Yan Lü
Impact in
- Nephrology top 2%
- Parathyroid Disorders and Treatments
- Hepatology top 5%
Papers in ⓘ
-
- Metabolism, Diabetes, and Cancer 9
- Epidemiology 30
- Liver Disease Diagnosis and Treatment 21
- Co-authors
- Huijie Zhang (11 shared papers)Eduardo Slatopolsky (6 shared papers)Xuelian Xiong (9 shared papers)Xin Gao (4 shared papers)Adriana Dusso (4 shared papers)Xiaopeng Zhu (3 shared papers)Min Li (1 shared paper)Xi Xu (3 shared papers)
- Journals
- Hepatology (3 papers)Journal of Clinical Investigation (3 papers)Journal of Hepatology (3 papers)Molecular Metabolism (3 papers)Diabetes (2 papers)
- Partner nations
- ChinaUnited StatesItaly
In The Last Decade
Yan Lü
109 papers receiving 3.5k citations
Peers
Comparison fields: 5 of 125
- Nephrology 338
- Hepatology 217
- Cancer Research 408
- Epidemiology 920
- Biological Psychiatry 66
Countries citing papers authored by Yan Lü
This map shows the geographic impact of Yan Lü'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 Lü with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yan Lü more than expected).
Fields of papers citing papers by Yan Lü
This network shows the impact of papers produced by Yan Lü. 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 Lü. The network helps show where Yan Lü may publish in the future.
Co-authors
The 25 scholars most cited alongside Yan Lü, 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 116 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 226 | |
| 2 | 2019 | 197 | |
| 3 | 2013 | 196 | |
| 4 | 2016 | 128 | |
| 5 | 2014 | 121 | |
| 6 | 2001 | 113 | |
| 7 | 2016 | 112 | |
| 8 | 2014 | 111 | |
| 9 | 2019 | 86 | |
| 10 | 2002 | 86 | |
| 11 | 2018 | 86 | |
| 12 | 2018 | 85 | |
| 13 | 2001 | 78 | |
| 14 | 2019 | 76 | |
| 15 | 2021 | 71 | |
| 16 | 2021 | 69 | |
| 17 | 2017 | 68 | |
| 18 | 2019 | 67 | |
| 19 | 2018 | 59 | |
| 20 | 2021 | 54 |
About Yan Lü
Yan Lü is a scholar working on Molecular Biology, Epidemiology, Endocrinology, Diabetes and Metabolism, Surgery and Physiology, having authored 116 papers that have together received 3.5k indexed citations. Recurring topics across this work include Liver Disease Diagnosis and Treatment (21 papers), Metabolism, Diabetes, and Cancer (9 papers), Adipose Tissue and Metabolism (9 papers), Diet, Metabolism, and Disease (8 papers), Endoplasmic Reticulum Stress and Disease (7 papers), Neurological Disease Mechanisms and Treatments (7 papers), Parathyroid Disorders and Treatments (7 papers) and Pancreatic function and diabetes (6 papers). The work is most often cited by research in Nephrology (338 citations), Hepatology (217 citations), Cancer Research (408 citations), Epidemiology (920 citations) and Biological Psychiatry (66 citations). Yan Lü has collaborated with scholars based in China, United States and Italy. Frequent co-authors include Huijie Zhang, Eduardo Slatopolsky, Xuelian Xiong, Xin Gao, Adriana Dusso, Xiaopeng Zhu, Min Li, Xi Xu, Mark D. Markel and Brian J. Cole. Their work appears in journals such as Hepatology, Journal of Clinical Investigation, Journal of Hepatology, Molecular Metabolism and Diabetes.
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.