Jun Gong
Impact in
- Oncology top 1%
- Cancer Immunotherapy and Biomarkers
- Pancreatic and Hepatic Oncology Research
- Colorectal Cancer Treatments and Studies
- CAR-T cell therapy research
- Cancer Research top 5%
- Cancer Genomics and Diagnostics
Papers in
- Oncology 109
- Pancreatic and Hepatic Oncology Research 45
- Cancer Immunotherapy and Biomarkers 31
- Colorectal Cancer Treatments and Studies 22
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- Cancer Genomics and Diagnostics 28
- Co-authors
- Ravi SalgiaAlex Chehrazi‐RaffleAndrew HendifarMarwan FakihMay ChoMonica MitaRichard TuliSumanta K. Pal
- Journals
- Journal of Clinical Oncology (24 papers)Cancers (11 papers)Journal of the National Comprehensive Cancer Network (7 papers)Oncotarget (5 papers)Frontiers in Oncology (4 papers)
- Partner nations
- United StatesChinaJapan
In The Last Decade
Jun Gong
149 papers receiving 3.3k citations
Hit Papers
Peers
Comparison fields: 5 of 127
- Oncology 2.1k
- Cancer Research 569
- Immunology 660
- Pulmonary and Respiratory Medicine 843
- Hepatology 184
Countries citing papers authored by Jun Gong
This map shows the geographic impact of Jun Gong'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 Jun Gong with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Gong more than expected).
Fields of papers citing papers by Jun Gong
This network shows the impact of papers produced by Jun Gong. 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 Jun Gong. The network helps show where Jun Gong may publish in the future.
Co-authors
The 25 scholars most cited alongside Jun Gong, 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 | 2024 | 0 | |
| 2 | 2024 | 2 | |
| 3 | 2024 | 2 | |
| 4 | 2023 | 8 | |
| 5 | 2023 | 4 | |
| 6 | 2023 | 4 | |
| 7 | 2023 | 2 | |
| 8 | 2023 | 5 | |
| 9 | 2023 | 2 | |
| 10 | 2023 | 0 | |
| 11 | 2022 | 4 | |
| 12 | 2021 | 19 | |
| 13 | 2021 | 9 | |
| 14 | 2020 | 4 | |
| 15 | 2019 | 13 | |
| 16 | 2019 | 2 | |
| 17 | 2018 | 1 | |
| 18 | 2017 | 35 | |
| 19 | 2017 | 12 | |
| 20 | [Single nucleotide polymorphisms of CYP1A2 and their correlation with prostate cancer]. | 2011 | 2 |
About Jun Gong
Jun Gong is a scholar working on Oncology, Cancer Research, Pulmonary and Respiratory Medicine, Hepatology and Pathology and Forensic Medicine, having authored 163 papers that have together received 3.4k indexed citations. Recurring topics across this work include Pancreatic and Hepatic Oncology Research (45 papers), Cancer Immunotherapy and Biomarkers (31 papers), Cancer Genomics and Diagnostics (28 papers), Gastric Cancer Management and Outcomes (24 papers), Colorectal Cancer Treatments and Studies (22 papers), Neuroendocrine Tumor Research Advances (14 papers), Genetic factors in colorectal cancer (13 papers) and Hepatocellular Carcinoma Treatment and Prognosis (12 papers). The work is most often cited by research in Oncology (2.1k citations), Cancer Research (569 citations), Immunology (660 citations), Pulmonary and Respiratory Medicine (843 citations) and Hepatology (184 citations). Jun Gong has collaborated with scholars based in United States, China and Japan. Frequent co-authors include Ravi Salgia, Alex Chehrazi‐Raffle, Andrew Hendifar, Marwan Fakih, May Cho, Monica Mita, Richard Tuli, Sumanta K. Pal, Chongkai Wang and Peter P. Lee. Their work appears in journals such as Journal of Clinical Oncology, Cancers, Journal of the National Comprehensive Cancer Network, Oncotarget and Frontiers in Oncology.
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.