Wangde Dai

80 papers receiving 2.2k citations

Peers

Wangde Dai
Comparison fields: 5 of 114
  • Genetics 528
  • Biomaterials 476
  • Surgery 860
  • Pathology and Forensic Medicine 334
  • Cardiology and Cardiovascular Medicine 418
Replace Joan Dow with:
Joan Dow United States
Aaron M. Abarbanell United States
Oliver Dewald Germany
Santosh K. Sanganalmath United States
Muhammad Mudassar Ashraf United States
Arnd Schaefer Germany
Elias A. Zias United States
Luis G. Melo Canada
Kevin Morine United States
Jitka A. I. Virag United States
Wangde Dai relative to Joan Dow United States Joan Dow's profile →
Citations per field
00.5×2×3×4×4.7×
Joan Dow · 1×
Citations per year

Countries citing papers authored by Wangde Dai

Since Specialization
Citations

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

Fields of papers citing papers by Wangde Dai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Wangde Dai. 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 Wangde Dai. The network helps show where Wangde Dai may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 81 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2005473
2 2005224
3 2012134
4 2007123
5 201478
6 200673
7 200973
8 201469
9 201767
10 201556
11 200847
12 201232
13 202030
14 201729
15 201428
16 200328
17 200527
18 200927
19 201326
20 201624

About Wangde Dai

Wangde Dai is a scholar working on Pathology and Forensic Medicine, Cardiology and Cardiovascular Medicine, Emergency Medicine, Genetics and Surgery, having authored 81 papers that have together received 2.2k indexed citations. Recurring topics across this work include Cardiac Ischemia and Reperfusion (20 papers), Tissue Engineering and Regenerative Medicine (12 papers), Cardiac Arrest and Resuscitation (11 papers), Mesenchymal stem cell research (11 papers), Electrospun Nanofibers in Biomedical Applications (8 papers), Cardiovascular Function and Risk Factors (7 papers), Smoking Behavior and Cessation (7 papers) and Pluripotent Stem Cells Research (5 papers). The work is most often cited by research in Genetics (528 citations), Biomaterials (476 citations), Surgery (860 citations), Pathology and Forensic Medicine (334 citations) and Cardiology and Cardiovascular Medicine (418 citations). Wangde Dai has collaborated with scholars based in United States, France and Czechia. Frequent co-authors include Robert Alan Kloner, Sharon L. Hale, Joan Dow, Loren E. Wold, Bradley J. Martin, Jin-Qiang Kuang, Jianru Shi, Loren E. Wold, Gregory Louis Kay and Aarne J. Jyrala. Their work appears in journals such as Journal of Cardiovascular Pharmacology and Therapeutics, Journal of the American Heart Association, Journal of the American College of Cardiology, Cardiovascular Drugs and Therapy and Life Sciences.

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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