Ju-Lun Yang
Impact in
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- CAR-T cell therapy research
- Peptidase Inhibition and Analysis
- Cancer-related Molecular Pathways
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- Virus-based gene therapy research
Papers in
- Oncology 23
- CAR-T cell therapy research 6
- Cancer-related Molecular Pathways 6
- HER2/EGFR in Cancer Research 5
- Peptidase Inhibition and Analysis 4
- Colorectal Cancer Treatments and Studies 3
- Cancer Immunotherapy and Biomarkers 3
- Co-authors
- Qiang Feng (17 shared papers)Xinyan Pan (17 shared papers)Shuling Song (11 shared papers)Wenxing Zhao (3 shared papers)Yue Chen (4 shared papers)Fang Dai (3 shared papers)Tao Li (2 shared papers)Lianzhen Li (1 shared paper)
- Journals
- BMC Cancer (5 papers)International Journal of Oncology (2 papers)International Journal of Molecular Medicine (2 papers)Journal of Cancer Research and Clinical Oncology (2 papers)PLoS ONE (2 papers)
- Partner nations
- ChinaUnited States
In The Last Decade
Ju-Lun Yang
33 papers receiving 334 citations
Peers
Comparison fields: 5 of 74
- Oncology 140
- Genetics 99
- Biotechnology 26
- Cancer Research 45
- Molecular Biology 184
Countries citing papers authored by Ju-Lun Yang
This map shows the geographic impact of Ju-Lun Yang'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 Ju-Lun Yang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ju-Lun Yang more than expected).
Fields of papers citing papers by Ju-Lun Yang
This network shows the impact of papers produced by Ju-Lun Yang. 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 Ju-Lun Yang. The network helps show where Ju-Lun Yang may publish in the future.
Co-authors
The 25 scholars most cited alongside Ju-Lun Yang, 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 33 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2010 | 41 | |
| 2 | 2013 | 33 | |
| 3 | 2015 | 27 | |
| 4 | 2016 | 22 | |
| 5 | 2011 | 19 | |
| 6 | 2018 | 17 | |
| 7 | 2023 | 15 | |
| 8 | 2015 | 14 | |
| 9 | 2017 | 13 | |
| 10 | 2016 | 13 | |
| 11 | 2021 | 13 | |
| 12 | 2019 | 12 | |
| 13 | 2021 | 11 | |
| 14 | 2016 | 11 | |
| 15 | 2017 | 10 | |
| 16 | 2018 | 9 | |
| 17 | 2012 | 6 | |
| 18 | 2021 | 6 | |
| 19 | 2018 | 6 | |
| 20 | 2021 | 6 |
About Ju-Lun Yang
Ju-Lun Yang is a scholar working on Oncology, Molecular Biology, Genetics, Radiology, Nuclear Medicine and Imaging and Cancer Research, having authored 33 papers that have together received 338 indexed citations. Recurring topics across this work include Virus-based gene therapy research (8 papers), Monoclonal and Polyclonal Antibodies Research (7 papers), CAR-T cell therapy research (6 papers), Cancer-related Molecular Pathways (6 papers), HER2/EGFR in Cancer Research (5 papers), Peptidase Inhibition and Analysis (4 papers), Colorectal Cancer Treatments and Studies (3 papers) and Cancer Immunotherapy and Biomarkers (3 papers). The work is most often cited by research in Oncology (140 citations), Genetics (99 citations), Biotechnology (26 citations), Cancer Research (45 citations) and Molecular Biology (184 citations). Ju-Lun Yang has collaborated with scholars based in China and United States. Frequent co-authors include Qiang Feng, Xinyan Pan, Shuling Song, Wenxing Zhao, Yue Chen, Fang Dai, Tao Li, Lianzhen Li, Baolin Li and Li Wang. Their work appears in journals such as BMC Cancer, International Journal of Oncology, International Journal of Molecular Medicine, Journal of Cancer Research and Clinical Oncology and PLoS ONE.
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.