Jennifer A. Smith
- Molecular Biology top 10%
- Immunology top 10%
- Epidemiology
- Genetics top 10%
- Oncology
- Co-authors
- Peter M. HowleyJ. Wade HarperMathew E. SowaMatthias OttingerShaila RahmanYang ShiStephanie E. MohrCaroline E. Shamu
- Topics
- T-cell and B-cell Immunology (7 papers)Monoclonal and Polyclonal Antibodies Research (7 papers)Immune Cell Function and Interaction (5 papers)
- Cited by
- Molecular BiologyVirologyHematology
- Journals
- Proceedings of the National Academy of SciencesNature CommunicationsThe Journal of Experimental Medicine
- Partner nations
- United StatesUnited KingdomBelgium
In The Last Decade
Jennifer A. Smith
27 papers receiving 1.4k citations
Peers
Comparison fields: 5 of 90
- Molecular Biology 1.0k
- Immunology 231
- Epidemiology 202
- Genetics 188
- Oncology 150
Countries citing papers authored by Jennifer A. Smith
This map shows the geographic impact of Jennifer A. Smith'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 Jennifer A. Smith with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jennifer A. Smith more than expected).
Fields of papers citing papers by Jennifer A. Smith
This network shows the impact of papers produced by Jennifer A. Smith. 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 Jennifer A. Smith. The network helps show where Jennifer A. Smith may publish in the future.
Co-authorship network of co-authors of Jennifer A. Smith
This figure shows the co-authorship network connecting the top 25 collaborators of Jennifer A. Smith. A scholar is included among the top collaborators of Jennifer A. Smith 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 Jennifer A. Smith. Jennifer A. Smith 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 | 39 | |
| 4 | 2 | |
| 5 | 5 | |
| 6 | 9 | |
| 7 | 9 | |
| 8 | 25 | |
| 9 | 44 | |
| 10 | 247 | |
| 11 | 32 | |
| 12 | 32 | |
| 13 | 18 | |
| 14 | 5 | |
| 15 | 4 | |
| 16 | 25 | |
| 17 | 6 | |
| 18 | 23 | |
| 19 | 8 | |
| 20 | 25 |
About Jennifer A. Smith
Jennifer A. Smith is a scholar working on Immunology, Infectious Diseases and Radiology, Nuclear Medicine and Imaging, having authored 28 papers that have together received 1.4k indexed citations. Recurring topics across this work include T-cell and B-cell Immunology (7 papers), Monoclonal and Polyclonal Antibodies Research (7 papers) and Immune Cell Function and Interaction (5 papers). The work is most often cited by research in Molecular Biology (1.0k citations), Virology (61 citations) and Hematology (138 citations). Jennifer A. Smith has collaborated with scholars based in United States, United Kingdom and Belgium. Frequent co-authors include Peter M. Howley, J. Wade Harper, Mathew E. Sowa, Matthias Ottinger, Shaila Rahman, Yang Shi, Stephanie E. Mohr, Caroline E. Shamu, Norbert Perrimon and Ralph A. Neumüller. Their work appears in journals such as Proceedings of the National Academy of Sciences, Nature Communications and The Journal of Experimental 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.