David R. Parks
- Molecular Biology top 5%
- Immunology top 1%
- Radiology, Nuclear Medicine and Imaging top 1%
- Oncology top 5%
- Biomedical Engineering top 5%
- Co-authors
- L A HerzenbergLeonard A. HerzenbergLeonore A. HerzenbergWayne MooreRichard R. HardyKyoko HayakawaMario RoedererJames W. Tung
- Topics
- Single-cell and spatial transcriptomics (19 papers)Monoclonal and Polyclonal Antibodies Research (15 papers)T-cell and B-cell Immunology (14 papers)
- Partner nations
- United StatesRussiaCanada
In The Last Decade
David R. Parks
57 papers receiving 5.1k citations
Hit Papers
Peers
Comparison fields: 5 of 159
- Molecular Biology 2.3k
- Immunology 2.2k
- Radiology, Nuclear Medicine and Imaging 974
- Oncology 566
- Biomedical Engineering 497
Countries citing papers authored by David R. Parks
This map shows the geographic impact of David R. Parks'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 David R. Parks with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David R. Parks more than expected).
Fields of papers citing papers by David R. Parks
This network shows the impact of papers produced by David R. Parks. 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 David R. Parks. The network helps show where David R. Parks may publish in the future.
Co-authorship network of co-authors of David R. Parks
This figure shows the co-authorship network connecting the top 25 collaborators of David R. Parks. A scholar is included among the top collaborators of David R. Parks 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 David R. Parks. David R. Parks is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 9 | |
| 2 | 13 | |
| 3 | 7 | |
| 4 | 151 | |
| 5 | 353 | |
| 6 | Performance of Ultra-Scale Applications on Leading Vector and Scalar HPC Platforms | 1 |
| 7 | 117 | |
| 8 | 40 | |
| 9 | 405 | |
| 10 | 218 | |
| 11 | 1 | |
| 12 | 76 | |
| 13 | 5 | |
| 14 | 16 | |
| 15 | 177 | |
| 16 | 126 | |
| 17 | The LY‐1B Cell Lineagebreakdown → | 521 |
| 18 | 97 | |
| 19 | The "Ly-1 B" cell subpopulation in normal immunodefective, and autoimmune mice.breakdown → | 692 |
| 20 | 152 |
About David R. Parks
David R. Parks is a scholar working on Biophysics, Immunology and Radiology, Nuclear Medicine and Imaging, having authored 57 papers that have together received 5.3k indexed citations. Recurring topics across this work include Single-cell and spatial transcriptomics (19 papers), Monoclonal and Polyclonal Antibodies Research (15 papers) and T-cell and B-cell Immunology (14 papers). The work is most often cited by research in Immunology (2.2k citations), Biophysics (402 citations) and Radiology, Nuclear Medicine and Imaging (974 citations). David R. Parks has collaborated with scholars based in United States, Russia and Canada. Frequent co-authors include L A Herzenberg, Leonard A. Herzenberg, Leonore A. Herzenberg, Wayne Moore, Richard R. Hardy, Kyoko Hayakawa, Mario Roederer, James W. Tung, Vernon T. Oi and Bita Sahaf. Their work appears in journals such as Nature, Proceedings of the National Academy of Sciences and Physical Review Letters.
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.