Yan Long
Impact in
- Biotechnology top 5%
- Cancer Research and Treatments
- Cancer Research top 10%
- Cancer, Hypoxia, and Metabolism
- Cancer-related molecular mechanisms research
Papers in
-
- Cancer Research and Treatments 6
-
- Cancer, Lipids, and Metabolism 2
- Co-authors
- Macus Tien Kuo (7 shared papers)Niramol Savaraj (7 shared papers)Lynn G. Feun (7 shared papers)Wen-Bin Tsai (6 shared papers)Isamu Aiba (2 shared papers)Hui‐Kuan Lin (1 shared paper)Medhi Wangpaichitr (2 shared papers)Helen H.W. Chen (5 shared papers)
- Journals
- Molecular Cancer Therapeutics (2 papers)Scientific Reports (2 papers)Oncotarget (2 papers)Translational Oncology (1 paper)Cell Biology International (1 paper)
- Partner nations
- United StatesChinaTaiwan
In The Last Decade
Yan Long
14 papers receiving 567 citations
Peers
Comparison fields: 5 of 73
- Biotechnology 153
- Cancer Research 208
- Oncology 132
- Biochemistry 34
- Molecular Biology 306
Countries citing papers authored by Yan Long
This map shows the geographic impact of Yan Long'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 Yan Long with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yan Long more than expected).
Fields of papers citing papers by Yan Long
This network shows the impact of papers produced by Yan Long. 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 Yan Long. The network helps show where Yan Long may publish in the future.
Co-authors
The 25 scholars most cited alongside Yan Long, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2012 | 182 | |
| 2 | 2013 | 97 | |
| 3 | 2012 | 67 | |
| 4 | 2016 | 39 | |
| 5 | 2019 | 34 | |
| 6 | 2020 | 33 | |
| 7 | 2015 | 33 | |
| 8 | 2022 | 24 | |
| 9 | 2017 | 21 | |
| 10 | 2015 | 18 | |
| 11 | 2019 | 14 | |
| 12 | 2017 | 7 | |
| 13 | [Xihuang Pills and its main components inhibit PI3K/Akt/mTOR signaling pathways and promote the apoptosis of prostate cancer cells in PC-3 tumor-bearing mice]. | 2021 | 4 |
| 14 | 2024 | 1 | |
| 15 | 2025 | 0 | |
| 16 | 2025 | 0 |
About Yan Long
Yan Long is a scholar working on Biotechnology, Cancer Research, Oncology, Molecular Biology and Pharmacology, having authored 16 papers that have together received 574 indexed citations. Recurring topics across this work include Cancer Research and Treatments (6 papers), Neuroblastoma Research and Treatments (3 papers), Trace Elements in Health (3 papers), Drug Transport and Resistance Mechanisms (3 papers), Phagocytosis and Immune Regulation (2 papers), Computational Drug Discovery Methods (2 papers), Cancer, Lipids, and Metabolism (2 papers) and Virus-based gene therapy research (2 papers). The work is most often cited by research in Biotechnology (153 citations), Cancer Research (208 citations), Oncology (132 citations), Biochemistry (34 citations) and Molecular Biology (306 citations). Yan Long has collaborated with scholars based in United States, China and Taiwan. Frequent co-authors include Macus Tien Kuo, Niramol Savaraj, Lynn G. Feun, Wen-Bin Tsai, Isamu Aiba, Hui‐Kuan Lin, Medhi Wangpaichitr, Helen H.W. Chen, Takashi Tsukamoto and Miaomiao Sun. Their work appears in journals such as Molecular Cancer Therapeutics, Scientific Reports, Oncotarget, Translational Oncology and Cell Biology International.
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.