Danjun Song
Impact in
- Hepatology top 5%
- Hepatocellular Carcinoma Treatment and Prognosis
Papers in ⓘ
- Oncology 12
- Drug Transport and Resistance Mechanisms 4
- Pancreatic and Hepatic Oncology Research 3
- Hepatology 10
- Hepatocellular Carcinoma Treatment and Prognosis 8
- Co-authors
- Kai Zhu (6 shared papers)Shengxiang Rao (8 shared papers)Manning Wang (5 shared papers)Jia Fan (6 shared papers)Xiaoying Wang (5 shared papers)Qiang Gao (6 shared papers)Manyun Dai (6 shared papers)Aiming Liu (7 shared papers)
- Journals
- Annals of Translational Medicine (2 papers)Cancers (2 papers)World Journal of Surgical Oncology (2 papers)Biomarker Research (1 paper)Journal of Pharmacy and Pharmacology (1 paper)
- Partner nations
- ChinaUnited StatesEthiopia
In The Last Decade
Danjun Song
26 papers receiving 457 citations
Peers
Comparison fields: 5 of 77
- Hepatology 134
- Health Informatics 8
- Radiology, Nuclear Medicine and Imaging 130
- Cancer Research 73
- Oncology 127
Countries citing papers authored by Danjun Song
This map shows the geographic impact of Danjun Song'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 Danjun Song with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Danjun Song more than expected).
Fields of papers citing papers by Danjun Song
This network shows the impact of papers produced by Danjun Song. 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 Danjun Song. The network helps show where Danjun Song may publish in the future.
Co-authors
The 25 scholars most cited alongside Danjun Song, 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 26 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 69 | |
| 2 | 2023 | 54 | |
| 3 | 2022 | 49 | |
| 4 | 2017 | 41 | |
| 5 | 2020 | 36 | |
| 6 | 2016 | 34 | |
| 7 | 2016 | 27 | |
| 8 | 2016 | 21 | |
| 9 | 2020 | 18 | |
| 10 | 2022 | 17 | |
| 11 | 2022 | 15 | |
| 12 | 2022 | 9 | |
| 13 | 2017 | 9 | |
| 14 | 2021 | 9 | |
| 15 | 2023 | 7 | |
| 16 | 2023 | 7 | |
| 17 | 2024 | 7 | |
| 18 | 2025 | 6 | |
| 19 | 2024 | 5 | |
| 20 | 2022 | 4 |
About Danjun Song
Danjun Song is a scholar working on Oncology, Hepatology, Molecular Biology, Surgery and Pulmonary and Respiratory Medicine, having authored 26 papers that have together received 459 indexed citations. Recurring topics across this work include Hepatocellular Carcinoma Treatment and Prognosis (8 papers), Cholangiocarcinoma and Gallbladder Cancer Studies (6 papers), Radiomics and Machine Learning in Medical Imaging (5 papers), Ferroptosis and cancer prognosis (4 papers), Peroxisome Proliferator-Activated Receptors (4 papers), Drug Transport and Resistance Mechanisms (4 papers), Cancer-related molecular mechanisms research (3 papers) and Pancreatic and Hepatic Oncology Research (3 papers). The work is most often cited by research in Hepatology (134 citations), Health Informatics (8 citations), Radiology, Nuclear Medicine and Imaging (130 citations), Cancer Research (73 citations) and Oncology (127 citations). Danjun Song has collaborated with scholars based in China, United States and Ethiopia. Frequent co-authors include Kai Zhu, Shengxiang Rao, Manning Wang, Jia Fan, Xiaoying Wang, Qiang Gao, Manyun Dai, Aiming Liu, Jiabin Cai and Yining Wang. Their work appears in journals such as Annals of Translational Medicine, Cancers, World Journal of Surgical Oncology, Biomarker Research and Journal of Pharmacy and Pharmacology.
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.