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Cited by 710

The DOI matches its Crossref record; 109 of the 109 references it cites were found in a registry or an index.

Multidrug evolutionary strategies to reverse antibiotic resistance

Open access
Baym, Michael, Stone, Laura K., Kishony, Roy·2016·Science
DOI 10.1126/science.aad3292
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Abstract

Evolving antibiotic rescue stratagems: Antibiotic resistance threatens to put modern medicine into reverse. But we are not at the end of our options for currently available drugs. Baym et al. review what can be done by using combinations of antibiotics to circumvent bacteria's evolutionary strategies. For instance, resistance to one drug may cause sensitivity to another, the effectiveness of two drugs can be synergized by a resistance mutation, and some negative drug interactions may even be beneficial in selecting against resistance. Although not simple to assess, drug combinations still have something to offer for the development of sorely needed anti-infectives. Science , this issue p. 10.1126/science.aad3292

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Crossref · 10.1126/science.aad3292

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Metadata

Authors
Baym, M., Stone, L. K., & Kishony, R.
Venue
Science
Publisher
American Association for the Advancement of Science (AAAS)
Published
2016-01
Volume
351
Issue
6268
Pages
aad3292-aad3292
ISSN
  • 0036-8075 (ISSN-L)
  • 1095-9203
DOI
10.1126/science.aad3292
OpenAlex
W2222642144
Cited by
710
References
109
FWCI
16.90
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Multidrug evolutionary strategies to reverse antibiotic resistance. https://app.cochat.ai/papers/10.1126/science.aad3292
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Baym, M., Stone, L. K., & Kishony, R. (2016). Multidrug evolutionary strategies to reverse antibiotic resistance. Science. https://doi.org/10.1126/science.aad3292

Data sources

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.