Aimee K. Murray

1.7k total citations · 1 hit paper
29 papers, 1.1k citations indexed

About

Aimee K. Murray is a scholar working on Pollution, Molecular Medicine and Applied Microbiology and Biotechnology. According to data from OpenAlex, Aimee K. Murray has authored 29 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Pollution, 14 papers in Molecular Medicine and 7 papers in Applied Microbiology and Biotechnology. Recurrent topics in Aimee K. Murray's work include Pharmaceutical and Antibiotic Environmental Impacts (24 papers), Antibiotic Resistance in Bacteria (14 papers) and Antibiotic Use and Resistance (7 papers). Aimee K. Murray is often cited by papers focused on Pharmaceutical and Antibiotic Environmental Impacts (24 papers), Antibiotic Resistance in Bacteria (14 papers) and Antibiotic Use and Resistance (7 papers). Aimee K. Murray collaborates with scholars based in United Kingdom, Australia and Hong Kong. Aimee K. Murray's co-authors include William H. Gaze, Jason Snape, Lihong Zhang, Isobel C. Stanton, Peter M. Hawkey, Anne Frances Clare Leonard, Andrew Balfour, Obioha C. Ukoumunne, Ruth Garside and Angus Buckling and has published in prestigious journals such as SHILAP Revista de lepidopterología, The Science of The Total Environment and Water Research.

In The Last Decade

Aimee K. Murray

27 papers receiving 1.1k citations

Hit Papers

Co-selection for antibiotic resistance by environmental c... 2024 2026 2025 2024 25 50 75

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Aimee K. Murray United Kingdom 17 698 421 218 216 159 29 1.1k
Carolin Rutgersson Sweden 9 853 1.2× 455 1.1× 220 1.0× 112 0.5× 89 0.6× 12 1.2k
P.M.C. Huijbers Netherlands 9 601 0.9× 589 1.4× 132 0.6× 160 0.7× 98 0.6× 10 924
Esther Sib Germany 18 513 0.7× 443 1.1× 191 0.9× 95 0.4× 201 1.3× 29 992
Gernot Zarfel Austria 23 539 0.8× 893 2.1× 392 1.8× 171 0.8× 240 1.5× 72 1.7k
Erik Gullberg Sweden 6 1.0k 1.5× 869 2.1× 410 1.9× 228 1.1× 122 0.8× 8 1.8k
Jaqueline Rocha Portugal 15 678 1.0× 406 1.0× 266 1.2× 86 0.4× 99 0.6× 29 1.1k
Ryszard Koczura Poland 16 575 0.8× 573 1.4× 222 1.0× 76 0.4× 85 0.5× 29 1.1k
Joanna Mokracka Poland 16 583 0.8× 557 1.3× 194 0.9× 78 0.4× 74 0.5× 34 1.1k
Reshma Silvester India 12 400 0.6× 342 0.8× 253 1.2× 156 0.7× 78 0.5× 57 1.2k
Anders Janzon Sweden 13 496 0.7× 335 0.8× 422 1.9× 81 0.4× 176 1.1× 14 1.3k

Countries citing papers authored by Aimee K. Murray

Since Specialization
Citations

This map shows the geographic impact of Aimee K. Murray's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Aimee K. Murray with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Aimee K. Murray more than expected).

Fields of papers citing papers by Aimee K. Murray

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Aimee K. Murray. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Aimee K. Murray. The network helps show where Aimee K. Murray may publish in the future.

Co-authorship network of co-authors of Aimee K. Murray

This figure shows the co-authorship network connecting the top 25 collaborators of Aimee K. Murray. A scholar is included among the top collaborators of Aimee K. Murray based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Aimee K. Murray. Aimee K. Murray is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Snape, Jason, et al.. (2025). Common non-antibiotic drugs enhance selection for antimicrobial resistance in mixture with ciprofloxacin. ISME Communications. 5(1). ycaf169–ycaf169.
2.
Zhang, Lihong, Edward J. Feil, Barbara Kasprzyk‐Hordern, et al.. (2025). Antimicrobial effects, and selection for AMR by non-antibiotic drugs in a wastewater bacterial community. Environment International. 199. 109490–109490. 1 indexed citations
3.
Buckling, Angus, et al.. (2025). Rising Tide to Silent Tsunami: Unveiling the role of plastics in driving antimicrobial resistance. Journal of Hazardous Materials. 494. 138700–138700.
4.
Murray, Aimee K., Isobel C. Stanton, Wiebke Schmidt, et al.. (2024). A critical meta-analysis of predicted no effect concentrations for antimicrobial resistance selection in the environment. Water Research. 266. 122310–122310. 7 indexed citations
5.
O’Brien, Jake, et al.. (2024). A review of wastewater-based epidemiology for antimicrobial resistance surveillance. 3(1). 12 indexed citations
6.
Snape, Jason, et al.. (2024). Co-selection for antibiotic resistance by environmental contaminants. PubMed. 2(1). 9–9. 98 indexed citations breakdown →
7.
Murray, Aimee K., et al.. (2024). Antimicrobial risk assessment–Aggregating aquatic chemical and resistome emissions. Water Research. 271. 122929–122929. 3 indexed citations
8.
Murray, Aimee K., Lihong Zhang, Jason Snape, & William H. Gaze. (2023). Functional metagenomic libraries generated from anthropogenically impacted environments reveal importance of metabolic genes in biocide and antibiotic resistance. Current Research in Microbial Sciences. 4. 100184–100184. 3 indexed citations
9.
Buckling, Angus, et al.. (2023). Culturing the Plastisphere: comparing methods to isolate culturable bacteria colonising microplastics. Frontiers in Microbiology. 14. 1259287–1259287. 15 indexed citations
10.
Barnish, Maxwell S., et al.. (2023). Exploring the potential of using simulation games for engaging with sheep farmers about lameness recognition. Frontiers in Veterinary Science. 10. 1079948–1079948. 2 indexed citations
12.
Stanton, Isobel C., et al.. (2022). Predicting selection for antimicrobial resistance in UK wastewater and aquatic environments: Ciprofloxacin poses a significant risk. Environment International. 169. 107488–107488. 39 indexed citations
13.
Wang, Yue, Zhigang Yu, Pengbo Ding, et al.. (2022). Non-antibiotic pharmaceuticals promote conjugative plasmid transfer at a community-wide level. Microbiome. 10(1). 124–124. 41 indexed citations
14.
Murray, Aimee K., Isobel C. Stanton, William H. Gaze, & Jason Snape. (2021). Dawning of a new ERA: Environmental Risk Assessment of antibiotics and their potential to select for antimicrobial resistance. Water Research. 200. 117233–117233. 101 indexed citations
16.
Murray, Aimee K.. (2020). The Novel Coronavirus COVID-19 Outbreak: Global Implications for Antimicrobial Resistance. Frontiers in Microbiology. 11. 1020–1020. 92 indexed citations
17.
Murray, Aimee K., Lihong Zhang, Jason Snape, & William H. Gaze. (2019). Comparing the selective and co-selective effects of different antimicrobials in bacterial communities. International Journal of Antimicrobial Agents. 53(6). 767–773. 41 indexed citations
18.
Zhang, Lifu, Leo Calvo‐Bado, Aimee K. Murray, et al.. (2019). Novel clinically relevant antibiotic resistance genes associated with sewage sludge and industrial waste streams revealed by functional metagenomic screening. Environment International. 132. 105120–105120. 27 indexed citations
19.
Zhang, Lihong, et al.. (2018). Carbapenem resistance in bacteria isolated from soil and water environments in Algeria. Journal of Global Antimicrobial Resistance. 15. 262–267. 16 indexed citations
20.
Murray, Aimee K., Lihong Zhang, Xiaole Yin, et al.. (2018). Novel Insights into Selection for Antibiotic Resistance in Complex Microbial Communities. mBio. 9(4). 116 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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