William A. Agger
- Parasitology top 1%
- Vector-borne infectious diseases 15
- Infectious Diseases top 1%
- Viral Infections and Vectors 12
- Antifungal resistance and susceptibility 9
- Antimicrobial Resistance in Staphylococcus 4
- Clinical Biochemistry top 1%
- Bacterial Identification and Susceptibility Testing 6
- Endocrinology top 2%
- Microbiology top 5%
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- Streptococcal Infections and Treatments 9
- Mosquito-borne diseases and control 5
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- Fungal Infections and Studies 9
- Co-authors
- Dennis G. MakiSteven M. CallisterMarc GurwithTodd J. KowalskiRonald F. SchellThomas H. CogbillJay L.E. EllingsonSteven D. Lovrich
- Journals
- Clinical Infectious Diseases (8 papers)Journal of Clinical Microbiology (8 papers)Mayo Clinic Proceedings (3 papers)
- Partner nations
- United StatesSwitzerland
In The Last Decade
William A. Agger
64 papers receiving 1.9k citations
Peers
Comparison fields: 5 of 117
- Parasitology 581
- Infectious Diseases 1.0k
- Clinical Biochemistry 313
- Endocrinology 175
- Microbiology 117
Countries citing papers authored by William A. Agger
This map shows the geographic impact of William A. Agger'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 William A. Agger with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites William A. Agger more than expected).
Fields of papers citing papers by William A. Agger
This network shows the impact of papers produced by William A. Agger. 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 William A. Agger. The network helps show where William A. Agger may publish in the future.
Co-authorship network
The 25 scholars most cited alongside William A. Agger, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 4 | |
| 2 | 2017 | 2 | |
| 3 | 2016 | 3 | |
| 4 | 2014 | 28 | |
| 5 | 2013 | 10 | |
| 6 | 2011 | 71 | |
| 7 | 2011 | 7 | |
| 8 | 2005 | 63 | |
| 9 | 2005 | 16 | |
| 10 | 2004 | 2 | |
| 11 | 2001 | 87 | |
| 12 | 1999 | 11 | |
| 13 | 1998 | 9 | |
| 14 | 1997 | 8 | |
| 15 | 1997 | 9 | |
| 16 | 1995 | 11 | |
| 17 | 1995 | 37 | |
| 18 | 1995 | 55 | |
| 19 | 1993 | 4 | |
| 20 | 1978 | 1 |
About William A. Agger
William A. Agger is a scholar working on Parasitology, Infectious Diseases, Clinical Biochemistry, Microbiology and Endocrinology, having authored 64 papers that have together received 2.0k indexed citations. Recurring topics across this work include Vector-borne infectious diseases (15 papers), Viral Infections and Vectors (12 papers), Streptococcal Infections and Treatments (9 papers), Antifungal resistance and susceptibility (9 papers), Fungal Infections and Studies (9 papers), Bacterial Identification and Susceptibility Testing (6 papers), Mosquito-borne diseases and control (5 papers) and Antimicrobial Resistance in Staphylococcus (4 papers). The work is most often cited by research in Parasitology (581 citations), Infectious Diseases (1.0k citations), Clinical Biochemistry (313 citations), Endocrinology (175 citations) and Microbiology (117 citations). William A. Agger has collaborated with scholars based in United States and Switzerland. Frequent co-authors include Dennis G. Maki, Steven M. Callister, Marc Gurwith, Todd J. Kowalski, Ronald F. Schell, Thomas H. Cogbill, Jay L.E. Ellingson, Steven D. Lovrich, Dean A. Jobe and Gary P. Wormser. Their work appears in journals such as Clinical Infectious Diseases, Journal of Clinical Microbiology, Mayo Clinic Proceedings, Clinical Medicine & Research and Medicine.
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.