Lie Dai
Impact in
- Rheumatology top 1%
- Rheumatoid Arthritis Research and Therapies
- Osteoarthritis Treatment and Mechanisms
- Systemic Lupus Erythematosus Research
- Nephrology top 5%
- Gout, Hyperuricemia, Uric Acid
Papers in
- Rheumatology 47
- Rheumatoid Arthritis Research and Therapies 30
- Systemic Lupus Erythematosus Research 10
- Spondyloarthritis Studies and Treatments 5
- Epidemiology 15
- Hepatitis B Virus Studies 9
- Co-authors
- Ying‐Qian Mo (51 shared papers)Jian‐Da Ma (38 shared papers)Dong-Hui Zheng (25 shared papers)Le‐Feng Chen (21 shared papers)Jun Jing (16 shared papers)H. Ralph Schumacher (12 shared papers)Frank Peßler (12 shared papers)Cèsar Díaz‐Torné (6 shared papers)
- Journals
- Annals of the Rheumatic Diseases (18 papers)Clinical Rheumatology (8 papers)Arthritis Research & Therapy (8 papers)The Journal of Rheumatology (3 papers)Frontiers in Immunology (3 papers)
- Partner nations
- ChinaUnited StatesGermany
In The Last Decade
Lie Dai
105 papers receiving 1.5k citations
Peers
Comparison fields: 5 of 93
- Rheumatology 541
- Nephrology 135
- Microbiology 10
- Hepatology 67
- Hematology 90
Countries citing papers authored by Lie Dai
This map shows the geographic impact of Lie Dai'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 Lie Dai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lie Dai more than expected).
Fields of papers citing papers by Lie Dai
This network shows the impact of papers produced by Lie Dai. 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 Lie Dai. The network helps show where Lie Dai may publish in the future.
Co-authors
The 25 scholars most cited alongside Lie Dai, 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 114 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 116 | |
| 2 | 2008 | 88 | |
| 3 | 2017 | 85 | |
| 4 | 2014 | 69 | |
| 5 | 2008 | 68 | |
| 6 | 2013 | 62 | |
| 7 | 2019 | 59 | |
| 8 | 2015 | 46 | |
| 9 | 2005 | 40 | |
| 10 | 2007 | 39 | |
| 11 | 2008 | 39 | |
| 12 | 2019 | 39 | |
| 13 | 2020 | 36 | |
| 14 | 2015 | 35 | |
| 15 | 2014 | 33 | |
| 16 | 2013 | 29 | |
| 17 | 2019 | 25 | |
| 18 | 2022 | 24 | |
| 19 | 2022 | 22 | |
| 20 | 2014 | 21 |
About Lie Dai
Lie Dai is a scholar working on Rheumatology, Epidemiology, Nephrology, Immunology and Molecular Biology, having authored 114 papers that have together received 1.5k indexed citations. Recurring topics across this work include Rheumatoid Arthritis Research and Therapies (30 papers), Systemic Lupus Erythematosus Research (10 papers), Hepatitis B Virus Studies (9 papers), Gout, Hyperuricemia, Uric Acid (9 papers), Hepatitis C virus research (6 papers), Immunodeficiency and Autoimmune Disorders (5 papers), Spondyloarthritis Studies and Treatments (5 papers) and Nutrition and Health in Aging (4 papers). The work is most often cited by research in Rheumatology (541 citations), Nephrology (135 citations), Microbiology (10 citations), Hepatology (67 citations) and Hematology (90 citations). Lie Dai has collaborated with scholars based in China, United States and Germany. Frequent co-authors include Ying‐Qian Mo, Jian‐Da Ma, Dong-Hui Zheng, Le‐Feng Chen, Jun Jing, H. Ralph Schumacher, Frank Peßler, Cèsar Díaz‐Torné, Qianhua Li and Eugene Einhorn. Their work appears in journals such as Annals of the Rheumatic Diseases, Clinical Rheumatology, Arthritis Research & Therapy, The Journal of Rheumatology and Frontiers in Immunology.
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.