William G. Gunn
- Statistics, Probability and Uncertainty top 2%
- Molecular Biology
- Information Systems and Management top 10%
- Information Systems
- Cancer Research
- Co-authors
- Elizabeth IornsTimothy M. ErringtonBrian A. NosekFraser Elisabeth TanŁukasz WieteskaMcLane J. WatsonCynthia S. HinckT. J. Yao
- Topics
- Immunotherapy and Immune Responses (3 papers)Cancer Research and Treatments (2 papers)CAR-T cell therapy research (2 papers)
- Cited by
- Statistics, Probability and UncertaintyInformation Systems and ManagementHealth Informatics
- Journals
- The Journal of Experimental MedicineSHILAP Revista de lepidopterologíaNature Cell Biology
- Partner nations
- United StatesSpainRomania
In The Last Decade
William G. Gunn
9 papers receiving 266 citations
Peers
Comparison fields: 5 of 96
- Statistics, Probability and Uncertainty 94
- Molecular Biology 78
- Information Systems and Management 39
- Information Systems 38
- Cancer Research 28
Countries citing papers authored by William G. Gunn
This map shows the geographic impact of William G. Gunn'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 G. Gunn with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites William G. Gunn more than expected).
Fields of papers citing papers by William G. Gunn
This network shows the impact of papers produced by William G. Gunn. 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 G. Gunn. The network helps show where William G. Gunn may publish in the future.
Co-authorship network of co-authors of William G. Gunn
This figure shows the co-authorship network connecting the top 25 collaborators of William G. Gunn. A scholar is included among the top collaborators of William G. Gunn 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 G. Gunn. William G. Gunn 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 | 2 | |
| 3 | 0 | |
| 4 | 4 | |
| 5 | 20 | |
| 6 | 1 | |
| 7 | 10 | |
| 8 | 1 | |
| 9 | 183 | |
| 10 | 47 | |
| 11 | Reproducibility Project: Cancer Biology | 13 |
About William G. Gunn
William G. Gunn is a scholar working on Statistics, Probability and Uncertainty, Biotechnology and History and Philosophy of Science, having authored 11 papers that have together received 281 indexed citations. Recurring topics across this work include Immunotherapy and Immune Responses (3 papers), Cancer Research and Treatments (2 papers) and CAR-T cell therapy research (2 papers). The work is most often cited by research in Statistics, Probability and Uncertainty (94 citations), Information Systems and Management (39 citations) and Health Informatics (5 citations). William G. Gunn has collaborated with scholars based in United States, Spain and Romania. Frequent co-authors include Elizabeth Iorns, Timothy M. Errington, Brian A. Nosek, Fraser Elisabeth Tan, Łukasz Wieteska, McLane J. Watson, Cynthia S. Hinck, T. J. Yao, Greg M. Delgoffe and Andrew P. Hinck. Their work appears in journals such as The Journal of Experimental Medicine, SHILAP Revista de lepidopterología and Nature Cell Biology.
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.