WU Guo-ting

423 citations
7 papers · 307 · h-index 5

Impact in

Papers in

WU Guo-ting

6 papers receiving 296 citations

Peers

WU Guo-ting
Comparison fields: 5 of 68
  • Endocrinology, Diabetes and Metabolism 208
  • Molecular Biology 165
  • Aging 4
  • Pharmacology 38
  • Cardiology and Cardiovascular Medicine 43
Replace Wang Dawang with:
Wang Dawang China
Rengna Yan China
Renate E. van Genugten Netherlands
Tetsuyuki Yasuda Japan
Hyo Jin Maeng South Korea
Guoyu Tong China
Surya Panicker Rajeev United Kingdom
Masahiko Miyagi Japan
Junpei Sanada Japan
Xiaoxuan Ma China
WU Guo-ting relative to Wang Dawang China Wang Dawang's profile →
Citations per field
00.5×1.5×
Wang Dawang · 1×
Citations per year

Countries citing papers authored by WU Guo-ting

Since Specialization
Citations

This map shows the geographic impact of WU Guo-ting'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 WU Guo-ting with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites WU Guo-ting more than expected).

Fields of papers citing papers by WU Guo-ting

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by WU Guo-ting. 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 WU Guo-ting. The network helps show where WU Guo-ting may publish in the future.

Co-authors

The 25 scholars most cited alongside WU Guo-ting, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with WU Guo-ting Line = papers co-authored together WU Guo-ting links everyone, so they are left out of the graph.

All Works

7 of 7 papers shown
#Work
1 2012277
2
Effects of glibenclamide, glimepiride, and gliclazide on ischemic preconditioning in rat heart.
200710
3
[Study on the relationship between polymorphisms of peroxisome proliferators-activated receptor-gamma coactivator-1alpha gene and type 2 diabetes in Shanghai Hans in China].
20058
4 20095
5 20164
6 20092
7 20211

About WU Guo-ting

WU Guo-ting is a scholar working on Molecular Biology, Endocrinology, Diabetes and Metabolism, Surgery, Pathology and Forensic Medicine and Cellular and Molecular Neuroscience, having authored 7 papers that have together received 307 indexed citations. Recurring topics across this work include Metabolism, Diabetes, and Cancer (2 papers), Diabetes Treatment and Management (2 papers), Peroxisome Proliferator-Activated Receptors (2 papers), Pancreatic function and diabetes (1 paper), Diabetes, Cardiovascular Risks, and Lipoproteins (1 paper), Bone health and osteoporosis research (1 paper), Diabetes Management and Research (1 paper) and Cancer, Hypoxia, and Metabolism (1 paper). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (208 citations), Molecular Biology (165 citations), Aging (4 citations), Pharmacology (38 citations) and Cardiology and Cardiovascular Medicine (43 citations). WU Guo-ting has collaborated with scholars based in China and United States. Frequent co-authors include Qing Su, Weiqing Wang, Dong Yan, Yifei Zhang, Hong Li, Weili Tang, Shenghan Lai, Weifeng Shen, Wang Dawang and Jie Hong. Their work appears in journals such as Journal of Bone and Mineral Metabolism, Diabetes Care, Diabetes Research and Clinical Practice, Scientia Sinica Technologica and PubMed.

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.

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