Jane Pheby
Impact in
- Infectious Diseases top 5%
- SARS-CoV-2 and COVID-19 Research
- COVID-19 Clinical Research Studies
- Immunology top 10%
- interferon and immune responses
- Immune responses and vaccinations
Papers in
-
- SARS-CoV-2 and COVID-19 Research 4
- COVID-19 Clinical Research Studies 3
-
- interferon and immune responses 3
- Co-authors
- Peter O.O. Julu (1 shared paper)Vikas Kapil (1 shared paper)David Collier (1 shared paper)Anne Zak (1 shared paper)C. B. Wolff (1 shared paper)Ajay Kumar Gupta (1 shared paper)Manish Saxena (1 shared paper)Armida Balawon (1 shared paper)
- Journals
- Nature (4 papers)Journal of the American Heart Association (2 papers)JAMA Cardiology (1 paper)Human Genetics and Genomics Advances (1 paper)Human Genetics (1 paper)
- Partner nations
- United KingdomGermanyItaly
In The Last Decade
Jane Pheby
11 papers receiving 1.1k citations
Jane Pheby's Hit Papers
Peers
Comparison fields: 5 of 93
- Infectious Diseases 493
- Immunology 253
- Neurology 110
- Genetics 181
- Modeling and Simulation 25
Countries citing papers authored by Jane Pheby
This map shows the geographic impact of Jane Pheby'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 Jane Pheby with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jane Pheby more than expected).
Fields of papers citing papers by Jane Pheby
This network shows the impact of papers produced by Jane Pheby. 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 Jane Pheby. The network helps show where Jane Pheby may publish in the future.
Co-authors
The 13 scholars most cited alongside Jane Pheby, 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 | Mapping the human genetic architecture of COVID-19 Hit paper breakdown → | 2021 | 641 |
| 2 | Whole-genome sequencing reveals host factors underlying critical COVID-19 Hit paper breakdown → | 2022 | 228 |
| 3 | GWAS and meta-analysis identifies 49 genetic variants underlying critical COVID-19 Hit paper breakdown → | 2023 | 121 |
| 4 | 2020 | 65 | |
| 5 | 2023 | 56 | |
| 6 | 2021 | 24 | |
| 7 | 2025 | 14 | |
| 8 | 2018 | 13 | |
| 9 | 2024 | 8 | |
| 10 | 2024 | 3 | |
| 11 | 2022 | 1 |
About Jane Pheby
Jane Pheby is a scholar working on Infectious Diseases, Immunology, Cardiology and Cardiovascular Medicine, Genetics and Epidemiology, having authored 11 papers that have together received 1.2k indexed citations. Recurring topics across this work include SARS-CoV-2 and COVID-19 Research (4 papers), COVID-19 Clinical Research Studies (3 papers), interferon and immune responses (3 papers), Heart Failure Treatment and Management (2 papers), Liver Disease Diagnosis and Treatment (1 paper), Machine Learning in Bioinformatics (1 paper), Telemedicine and Telehealth Implementation (1 paper) and Respiratory viral infections research (1 paper). The work is most often cited by research in Infectious Diseases (493 citations), Immunology (253 citations), Neurology (110 citations), Genetics (181 citations) and Modeling and Simulation (25 citations). Jane Pheby has collaborated with scholars based in United Kingdom, Germany and Italy. Frequent co-authors include Peter O.O. Julu, Vikas Kapil, David Collier, Anne Zak, C. B. Wolff, Ajay Kumar Gupta, Manish Saxena, Armida Balawon, Roland Erich Schmieder and Mussadiq Shah. Their work appears in journals such as Nature, Journal of the American Heart Association, JAMA Cardiology, Human Genetics and Genomics Advances and Human Genetics.
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.