Can Lu
Impact in
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- Cancer-related molecular mechanisms research
- MicroRNA in disease regulation
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- Viral-associated cancers and disorders
Papers in
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- Cancer-related molecular mechanisms research 5
- Oncology 7
- Viral-associated cancers and disorders 3
- Peptidase Inhibition and Analysis 2
- Cancer Cells and Metastasis 2
- Co-authors
- Chen Chen (3 shared papers)Jian-hua Zhou (4 shared papers)Zhijie Xu (5 shared papers)Bin Xie (3 shared papers)Tomoya Yamaguchi (2 shared papers)Toyoshi Fujimoto (2 shared papers)Hisanori Isomura (2 shared papers)Liang Weng (5 shared papers)
- Journals
- Signal Transduction and Targeted Therapy (1 paper)Cancer Science (1 paper)Journal of Cancer (1 paper)Journal of Cellular and Molecular Medicine (1 paper)Cell Reports (1 paper)
- Partner nations
- ChinaJapanUnited States
In The Last Decade
Can Lu
22 papers receiving 438 citations
Peers
Comparison fields: 5 of 76
- Cancer Research 92
- Oncology 98
- Molecular Biology 201
- Pathology and Forensic Medicine 49
- Cell Biology 47
Countries citing papers authored by Can Lu
This map shows the geographic impact of Can Lu'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 Can Lu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Can Lu more than expected).
Fields of papers citing papers by Can Lu
This network shows the impact of papers produced by Can Lu. 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 Can Lu. The network helps show where Can Lu may publish in the future.
Co-authors
The 25 scholars most cited alongside Can Lu, 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 22 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2016 | 78 | |
| 2 | 2020 | 51 | |
| 3 | 2019 | 44 | |
| 4 | 2014 | 38 | |
| 5 | 2020 | 21 | |
| 6 | 2020 | 19 | |
| 7 | 2023 | 19 | |
| 8 | 2020 | 17 | |
| 9 | 2025 | 17 | |
| 10 | 2019 | 16 | |
| 11 | 2021 | 16 | |
| 12 | 2022 | 16 | |
| 13 | 2021 | 16 | |
| 14 | 2021 | 15 | |
| 15 | Expression of Girdin in primary hepatocellular carcinoma and its effect on cell proliferation and invasion. | 2015 | 12 |
| 16 | 2022 | 11 | |
| 17 | 2025 | 11 | |
| 18 | 2022 | 10 | |
| 19 | 2022 | 8 | |
| 20 | 2025 | 5 |
About Can Lu
Can Lu is a scholar working on Cancer Research, Oncology, Immunology, Cell Biology and Pathology and Forensic Medicine, having authored 22 papers that have together received 444 indexed citations. Recurring topics across this work include Cancer-related molecular mechanisms research (5 papers), Viral-associated cancers and disorders (3 papers), Lymphoma Diagnosis and Treatment (3 papers), Caveolin-1 and cellular processes (3 papers), Immune Cell Function and Interaction (3 papers), Epigenetics and DNA Methylation (2 papers), Peptidase Inhibition and Analysis (2 papers) and Cancer Cells and Metastasis (2 papers). The work is most often cited by research in Cancer Research (92 citations), Oncology (98 citations), Molecular Biology (201 citations), Pathology and Forensic Medicine (49 citations) and Cell Biology (47 citations). Can Lu has collaborated with scholars based in China, Japan and United States. Frequent co-authors include Chen Chen, Jian-hua Zhou, Zhijie Xu, Bin Xie, Tomoya Yamaguchi, Toyoshi Fujimoto, Hisanori Isomura, Liang Weng, Takashi Takahashi and Jinglei Cheng. Their work appears in journals such as Signal Transduction and Targeted Therapy, Cancer Science, Journal of Cancer, Journal of Cellular and Molecular Medicine and Cell Reports.
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.