Phelim Bradley

3.5k total citations · 1 hit paper
9 papers, 984 citations indexed

About

Phelim Bradley is a scholar working on Infectious Diseases, Epidemiology and Molecular Biology. According to data from OpenAlex, Phelim Bradley has authored 9 papers receiving a total of 984 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Infectious Diseases, 4 papers in Epidemiology and 3 papers in Molecular Biology. Recurrent topics in Phelim Bradley's work include Bacterial Identification and Susceptibility Testing (3 papers), Tuberculosis Research and Epidemiology (3 papers) and Mycobacterium research and diagnosis (3 papers). Phelim Bradley is often cited by papers focused on Bacterial Identification and Susceptibility Testing (3 papers), Tuberculosis Research and Epidemiology (3 papers) and Mycobacterium research and diagnosis (3 papers). Phelim Bradley collaborates with scholars based in United Kingdom, France and United States. Phelim Bradley's co-authors include Zamin Iqbal, Adrien Rieux, Xavier Didelot, Hui Wang, Qi Wang, Thamarai Schneiders, Lucy van Dorp, Liam P. Shaw, Qing Zhang and François Balloux and has published in prestigious journals such as Nature Communications, Nature Biotechnology and Journal of Clinical Microbiology.

In The Last Decade

Phelim Bradley

9 papers receiving 972 citations

Hit Papers

The global distribution and spread of the mobilized colis... 2018 2026 2020 2023 2018 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Phelim Bradley United Kingdom 8 483 321 314 282 216 9 984
Sara Christianson Canada 14 500 1.0× 292 0.9× 249 0.8× 281 1.0× 135 0.6× 21 936
Danesh Moradigaravand United Kingdom 18 399 0.8× 339 1.1× 237 0.8× 372 1.3× 101 0.5× 33 935
Masahiro Shimojima Japan 19 605 1.3× 186 0.6× 286 0.9× 270 1.0× 121 0.6× 37 936
Guilène Barnaud France 14 584 1.2× 240 0.7× 244 0.8× 298 1.1× 165 0.8× 23 1.1k
José María González‐Alba Spain 10 672 1.4× 169 0.5× 189 0.6× 170 0.6× 276 1.3× 24 948
Mari Matsui Japan 20 612 1.3× 124 0.4× 181 0.6× 253 0.9× 149 0.7× 53 910
Apostolos Liakopoulos Netherlands 20 672 1.4× 246 0.8× 163 0.5× 329 1.2× 197 0.9× 40 1.1k
Mohammad M. Feizabadi Iran 20 396 0.8× 508 1.6× 388 1.2× 370 1.3× 121 0.6× 40 1.1k
E. Espaze France 15 477 1.0× 170 0.5× 149 0.5× 227 0.8× 129 0.6× 30 943
Steven H. Marshall United States 20 994 2.1× 293 0.9× 288 0.9× 333 1.2× 178 0.8× 60 1.3k

Countries citing papers authored by Phelim Bradley

Since Specialization
Citations

This map shows the geographic impact of Phelim Bradley'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 Phelim Bradley with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Phelim Bradley more than expected).

Fields of papers citing papers by Phelim Bradley

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Phelim Bradley. 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 Phelim Bradley. The network helps show where Phelim Bradley may publish in the future.

Co-authorship network of co-authors of Phelim Bradley

This figure shows the co-authorship network connecting the top 25 collaborators of Phelim Bradley. A scholar is included among the top collaborators of Phelim Bradley 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 Phelim Bradley. Phelim Bradley is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

9 of 9 papers shown
1.
Bradley, Phelim, Henk C. den Bakker, Eduardo P. C. Rocha, Gil McVean, & Zamin Iqbal. (2019). Ultrafast search of all deposited bacterial and viral genomic data. Nature Biotechnology. 37(2). 152–159. 77 indexed citations
2.
Lipworth, Samuel, Rana Jajou, Albert J. de Neeling, et al.. (2019). SNP-IT Tool for Identifying Subspecies and Associated Lineages of Mycobacterium tuberculosis Complex. Emerging infectious diseases. 25(3). 482–488. 45 indexed citations
3.
Anson, Luke, Kevin Chau, Nicholas D. Sanderson, et al.. (2018). DNA extraction from primary liquid blood cultures for bloodstream infection diagnosis using whole genome sequencing. Journal of Medical Microbiology. 67(3). 347–357. 23 indexed citations
4.
Wang, Ruobing, Lucy van Dorp, Liam P. Shaw, et al.. (2018). The global distribution and spread of the mobilized colistin resistance gene mcr-1. Nature Communications. 9(1). 1179–1179. 476 indexed citations breakdown →
5.
Mason, Amy M., Dona Foster, Phelim Bradley, et al.. (2018). Accuracy of Different Bioinformatics Methods in Detecting Antibiotic Resistance and Virulence Factors from Staphylococcus aureus Whole-Genome Sequences. Journal of Clinical Microbiology. 56(9). 54 indexed citations
6.
Votintseva, Antonina A., Phelim Bradley, Louise Pankhurst, et al.. (2017). Same-Day Diagnostic and Surveillance Data for Tuberculosis via Whole-Genome Sequencing of Direct Respiratory Samples. Journal of Clinical Microbiology. 55(5). 1285–1298. 231 indexed citations
8.
Jay, Michele T., et al.. (1997). Clostridium perfringens outbreak at a juvenile detention facility linked to a Thanksgiving holiday meal.. PubMed. 166(6). 417–9. 10 indexed citations
9.
Bruce, David & Phelim Bradley. (1977). Metronidazole discs on anaerobic neomycin blood agar plates. An aid to diagnosis of anaerobic infections.. PubMed. 34(3). 273–5. 3 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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