to false-negative results. The PCR inhibitors represent a diverse group of substances with different properties and mechanisms of action. Some of them are predominantly found in specific types of samples thus necessitating matrix-specific protocols for preparation of nucleic acids before PCR. A variety of protocols have been developed to remove the PCR inhibitors. This review focuses on the general properties of PCR inhibitors and their occurrence in specific matrices. Strategies for their removal from the sample and for quality control by assessing their influence on the individual PCR test are presented and discussed.

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Crossref · 10.1111/j.1365-2672.2012.05384.x

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Metadata

Authors
Schrader, C., Schielke, A., Ellerbroek, L., & Johne, R.
Venue
Journal of Applied Microbiology
Published
2012-07-24
Volume
113
Issue
5
Pages
1014-1026
ISSN
1364-5072 (ISSN-L)
OpenAlex
W1973207608
Cited by
2,118
References
71
FWCI
14.29
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: PCR inhibitors - occurrence, properties and removal. https://app.cochat.ai/papers/10.1111/j.1365-2672.2012.05384.x
The paper
Schrader, C., Schielke, A., Ellerbroek, L., & Johne, R. (2012). PCR inhibitors - occurrence, properties and removal. Journal of Applied Microbiology. https://doi.org/10.1111/j.1365-2672.2012.05384.x

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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.