Daniel Kaul

5.4k citations
89 papers · 2.5k · h-index 29

Impact in

Papers in

    • Cytomegalovirus and herpesvirus research 19
    • Pneumocystis jirovecii pneumonia detection and treatment 9
    • Mycobacterium research and diagnosis 8
    • Herpesvirus Infections and Treatments 6
    • Clostridium difficile and Clostridium perfringens research 5

Daniel Kaul

86 papers receiving 2.5k citations

Peers

Daniel Kaul
Comparison fields: 5 of 121
  • Transplantation 167
  • Infectious Diseases 683
  • Epidemiology 1.2k
  • Oncology 466
  • Parasitology 115
Replace Diana F. Florescu with:
Diana F. Florescu United States
Oriol Manuel Switzerland
Michele I. Morris United States
N. Singh United States
Barbara C. Gärtner Germany
Elisa Cordero Spain
Lara Danziger‐Isakov United States
Carlos Lumbreras Spain
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Citations per field
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Citations per year

Countries citing papers authored by Daniel Kaul

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Kaul

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Daniel Kaul, 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 Daniel Kaul Line = papers co-authored together Daniel Kaul links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 89 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2012245
2 2012215
3 2013200
4 2011133
5 2015119
6 202088
7 202186
8 200784
9 201758
10 199954
11 201152
12 201149
13 201649
14 202148
15 200047
16 199945
17 200943
18 200938
19 200836
20 200836

About Daniel Kaul

Daniel Kaul is a scholar working on Epidemiology, Infectious Diseases, Oncology, Surgery and Public Health, Environmental and Occupational Health, having authored 89 papers that have together received 2.5k indexed citations. Recurring topics across this work include Cytomegalovirus and herpesvirus research (19 papers), Pneumocystis jirovecii pneumonia detection and treatment (9 papers), Mycobacterium research and diagnosis (8 papers), Polyomavirus and related diseases (7 papers), Herpesvirus Infections and Treatments (6 papers), Infectious Diseases and Tuberculosis (6 papers), Clostridium difficile and Clostridium perfringens research (5 papers) and Hematological disorders and diagnostics (5 papers). The work is most often cited by research in Transplantation (167 citations), Infectious Diseases (683 citations), Epidemiology (1.2k citations), Oncology (466 citations) and Parasitology (115 citations). Daniel Kaul has collaborated with scholars based in United States, Canada and Switzerland. Frequent co-authors include Sanjay Saint, Powel Kazanjian, Cameron R. Wolfe, Michael G. Ison, Preeti Malani, Andrew R. Martin, Robert Krell, Shijie Cai, Michael J. Englesbe and Christopher J. Sonnenday. Their work appears in journals such as New England Journal of Medicine, American Journal of Transplantation, Clinical Infectious Diseases, Transplantation and Open Forum Infectious Diseases.

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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