Xiangjun Tang
Impact in
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- MicroRNA in disease regulation
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- Virus-based gene therapy research
Papers in
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- RNA Interference and Gene Delivery 4
- RNA modifications and cancer 2
- Circular RNAs in diseases 2
- Genetics 7
- Glioma Diagnosis and Treatment 6
- Virus-based gene therapy research 3
- Co-authors
- Long‐Jun Dai (12 shared papers)Kuan-Ming Huang (7 shared papers)Li Zhang (6 shared papers)Jie Luo (6 shared papers)Zhuoshun Yang (4 shared papers)Xuyong Sun (3 shared papers)Garth L. Warnock (3 shared papers)Bin Wang (2 shared papers)
- Journals
- Molecular Therapy — Oncolytics (2 papers)Frontiers in Oncology (2 papers)Oncotarget (2 papers)Bioactive Materials (1 paper)Frontiers in Bioengineering and Biotechnology (1 paper)
- Partner nations
- ChinaUnited StatesCanada
In The Last Decade
Xiangjun Tang
26 papers receiving 557 citations
Peers
Comparison fields: 5 of 81
- Cancer Research 108
- Genetics 56
- Biomaterials 73
- Molecular Biology 302
- Pharmaceutical Science 25
Countries citing papers authored by Xiangjun Tang
This map shows the geographic impact of Xiangjun Tang'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 Xiangjun Tang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiangjun Tang more than expected).
Fields of papers citing papers by Xiangjun Tang
This network shows the impact of papers produced by Xiangjun Tang. 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 Xiangjun Tang. The network helps show where Xiangjun Tang may publish in the future.
Co-authors
The 25 scholars most cited alongside Xiangjun Tang, 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 27 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2015 | 134 | |
| 2 | 2016 | 60 | |
| 3 | 2019 | 54 | |
| 4 | 2020 | 37 | |
| 5 | TRAIL-engineered bone marrow-derived mesenchymal stem cells: TRAIL expression and cytotoxic effects on C6 glioma cells. | 2014 | 31 |
| 6 | 2016 | 31 | |
| 7 | 2021 | 24 | |
| 8 | 2012 | 23 | |
| 9 | 2019 | 19 | |
| 10 | 2020 | 18 | |
| 11 | 2022 | 17 | |
| 12 | 2016 | 17 | |
| 13 | 2022 | 16 | |
| 14 | 2013 | 14 | |
| 15 | 2021 | 14 | |
| 16 | 2016 | 11 | |
| 17 | 2024 | 9 | |
| 18 | 2024 | 9 | |
| 19 | 2014 | 7 | |
| 20 | 2020 | 7 |
About Xiangjun Tang
Xiangjun Tang is a scholar working on Molecular Biology, Genetics, Pulmonary and Respiratory Medicine, Cancer Research and Biomaterials, having authored 27 papers that have together received 563 indexed citations. Recurring topics across this work include Glioma Diagnosis and Treatment (6 papers), RNA Interference and Gene Delivery (4 papers), Nanoparticle-Based Drug Delivery (3 papers), Virus-based gene therapy research (3 papers), Sarcoma Diagnosis and Treatment (2 papers), Cancer-related molecular mechanisms research (2 papers), RNA modifications and cancer (2 papers) and Circular RNAs in diseases (2 papers). The work is most often cited by research in Cancer Research (108 citations), Genetics (56 citations), Biomaterials (73 citations), Molecular Biology (302 citations) and Pharmaceutical Science (25 citations). Xiangjun Tang has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Long‐Jun Dai, Kuan-Ming Huang, Li Zhang, Jie Luo, Zhuoshun Yang, Xuyong Sun, Garth L. Warnock, Bin Wang, Qianxue Chen and Gang Wang. Their work appears in journals such as Molecular Therapy — Oncolytics, Frontiers in Oncology, Oncotarget, Bioactive Materials and Frontiers in Bioengineering and Biotechnology.
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.