Jeffrey E. Topal

2.6k citations
80 papers · 1.9k · h-index 19

Impact in

Papers in

    • Antimicrobial Resistance in Staphylococcus 11
    • Antifungal resistance and susceptibility 9
    • COVID-19 Clinical Research Studies 5
    • Clostridium difficile and Clostridium perfringens research 5

Jeffrey E. Topal

74 papers receiving 1.8k citations

Peers

Jeffrey E. Topal
Comparison fields: 5 of 114
  • Applied Microbiology and Biotechnology 86
  • Infectious Diseases 637
  • Parasitology 148
  • Epidemiology 660
  • Hepatology 129
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C. Michelet France
Brian S. Schwartz United States
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Citations per field
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Citations per year

Countries citing papers authored by Jeffrey E. Topal

Since Specialization
Citations

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

Fields of papers citing papers by Jeffrey E. Topal

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jeffrey E. Topal. 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 Jeffrey E. Topal. The network helps show where Jeffrey E. Topal may publish in the future.

Co-authors

The 25 scholars most cited alongside Jeffrey E. Topal, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Jeffrey E. Topal Line = papers co-authored together Jeffrey E. Topal links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 80 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2016325
2 2003200
3 2020172
4 2012137
5 2005114
6 2010107
7 200585
8 202070
9 202051
10 200150
11 200938
12 200435
13 202435
14 202033
15 200128
16 201526
17 201220
18 201320
19 201420
20 200319

About Jeffrey E. Topal

Jeffrey E. Topal is a scholar working on Infectious Diseases, Epidemiology, Applied Microbiology and Biotechnology, Pharmacology and Clinical Biochemistry, having authored 80 papers that have together received 1.9k indexed citations. Recurring topics across this work include Antimicrobial Resistance in Staphylococcus (11 papers), Antifungal resistance and susceptibility (9 papers), Neutropenia and Cancer Infections (7 papers), Antibiotics Pharmacokinetics and Efficacy (7 papers), Antibiotic Use and Resistance (6 papers), COVID-19 Clinical Research Studies (5 papers), Bacterial Identification and Susceptibility Testing (5 papers) and Clostridium difficile and Clostridium perfringens research (5 papers). The work is most often cited by research in Applied Microbiology and Biotechnology (86 citations), Infectious Diseases (637 citations), Parasitology (148 citations), Epidemiology (660 citations) and Hepatology (129 citations). Jeffrey E. Topal has collaborated with scholars based in United States, Italy and India. Frequent co-authors include Richard A. Martinello, Laura Jones, Dayna S. McManus, Guadalupe García–Tsao, Puneeta Tandon, Thomas J. Balcezak, Sunish Shah, Peter Herbert, David R. Peaper and Matteo Bassetti. Their work appears in journals such as Open Forum Infectious Diseases, Infection Control and Hospital Epidemiology, Journal of Antimicrobial Chemotherapy, Journal of Clinical Microbiology and Journal of the National Comprehensive Cancer Network.

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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