Ding Long
Impact in
- Infectious Diseases top 10%
- COVID-19 Clinical Research Studies
- SARS-CoV-2 and COVID-19 Research
- Neurology top 10%
- Long-Term Effects of COVID-19
Papers in
-
- Sepsis Diagnosis and Treatment 4
-
- Inflammation biomarkers and pathways 2
- Immune Response and Inflammation 2
- Co-authors
- Liangkai Chen (3 shared papers)Zhao Su (3 shared papers)Wenwu Sun (3 shared papers)Li Yu (4 shared papers)Lijuan Zhang (1 shared paper)Yanan Guo (2 shared papers)Xiaoling Wu (2 shared papers)Junhui Yang (2 shared papers)
In The Last Decade
Ding Long
17 papers receiving 357 citations
Peers
Comparison fields: 5 of 69
- Infectious Diseases 225
- Neurology 105
- Internal Medicine 21
- Dermatology 40
- Oncology 82
Countries citing papers authored by Ding Long
This map shows the geographic impact of Ding 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 Ding Long with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ding Long more than expected).
Fields of papers citing papers by Ding Long
This network shows the impact of papers produced by Ding 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 Ding Long. The network helps show where Ding Long may publish in the future.
Co-authors
The 25 scholars most cited alongside Ding 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 | 2020 | 224 | |
| 2 | 2018 | 30 | |
| 3 | 2020 | 28 | |
| 4 | 2021 | 21 | |
| 5 | 2020 | 12 | |
| 6 | 2014 | 8 | |
| 7 | 1977 | 8 | |
| 8 | 2019 | 6 | |
| 9 | 2018 | 6 | |
| 10 | 2013 | 5 | |
| 11 | Urokinase-type plasminogen activator protects human umbilical vein endothelial cells from apoptosis in sepsis. | 2019 | 5 |
| 12 | 2017 | 4 | |
| 13 | 2011 | 4 | |
| 14 | Correlation of plasma suPAR expression with disease risk and severity as well as prognosis of sepsis-induced acute respiratory distress syndrome. | 2017 | 4 |
| 15 | [Dynamic changes in plasma levels of urokinase type plasminogen activator and urokinase type plasminogen activator receptor in patients with systemic inflammatory response syndrome]. | 2011 | 2 |
| 16 | 2019 | 2 | |
| 17 | [Species distribution of pathogens and prognostic factors for catheter-related bloodstream infections in intensive care unit]. | 2015 | 1 |
| 18 | 2024 | 0 | |
| 19 | 2025 | 0 |
About Ding Long
Ding Long is a scholar working on Epidemiology, Immunology, Hematology, Cancer Research and Infectious Diseases, having authored 19 papers that have together received 370 indexed citations. Recurring topics across this work include Sepsis Diagnosis and Treatment (4 papers), COVID-19 Clinical Research Studies (3 papers), Blood Coagulation and Thrombosis Mechanisms (3 papers), Inflammation biomarkers and pathways (2 papers), Central Venous Catheters and Hemodialysis (2 papers), Immune Response and Inflammation (2 papers), Venous Thromboembolism Diagnosis and Management (2 papers) and Protease and Inhibitor Mechanisms (2 papers). The work is most often cited by research in Infectious Diseases (225 citations), Neurology (105 citations), Internal Medicine (21 citations), Dermatology (40 citations) and Oncology (82 citations). Ding Long has collaborated with scholars based in China, Israel and Hong Kong. Frequent co-authors include Liangkai Chen, Zhao Su, Wenwu Sun, Li Yu, Lijuan Zhang, Yanan Guo, Xiaoling Wu, Junhui Yang, Yanli Liu and Xiaoling Wu. Their work appears in journals such as Journal of Cellular Biochemistry, Gene, Medicine, Toxicology and Pancreas.
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.