Li Che
Impact in
- Cancer Research top 2%
- Cancer, Hypoxia, and Metabolism
- Cancer, Lipids, and Metabolism
- MicroRNA in disease regulation
- Cancer-related molecular mechanisms research
- Hepatology top 5%
Papers in
-
- Cancer-related gene regulation 8
- PI3K/AKT/mTOR signaling in cancer 8
- Peroxisome Proliferator-Activated Receptors 7
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- Cancer, Lipids, and Metabolism 10
- Cancer, Hypoxia, and Metabolism 8
- Co-authors
- Xin Chen (34 shared papers)Diego F. Calvisi (37 shared papers)Antonio Cigliano (26 shared papers)Silvia Ribback (23 shared papers)Matthias Evert (19 shared papers)Frank Dombrowski (15 shared papers)Xinhua Song (18 shared papers)Maria G. Pilo (10 shared papers)
- Journals
- Hepatology (7 papers)Journal of Hepatology (4 papers)American Journal Of Pathology (4 papers)Clinical & Translational Oncology (3 papers)Cell Death and Disease (3 papers)
- Partner nations
- ChinaUnited StatesGermany
In The Last Decade
Li Che
72 papers receiving 1.9k citations
Peers
Comparison fields: 5 of 129
- Cancer Research 746
- Hepatology 246
- Molecular Biology 1.1k
- Cell Biology 229
- Oncology 370
Countries citing papers authored by Li Che
This map shows the geographic impact of Li Che'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 Li Che with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Li Che more than expected).
Fields of papers citing papers by Li Che
This network shows the impact of papers produced by Li Che. 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 Li Che. The network helps show where Li Che may publish in the future.
Co-authors
The 25 scholars most cited alongside Li Che, 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 74 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2015 | 119 | |
| 2 | 2016 | 103 | |
| 3 | 2016 | 87 | |
| 4 | 2014 | 84 | |
| 5 | 2019 | 82 | |
| 6 | 2018 | 77 | |
| 7 | 2020 | 75 | |
| 8 | 2021 | 68 | |
| 9 | 2017 | 67 | |
| 10 | 2017 | 64 | |
| 11 | 2016 | 60 | |
| 12 | 2019 | 54 | |
| 13 | 2016 | 53 | |
| 14 | 2019 | 47 | |
| 15 | 2017 | 47 | |
| 16 | 2009 | 44 | |
| 17 | 2013 | 44 | |
| 18 | 2012 | 40 | |
| 19 | 2019 | 40 | |
| 20 | 2012 | 35 |
About Li Che
Li Che is a scholar working on Molecular Biology, Cancer Research, Oncology, Surgery and Pathology and Forensic Medicine, having authored 74 papers that have together received 1.9k indexed citations. Recurring topics across this work include Cancer, Lipids, and Metabolism (10 papers), Cancer Mechanisms and Therapy (10 papers), Cancer-related gene regulation (8 papers), PI3K/AKT/mTOR signaling in cancer (8 papers), Cancer, Hypoxia, and Metabolism (8 papers), Liver physiology and pathology (7 papers), Peroxisome Proliferator-Activated Receptors (7 papers) and Cholangiocarcinoma and Gallbladder Cancer Studies (7 papers). The work is most often cited by research in Cancer Research (746 citations), Hepatology (246 citations), Molecular Biology (1.1k citations), Cell Biology (229 citations) and Oncology (370 citations). Li Che has collaborated with scholars based in China, United States and Germany. Frequent co-authors include Xin Chen, Diego F. Calvisi, Antonio Cigliano, Silvia Ribback, Matthias Evert, Frank Dombrowski, Xinhua Song, Maria G. Pilo, Jingxiao Wang and Zhong Xu. Their work appears in journals such as Hepatology, Journal of Hepatology, American Journal Of Pathology, Clinical & Translational Oncology and Cell Death and Disease.
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.