William R. Schwan
- Molecular Biology top 10%
- Endocrinology top 0.5%
- Infectious Diseases top 5%
- Epidemiology top 10%
- Genetics top 5%
- Co-authors
- J L DuncanS.J. HultgrenC. Kendall StoverAnthony J. SchaefferDennis J. KopeckoKim R. FolgerHeather RitchieSilvija N. Coulter
- Topics
- Antimicrobial Resistance in Staphylococcus (21 papers)Escherichia coli research studies (15 papers)Bacterial Genetics and Biotechnology (13 papers)
- Journals
- Proceedings of the National Academy of SciencesSHILAP Revista de lepidopterologíaJournal of Bacteriology
- Partner nations
- United StatesGermanyChina
In The Last Decade
William R. Schwan
62 papers receiving 1.9k citations
Peers
Comparison fields: 5 of 111
- Molecular Biology 802
- Endocrinology 659
- Infectious Diseases 552
- Epidemiology 438
- Genetics 382
Countries citing papers authored by William R. Schwan
This map shows the geographic impact of William R. Schwan'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 R. Schwan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites William R. Schwan more than expected).
Fields of papers citing papers by William R. Schwan
This network shows the impact of papers produced by William R. Schwan. 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 R. Schwan. The network helps show where William R. Schwan may publish in the future.
Co-authorship network of co-authors of William R. Schwan
This figure shows the co-authorship network connecting the top 25 collaborators of William R. Schwan. A scholar is included among the top collaborators of William R. Schwan 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 William R. Schwan. William R. Schwan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 11 | |
| 4 | 11 | |
| 5 | 10 | |
| 6 | 16 | |
| 7 | 8 | |
| 8 | 20 | |
| 9 | 14 | |
| 10 | 30 | |
| 11 | 40 | |
| 12 | 26 | |
| 13 | 44 | |
| 14 | 28 | |
| 15 | 46 | |
| 16 | 228 | |
| 17 | 2 | |
| 18 | 1 | |
| 19 | 18 | |
| 20 | 6 |
About William R. Schwan
William R. Schwan is a scholar working on Endocrinology, Infectious Diseases and Molecular Medicine, having authored 63 papers that have together received 1.9k indexed citations. Recurring topics across this work include Antimicrobial Resistance in Staphylococcus (21 papers), Escherichia coli research studies (15 papers) and Bacterial Genetics and Biotechnology (13 papers). The work is most often cited by research in Endocrinology (659 citations), Molecular Medicine (235 citations) and Infectious Diseases (552 citations). William R. Schwan has collaborated with scholars based in United States, Germany and China. Frequent co-authors include J L Duncan, S.J. Hultgren, C. Kendall Stover, Anthony J. Schaeffer, Dennis J. Kopecko, Kim R. Folger, Heather Ritchie, Silvija N. Coulter, Arnold S. Bayer and Xiao-Zhe Huang. Their work appears in journals such as Proceedings of the National Academy of Sciences, SHILAP Revista de lepidopterología and Journal of Bacteriology.
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.