John D. Huck
Impact in
- Infectious Diseases top 5%
- COVID-19 Clinical Research Studies
- SARS-CoV-2 and COVID-19 Research
- Neurology top 5%
- Long-Term Effects of COVID-19
Papers in
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- Immunotherapy and Immune Responses 2
-
- SARS-CoV-2 and COVID-19 Research 4
- COVID-19 Clinical Research Studies 2
- Co-authors
- Daniel T. Gewirth (6 shared papers)Nanette L. S. Que (5 shared papers)Zihai Li (3 shared papers)Jennifer A. Surtees (1 shared paper)Ilya J. Finkelstein (1 shared paper)Gabriela Chiosis (3 shared papers)Tony Taldone (3 shared papers)Gregory M. Williams (1 shared paper)
- Journals
- Cell Reports (2 papers)Nature Communications (2 papers)Proteins Structure Function and Bioinformatics (2 papers)Nature (2 papers)Science Immunology (2 papers)
- Partner nations
- United StatesAustraliaSenegal
In The Last Decade
John D. Huck
17 papers receiving 1.1k citations
John D. Huck's Hit Papers
Peers
Comparison fields: 5 of 88
- Infectious Diseases 407
- Neurology 322
- Immunology 212
- Biological Psychiatry 14
- Critical Care and Intensive Care Medicine 24
Countries citing papers authored by John D. Huck
This map shows the geographic impact of John D. Huck'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 John D. Huck with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John D. Huck more than expected).
Fields of papers citing papers by John D. Huck
This network shows the impact of papers produced by John D. Huck. 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 John D. Huck. The network helps show where John D. Huck may publish in the future.
Co-authors
The 25 scholars most cited alongside John D. Huck, 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 | Diverse functional autoantibodies in patients with COVID-19 Hit paper breakdown → | 2021 | 728 |
| 2 | 2020 | 108 | |
| 3 | 2017 | 56 | |
| 4 | 2016 | 40 | |
| 5 | 2024 | 33 | |
| 6 | 2022 | 28 | |
| 7 | 2022 | 26 | |
| 8 | 2019 | 20 | |
| 9 | 2019 | 14 | |
| 10 | 2023 | 13 | |
| 11 | 2016 | 10 | |
| 12 | 2019 | 9 | |
| 13 | 2024 | 8 | |
| 14 | 2023 | 7 | |
| 15 | 2016 | 4 | |
| 16 | 2024 | 3 | |
| 17 | 2023 | 1 | |
| 18 | 2025 | 1 | |
| 19 | 2026 | 0 |
About John D. Huck
John D. Huck is a scholar working on Immunology, Infectious Diseases, Oncology, Molecular Biology and Neurology, having authored 19 papers that have together received 1.1k indexed citations. Recurring topics across this work include Heat shock proteins research (5 papers), SARS-CoV-2 and COVID-19 Research (4 papers), Protein Structure and Dynamics (4 papers), COVID-19 Clinical Research Studies (2 papers), CAR-T cell therapy research (2 papers), Cancer Immunotherapy and Biomarkers (2 papers), Enzyme Structure and Function (2 papers) and Immunotherapy and Immune Responses (2 papers). The work is most often cited by research in Infectious Diseases (407 citations), Neurology (322 citations), Immunology (212 citations), Biological Psychiatry (14 citations) and Critical Care and Intensive Care Medicine (24 citations). John D. Huck has collaborated with scholars based in United States, Australia and Senegal. Frequent co-authors include Daniel T. Gewirth, Nanette L. S. Que, Zihai Li, Jennifer A. Surtees, Ilya J. Finkelstein, Gabriela Chiosis, Tony Taldone, Gregory M. Williams, Yoori Kim and Carsten Krieg. Their work appears in journals such as Cell Reports, Nature Communications, Proteins Structure Function and Bioinformatics, Nature and Science Immunology.
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.