Ding Long
Impact in
- Infectious Diseases top 10%
- COVID-19 Clinical Research Studies
- SARS-CoV-2 and COVID-19 Research
-
- Long-Term Effects of COVID-19
Papers in
-
- Protease and Inhibitor Mechanisms 2
- MicroRNA in disease regulation 1
-
- Immune Response and Inflammation 2
- Inflammation biomarkers and pathways 2
- Complement system in diseases 1
- Biomarkers in Disease Mechanisms 1
- Co-authors
- Liangkai Chen (3 shared papers)Wenwu Sun (3 shared papers)Li Yu (4 shared papers)Zhao Su (3 shared papers)Yanan Guo (2 shared papers)Lijuan Zhang (1 shared paper)Junhui Yang (2 shared papers)Xiaoling Wu (2 shared papers)
In The Last Decade
Ding Long
15 papers receiving 377 citations
Ding Long's Hit Papers
Peers
Comparison fields: 5 of 62
- Infectious Diseases 189
- Neurology 82
- Internal Medicine 16
- Dermatology 34
- Hematology 30
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 | Association between platelet parameters and mortality in coronavirus disease 2019: Retrospective cohort study Hit paper breakdown → | 2020 | 238 |
| 2 | 2018 | 31 | |
| 3 | 2020 | 30 | |
| 4 | 2021 | 23 | |
| 5 | 2020 | 12 | |
| 6 | 2014 | 10 | |
| 7 | 2018 | 8 | |
| 8 | 2019 | 6 | |
| 9 | 2013 | 6 | |
| 10 | Urokinase-type plasminogen activator protects human umbilical vein endothelial cells from apoptosis in sepsis. | 2019 | 5 |
| 11 | Correlation of plasma suPAR expression with disease risk and severity as well as prognosis of sepsis-induced acute respiratory distress syndrome. | 2017 | 4 |
| 12 | 2011 | 4 | |
| 13 | 2017 | 4 | |
| 14 | 2019 | 3 | |
| 15 | [Species distribution of pathogens and prognostic factors for catheter-related bloodstream infections in intensive care unit]. | 2015 | 1 |
| 16 | 2024 | 0 | |
| 17 | 2025 | 0 |
About Ding Long
Ding Long is a scholar working on Cancer Research, Immunology, Epidemiology, Internal Medicine and Pulmonary and Respiratory Medicine, having authored 17 papers that have together received 385 indexed citations. Recurring topics across this work include Sepsis Diagnosis and Treatment (3 papers), Protease and Inhibitor Mechanisms (2 papers), Immune Response and Inflammation (2 papers), Inflammation biomarkers and pathways (2 papers), MicroRNA in disease regulation (1 paper), Venous Thromboembolism Diagnosis and Management (1 paper), Complement system in diseases (1 paper) and Biomarkers in Disease Mechanisms (1 paper). The work is most often cited by research in Infectious Diseases (189 citations), Neurology (82 citations), Internal Medicine (16 citations), Dermatology (34 citations) and Hematology (30 citations). Ding Long has collaborated with scholars based in China and Hong Kong. Frequent co-authors include Liangkai Chen, Wenwu Sun, Li Yu, Zhao Su, Yanan Guo, Lijuan Zhang, Junhui Yang, Xiaoling Wu, Yanli Liu and Xiaoling Wu. Their work appears in journals such as Medicine, Gene, Diabetes Care, BMC Cardiovascular Disorders and Stroke.
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.