David Schauder
Impact in
- Structural Biology top 5%
- Advanced Electron Microscopy Techniques and Applications
- Virology top 5%
- HIV Research and Treatment
Papers in
- Immunology 13
- Immune Cell Function and Interaction 11
- T-cell and B-cell Immunology 8
- Immunotherapy and Immune Responses 6
- Co-authors
- Weiguo Cui (12 shared papers)Ryan Zander (5 shared papers)Sriram Subramaniam (6 shared papers)Mario J. Borgnia (6 shared papers)Alberto Bartesaghi (6 shared papers)Yao Chen (3 shared papers)Jacqueline L.S. Milne (2 shared papers)Erin E. H. Tran (2 shared papers)
- Journals
- Proceedings of the National Academy of Sciences (3 papers)Journal of Visualized Experiments (2 papers)The Journal of Immunology (2 papers)iScience (1 paper)Current Biology (1 paper)
- Partner nations
- United StatesUnited KingdomIndia
In The Last Decade
David Schauder
21 papers receiving 995 citations
Peers
Comparison fields: 5 of 107
- Structural Biology 68
- Virology 147
- Immunology 486
- Oncology 224
- Infectious Diseases 102
Countries citing papers authored by David Schauder
This map shows the geographic impact of David Schauder'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 Schauder with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Schauder more than expected).
Fields of papers citing papers by David Schauder
This network shows the impact of papers produced by David Schauder. 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 Schauder. The network helps show where David Schauder may publish in the future.
Co-authors
The 25 scholars most cited alongside David Schauder, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2012 | 166 | |
| 2 | 2012 | 161 | |
| 3 | 2021 | 116 | |
| 4 | 2018 | 110 | |
| 5 | 2015 | 108 | |
| 6 | 2018 | 64 | |
| 7 | 2013 | 49 | |
| 8 | 2019 | 39 | |
| 9 | 2020 | 38 | |
| 10 | 2021 | 27 | |
| 11 | 2017 | 24 | |
| 12 | 2020 | 20 | |
| 13 | 2021 | 19 | |
| 14 | 2016 | 18 | |
| 15 | 2018 | 16 | |
| 16 | 2011 | 15 | |
| 17 | 2011 | 6 | |
| 18 | 2020 | 2 | |
| 19 | 2013 | 1 | |
| 20 | 2017 | 1 |
About David Schauder
David Schauder is a scholar working on Immunology, Molecular Biology, Genetics, Oncology and Cellular and Molecular Neuroscience, having authored 22 papers that have together received 1.0k indexed citations. Recurring topics across this work include Immune Cell Function and Interaction (11 papers), T-cell and B-cell Immunology (8 papers), Immunotherapy and Immune Responses (6 papers), HIV Research and Treatment (3 papers), CAR-T cell therapy research (3 papers), Virus-based gene therapy research (2 papers), Diabetes and associated disorders (2 papers) and Advanced Electron Microscopy Techniques and Applications (2 papers). The work is most often cited by research in Structural Biology (68 citations), Virology (147 citations), Immunology (486 citations), Oncology (224 citations) and Infectious Diseases (102 citations). David Schauder has collaborated with scholars based in United States, United Kingdom and India. Frequent co-authors include Weiguo Cui, Ryan Zander, Sriram Subramaniam, Mario J. Borgnia, Alberto Bartesaghi, Yao Chen, Jacqueline L.S. Milne, Erin E. H. Tran, Achia Khatun and Oleg Kuybeda. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of Visualized Experiments, The Journal of Immunology, iScience and Current 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.