Tomi Jun
Impact in
- Hepatology top 10%
- Hepatitis C virus research
- Infectious Diseases top 10%
- COVID-19 Clinical Research Studies
- SARS-CoV-2 and COVID-19 Research
Papers in
- Oncology 21
- Cancer Immunotherapy and Biomarkers 9
- PARP inhibition in cancer therapy 5
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- Prostate Cancer Treatment and Research 7
- Co-authors
- Kuan‐lin Huang (7 shared papers)Douglas Tremblay (3 shared papers)Ruma Rajbhandari (1 shared paper)Hamed Khalili (1 shared paper)Sheena Bhalla (3 shared papers)Raymond T. Chung (1 shared paper)Leonard Naymagon (2 shared papers)Jonathan Feld (3 shared papers)
- Journals
- Journal of Clinical Oncology (8 papers)Scientific Reports (2 papers)JCO Clinical Cancer Informatics (2 papers)Annals of Oncology (2 papers)The Oncologist (2 papers)
- Partner nations
- United StatesTaiwanUnited Kingdom
In The Last Decade
Tomi Jun
49 papers receiving 519 citations
Peers
Comparison fields: 5 of 89
- Hepatology 105
- Infectious Diseases 150
- Internal Medicine 23
- Epidemiology 150
- Oncology 115
Countries citing papers authored by Tomi Jun
This map shows the geographic impact of Tomi Jun'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 Tomi Jun with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tomi Jun more than expected).
Fields of papers citing papers by Tomi Jun
This network shows the impact of papers produced by Tomi Jun. 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 Tomi Jun. The network helps show where Tomi Jun may publish in the future.
Co-authors
The 25 scholars most cited alongside Tomi Jun, 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 53 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 83 | |
| 2 | 2016 | 33 | |
| 3 | 2020 | 32 | |
| 4 | 2019 | 31 | |
| 5 | 2018 | 29 | |
| 6 | 2021 | 28 | |
| 7 | 2019 | 27 | |
| 8 | 2018 | 26 | |
| 9 | 2017 | 25 | |
| 10 | 2021 | 23 | |
| 11 | 2022 | 15 | |
| 12 | 2021 | 14 | |
| 13 | 2017 | 14 | |
| 14 | 2018 | 13 | |
| 15 | 2021 | 12 | |
| 16 | 2019 | 11 | |
| 17 | 2014 | 10 | |
| 18 | 2017 | 10 | |
| 19 | 2024 | 9 | |
| 20 | 2023 | 9 |
About Tomi Jun
Tomi Jun is a scholar working on Oncology, Pulmonary and Respiratory Medicine, Epidemiology, Infectious Diseases and Hepatology, having authored 53 papers that have together received 528 indexed citations. Recurring topics across this work include Cancer Immunotherapy and Biomarkers (9 papers), Prostate Cancer Treatment and Research (7 papers), COVID-19 Clinical Research Studies (7 papers), Cancer Genomics and Diagnostics (6 papers), Hepatitis C virus research (5 papers), PARP inhibition in cancer therapy (5 papers), Liver Disease Diagnosis and Treatment (5 papers) and Hepatocellular Carcinoma Treatment and Prognosis (4 papers). The work is most often cited by research in Hepatology (105 citations), Infectious Diseases (150 citations), Internal Medicine (23 citations), Epidemiology (150 citations) and Oncology (115 citations). Tomi Jun has collaborated with scholars based in United States, Taiwan and United Kingdom. Frequent co-authors include Kuan‐lin Huang, Douglas Tremblay, Ruma Rajbhandari, Hamed Khalili, Sheena Bhalla, Raymond T. Chung, Leonard Naymagon, Jonathan Feld, Ashwin N. Ananthakrishnan and Mindie H. Nguyen. Their work appears in journals such as Journal of Clinical Oncology, Scientific Reports, JCO Clinical Cancer Informatics, Annals of Oncology and The Oncologist.
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.