Jia‐Ping Wu

28 papers receiving 551 citations

Peers

Jia‐Ping Wu
Comparison fields: 5 of 75
  • Cancer Research 90
  • Geriatrics and Gerontology 13
  • Molecular Biology 280
  • Microbiology 20
  • Immunology 63
Replace Huilan Wang with:
Huilan Wang China
Myoung Seok Ko South Korea
Tomoko Kumagai Japan
Yuqing Wu Germany
Ming He China
Tze-Tze Liu Taiwan
Qinghang Meng United States
Srinivasa Prasad Kolapalli India
Senthil S. Saravanamuthu United States
Jia‐Ping Wu relative to Huilan Wang China Huilan Wang's profile →
Citations per field
00.5×1.5×2.2×
Huilan Wang · 1×
Citations per year

Countries citing papers authored by Jia‐Ping Wu

Since Specialization
Citations

This map shows the geographic impact of Jia‐Ping Wu'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 Jia‐Ping Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jia‐Ping Wu more than expected).

Fields of papers citing papers by Jia‐Ping Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jia‐Ping Wu. 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 Jia‐Ping Wu. The network helps show where Jia‐Ping Wu may publish in the future.

Co-authors

The 25 scholars most cited alongside Jia‐Ping Wu, 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 Jia‐Ping Wu Line = papers co-authored together Jia‐Ping Wu links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 29 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2008103
2 200386
3 200962
4 200448
5 200442
6 200528
7 201419
8 202019
9 201419
10 201118
11 200615
12 201515
13 201015
14 201212
15
Response gene to complement 32 (RGC-32) in endothelial cells is induced by glucose and helpful to maintain glucose homeostasis.
20149
16 20148
17 20147
18 20127
19
Secondhand Smoke Exposure in Aging-related Cardiac Disease.
20136
20 20195

About Jia‐Ping Wu

Jia‐Ping Wu is a scholar working on Molecular Biology, Physiology, Cancer Research, Cardiology and Cardiovascular Medicine and Endocrinology, Diabetes and Metabolism, having authored 29 papers that have together received 561 indexed citations. Recurring topics across this work include Adipose Tissue and Metabolism (4 papers), Cancer, Hypoxia, and Metabolism (4 papers), Angiogenesis and VEGF in Cancer (3 papers), Liver Disease Diagnosis and Treatment (2 papers), Advanced Glycation End Products research (2 papers), Receptor Mechanisms and Signaling (2 papers), Sirtuins and Resveratrol in Medicine (2 papers) and Muscle Physiology and Disorders (2 papers). The work is most often cited by research in Cancer Research (90 citations), Geriatrics and Gerontology (13 citations), Molecular Biology (280 citations), Microbiology (20 citations) and Immunology (63 citations). Jia‐Ping Wu has collaborated with scholars based in United States, Taiwan and China. Frequent co-authors include Roger J. Laham, Guifu Wu, Jue‐Lon Shie, Frank W. Sellke, Xiaojin An, Yi Jin, Yuan Cheng, Thomas M. Roberts, Sergei Boichuk and Ole Gjoerup. Their work appears in journals such as Journal of Biological Chemistry, American Journal of Physiology-Heart and Circulatory Physiology, BMC Cardiovascular Disorders, The FASEB Journal and PLoS ONE.

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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