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Cited by 414

The DOI matches its Crossref record; 22 of the 22 references it cites were found in a registry or an index.

Identification of Critical Staphylococcal Genes Using Conditional Phenotypes Generated by Antisense RNA

Ji, Yinduo, Zhang, Barbara, Van, Stephanie F., Horn, Warren, Patrick, Woodnutt, Gary, Burnham, Martin K. R., Rosenberg, Martin·2001·Science

Abstract

Comprehensive genomic analysis of the important human pathogen Staphylococcus aureus was achieved by a strategy involving antisense technology in a regulatable gene expression system. In addition to known essential genes, many genes of unknown or poorly defined biological function were identified. This methodology allowed gene function to be characterized in a comprehensive, defined set of conditionally growth-defective/lethal isogenic strains. Quantitative titration of the conditional growth effect was performed either in bacterial culture or in an animal model of infection. This genomic strategy offers an approach to the identification of staphylococcal gene products that could serve as targets for antibiotic discovery.

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Metadata

Authors
Ji, Y., Zhang, B., Van, S. F., Horn, Warren, P., Woodnutt, G., Burnham, M. K. R., & Rosenberg, M.
Venue
Science
Published
2001-09-21
Volume
293
Issue
5538
Pages
2266-2269
ISSN
  • 0036-8075 (ISSN-L)
  • 1095-9203
OpenAlex
W2040226264
Cited by
414
References
22
FWCI
18.09
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Identification of Critical Staphylococcal Genes Using Conditional Phenotypes Generated by Antisense RNA. https://app.cochat.ai/papers/10.1126/science.1063566
The paper
Ji, Y., Zhang, B., Van, S. F., Horn, Warren, P., Woodnutt, G., Burnham, M. K. R., & Rosenberg, M. (2001). Identification of Critical Staphylococcal Genes Using Conditional Phenotypes Generated by Antisense RNA. Science. https://doi.org/10.1126/science.1063566

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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.