Dee Aud
Impact in
- Immunology top 5%
- Immune Response and Inflammation
- Complement system in diseases
- T-cell and B-cell Immunology
- Genetics top 10%
- Genetic Mapping and Diversity in Plants and Animals
- Genetic Associations and Epidemiology
Papers in
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- Immune Response and Inflammation 2
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- Rheumatoid Arthritis Research and Therapies 2
- Co-authors
- Gary Peltz (6 shared papers)Robyn Maree Slattery (2 shared papers)Stacie A. Dalrymple (2 shared papers)Andrew Grupe (4 shared papers)Søren Germer (3 shared papers)Tom McNeil (2 shared papers)Jonathan Usuka (2 shared papers)Russell Higuchi (2 shared papers)
- Journals
- Blood (2 papers)Infection and Immunity (2 papers)Nature Immunology (1 paper)American Journal Of Pathology (1 paper)Diabetes (1 paper)
- Partner nations
- United StatesGermanyItaly
In The Last Decade
Dee Aud
16 papers receiving 1.5k citations
Peers
Comparison fields: 5 of 92
- Immunology 386
- Genetics 292
- Physiology 195
- Oncology 159
- Hematology 74
Countries citing papers authored by Dee Aud
This map shows the geographic impact of Dee Aud'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 Dee Aud with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dee Aud more than expected).
Fields of papers citing papers by Dee Aud
This network shows the impact of papers produced by Dee Aud. 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 Dee Aud. The network helps show where Dee Aud may publish in the future.
Co-authors
The 25 scholars most cited alongside Dee Aud, 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 | 2000 | 326 | |
| 2 | 1995 | 260 | |
| 3 | 1995 | 240 | |
| 4 | 2001 | 236 | |
| 5 | 1996 | 175 | |
| 6 | 2008 | 67 | |
| 7 | 2006 | 64 | |
| 8 | 2007 | 36 | |
| 9 | 2003 | 34 | |
| 10 | 2017 | 33 | |
| 11 | 2006 | 26 | |
| 12 | Grupe, A. et al. In silico mapping of complex disease-related traits in mice. Science 292, 1915-1918 | 2001 | 21 |
| 13 | 2019 | 20 | |
| 14 | 2014 | 4 | |
| 15 | 2007 | 3 | |
| 16 | 2014 | 2 |
About Dee Aud
Dee Aud is a scholar working on Immunology, Rheumatology, Radiology, Nuclear Medicine and Imaging, Genetics and Oncology, having authored 16 papers that have together received 1.5k indexed citations. Recurring topics across this work include Monoclonal and Polyclonal Antibodies Research (4 papers), Acute Myeloid Leukemia Research (2 papers), Genetic Mapping and Diversity in Plants and Animals (2 papers), Rheumatoid Arthritis Research and Therapies (2 papers), Asthma and respiratory diseases (2 papers), Genetic Associations and Epidemiology (2 papers), Cytokine Signaling Pathways and Interactions (2 papers) and Immune Response and Inflammation (2 papers). The work is most often cited by research in Immunology (386 citations), Genetics (292 citations), Physiology (195 citations), Oncology (159 citations) and Hematology (74 citations). Dee Aud has collaborated with scholars based in United States, Germany and Italy. Frequent co-authors include Gary Peltz, Robyn Maree Slattery, Stacie A. Dalrymple, Andrew Grupe, Søren Germer, Tom McNeil, Jonathan Usuka, Russell Higuchi, John K. Belknap and Robert F. Klein. Their work appears in journals such as Blood, Infection and Immunity, Nature Immunology, American Journal Of Pathology and Diabetes.
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.