Peter De Hoff
Impact in
- Infectious Diseases top 5%
- SARS-CoV-2 detection and testing
- SARS-CoV-2 and COVID-19 Research
- Cancer Research top 10%
- MicroRNA in disease regulation
- Cancer-related molecular mechanisms research
Papers in
-
- SARS-CoV-2 and COVID-19 Research 3
- SARS-CoV-2 detection and testing 3
-
- COVID-19 epidemiological studies 3
- Co-authors
- James Umen (2 shared papers)Louise Chang Laurent (4 shared papers)Sa Geng (1 shared paper)Alejandro Villar‐Prados (1 shared paper)Robert E. Morey (1 shared paper)Akira Yokoi (1 shared paper)Anil K. Sood (1 shared paper)Jianhua Zhang (1 shared paper)
- Journals
- Cell (3 papers)mSystems (3 papers)Infection Control and Hospital Epidemiology (1 paper)American Journal of Respiratory and Critical Care Medicine (1 paper)Science Advances (1 paper)
- Partner nations
- United StatesItalyChina
In The Last Decade
Peter De Hoff
18 papers receiving 1.3k citations
Peter De Hoff's Hit Papers
Peers
Comparison fields: 5 of 107
- Infectious Diseases 535
- Cancer Research 300
- Modeling and Simulation 70
- Molecular Biology 657
- Biomedical Engineering 182
Countries citing papers authored by Peter De Hoff
This map shows the geographic impact of Peter De Hoff'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 Peter De Hoff with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Peter De Hoff more than expected).
Fields of papers citing papers by Peter De Hoff
This network shows the impact of papers produced by Peter De Hoff. 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 Peter De Hoff. The network helps show where Peter De Hoff may publish in the future.
Co-authors
The 25 scholars most cited alongside Peter De Hoff, 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 | Wastewater sequencing reveals early cryptic SARS-CoV-2 variant transmission Hit paper breakdown → | 2022 | 333 |
| 2 | 2019 | 258 | |
| 3 | 2019 | 244 | |
| 4 | Emergence and rapid transmission of SARS-CoV-2 B.1.1.7 in the United States Hit paper breakdown → | 2021 | 234 |
| 5 | 2014 | 62 | |
| 6 | 2015 | 58 | |
| 7 | 2022 | 28 | |
| 8 | 2023 | 23 | |
| 9 | 2003 | 13 | |
| 10 | 2021 | 9 | |
| 11 | 2022 | 9 | |
| 12 | 2010 | 9 | |
| 13 | 2023 | 8 | |
| 14 | 2022 | 6 | |
| 15 | 2022 | 4 | |
| 16 | 2024 | 3 | |
| 17 | 2023 | 2 | |
| 18 | 2022 | 1 |
About Peter De Hoff
Peter De Hoff is a scholar working on Infectious Diseases, Modeling and Simulation, Obstetrics and Gynecology, Pulmonary and Respiratory Medicine and Oceanography, having authored 18 papers that have together received 1.3k indexed citations. Recurring topics across this work include Infection Control and Ventilation (3 papers), COVID-19 epidemiological studies (3 papers), SARS-CoV-2 and COVID-19 Research (3 papers), SARS-CoV-2 detection and testing (3 papers), Extracellular vesicles in disease (3 papers), Algal biology and biofuel production (2 papers), COVID-19 Impact on Reproduction (2 papers) and Marine and coastal plant biology (2 papers). The work is most often cited by research in Infectious Diseases (535 citations), Cancer Research (300 citations), Modeling and Simulation (70 citations), Molecular Biology (657 citations) and Biomedical Engineering (182 citations). Peter De Hoff has collaborated with scholars based in United States, Italy and China. Frequent co-authors include James Umen, Louise Chang Laurent, Sa Geng, Alejandro Villar‐Prados, Robert E. Morey, Akira Yokoi, Anil K. Sood, Jianhua Zhang, Jared K. Burks and Jinsong Liu. Their work appears in journals such as Cell, mSystems, Infection Control and Hospital Epidemiology, American Journal of Respiratory and Critical Care Medicine and Science Advances.
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.