Nan Ji
Impact in
- Genetics top 2%
- Glioma Diagnosis and Treatment
- Hepatology top 5%
- Hepatitis C virus research
Papers in
- Genetics 53
- Glioma Diagnosis and Treatment 49
- Co-authors
- Fang Luo (18 shared papers)Liwei Zhang (23 shared papers)Chalet Tan (5 shared papers)Yusheng Li (2 shared papers)Haiyang Yu (3 shared papers)Yilong Ren (4 shared papers)Tao Wang (5 shared papers)Shengli Bi (1 shared paper)
- Journals
- Frontiers in Oncology (9 papers)Journal of Neuro-Oncology (5 papers)World Neurosurgery (5 papers)Frontiers in Immunology (4 papers)Frontiers in Neurology (4 papers)
- Partner nations
- ChinaUnited StatesGermany
In The Last Decade
Nan Ji
173 papers receiving 2.6k citations
Peers
Comparison fields: 5 of 161
- Genetics 420
- Hepatology 178
- Neurology 300
- Cancer Research 297
- Pathology and Forensic Medicine 286
Countries citing papers authored by Nan Ji
This map shows the geographic impact of Nan Ji'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 Nan Ji with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nan Ji more than expected).
Fields of papers citing papers by Nan Ji
This network shows the impact of papers produced by Nan Ji. 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 Nan Ji. The network helps show where Nan Ji may publish in the future.
Co-authors
The 25 scholars most cited alongside Nan Ji, 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 193 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 1996 | 194 | |
| 2 | 2019 | 112 | |
| 3 | 2018 | 110 | |
| 4 | 2005 | 74 | |
| 5 | 2015 | 71 | |
| 6 | 2022 | 68 | |
| 7 | 2017 | 65 | |
| 8 | 2018 | 60 | |
| 9 | 2015 | 56 | |
| 10 | 2014 | 52 | |
| 11 | 2021 | 52 | |
| 12 | 2021 | 49 | |
| 13 | 2014 | 47 | |
| 14 | 2013 | 43 | |
| 15 | 2017 | 41 | |
| 16 | 2003 | 40 | |
| 17 | 2019 | 38 | |
| 18 | 2017 | 36 | |
| 19 | 2017 | 32 | |
| 20 | 2022 | 32 |
About Nan Ji
Nan Ji is a scholar working on Genetics, Molecular Biology, Neurology, Pathology and Forensic Medicine and Radiology, Nuclear Medicine and Imaging, having authored 193 papers that have together received 2.7k indexed citations. Recurring topics across this work include Glioma Diagnosis and Treatment (49 papers), Lymphoma Diagnosis and Treatment (17 papers), CNS Lymphoma Diagnosis and Treatment (16 papers), Radiomics and Machine Learning in Medical Imaging (14 papers), Nanoplatforms for cancer theranostics (10 papers), Trigeminal Neuralgia and Treatments (9 papers), CAR-T cell therapy research (9 papers) and Immunotherapy and Immune Responses (9 papers). The work is most often cited by research in Genetics (420 citations), Hepatology (178 citations), Neurology (300 citations), Cancer Research (297 citations) and Pathology and Forensic Medicine (286 citations). Nan Ji has collaborated with scholars based in China, United States and Germany. Frequent co-authors include Fang Luo, Liwei Zhang, Chalet Tan, Yusheng Li, Haiyang Yu, Yilong Ren, Tao Wang, Shengli Bi, Xiaolan Qi and Hong Cao. Their work appears in journals such as Frontiers in Oncology, Journal of Neuro-Oncology, World Neurosurgery, Frontiers in Immunology and Frontiers in Neurology.
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.