Guo-Ping Tian
Impact in
- Cancer Research top 10%
- MicroRNA in disease regulation
- Cancer-related molecular mechanisms research
- Cancer, Lipids, and Metabolism
- Pharmacology top 10%
- Apelin-related biomedical research
Papers in
-
- Peroxisome Proliferator-Activated Receptors 3
- Surgery 7
- Cholesterol and Lipid Metabolism 5
- Co-authors
- Chao‐Ke Tang (9 shared papers)Dawei Zhang (4 shared papers)Shilin Tang (5 shared papers)Pingping He (7 shared papers)Xiao-Hua Yu (2 shared papers)Hong Qian (1 shared paper)Xin-Ping Ouyang (5 shared papers)Li-Jing Liu (1 shared paper)
In The Last Decade
Guo-Ping Tian
23 papers receiving 467 citations
Peers
Comparison fields: 5 of 72
- Cancer Research 194
- Pharmacology 109
- Immunology 86
- Surgery 166
- Cardiology and Cardiovascular Medicine 69
Countries citing papers authored by Guo-Ping Tian
This map shows the geographic impact of Guo-Ping Tian'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 Guo-Ping Tian with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Guo-Ping Tian more than expected).
Fields of papers citing papers by Guo-Ping Tian
This network shows the impact of papers produced by Guo-Ping Tian. 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 Guo-Ping Tian. The network helps show where Guo-Ping Tian may publish in the future.
Co-authors
The 25 scholars most cited alongside Guo-Ping Tian, 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 24 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2013 | 112 | |
| 2 | 2014 | 106 | |
| 3 | 2014 | 49 | |
| 4 | 2012 | 41 | |
| 5 | 2013 | 27 | |
| 6 | 2014 | 23 | |
| 7 | 2017 | 20 | |
| 8 | 2019 | 17 | |
| 9 | 2021 | 16 | |
| 10 | 2021 | 9 | |
| 11 | 2019 | 8 | |
| 12 | 2022 | 8 | |
| 13 | 2012 | 8 | |
| 14 | 2016 | 7 | |
| 15 | [Current progress in lipoprotein lipase and atherosclerosis]. | 2012 | 6 |
| 16 | 2012 | 4 | |
| 17 | 2019 | 4 | |
| 18 | 2021 | 3 | |
| 19 | [Clinical characteristics of cerebral infarction in China and Japan]. | 2004 | 2 |
| 20 | 2019 | 1 |
About Guo-Ping Tian
Guo-Ping Tian is a scholar working on Molecular Biology, Surgery, Cardiology and Cardiovascular Medicine, Cancer Research and Cellular and Molecular Neuroscience, having authored 24 papers that have together received 475 indexed citations. Recurring topics across this work include Cholesterol and Lipid Metabolism (5 papers), MicroRNA in disease regulation (3 papers), Lipid metabolism and disorders (3 papers), Peroxisome Proliferator-Activated Receptors (3 papers), Mesenchymal stem cell research (2 papers), Cancer, Lipids, and Metabolism (2 papers), Cancer-related molecular mechanisms research (2 papers) and Neurological Disease Mechanisms and Treatments (2 papers). The work is most often cited by research in Cancer Research (194 citations), Pharmacology (109 citations), Immunology (86 citations), Surgery (166 citations) and Cardiology and Cardiovascular Medicine (69 citations). Guo-Ping Tian has collaborated with scholars based in China, Canada and Japan. Frequent co-authors include Chao‐Ke Tang, Dawei Zhang, Shilin Tang, Pingping He, Xiao-Hua Yu, Hong Qian, Xin-Ping Ouyang, Li-Jing Liu, Yun-Cheng Lv and Xi‐Long Zheng. Their work appears in journals such as Atherosclerosis, Circulation Journal, Biochemical and Biophysical Research Communications, Clinica Chimica Acta and Gene.
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.