Shao-kui Wei

773 citations
15 papers · 634 · h-index 12

Impact in

Papers in

Shao-kui Wei

15 papers receiving 622 citations

Peers

Shao-kui Wei
Comparison fields: 5 of 68
  • Cardiology and Cardiovascular Medicine 423
  • Cellular and Molecular Neuroscience 176
  • Molecular Biology 408
  • Sensory Systems 16
  • Nutrition and Dietetics 43
Replace Hajime Terada with:
Hajime Terada Japan
Iva Dostanic United States
Yoshizumi Habuchi Japan
Sven Zumhagen Germany
Hitoshi Oonuma Japan
Hai‐Lei Zhu Canada
B Chevalier France
Ming Tao Jiang United States
Junzhi Ji Canada
P. Y. Hatt France
Shao-kui Wei relative to Hajime Terada Japan Hajime Terada's profile →
Citations per field
00.5×
Hajime Terada · 1×
Citations per year

Countries citing papers authored by Shao-kui Wei

Since Specialization
Citations

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

Fields of papers citing papers by Shao-kui Wei

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Shao-kui Wei. 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 Shao-kui Wei. The network helps show where Shao-kui Wei may publish in the future.

Co-authors

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

All Works

15 of 15 papers shown
#Work
1 2004113
2 1998105
3 199776
4 200074
5 200369
6 199845
7 199743
8 200222
9 200720
10 200719
11 200717
12 200214
13 20118
14 20217
15 20022

About Shao-kui Wei

Shao-kui Wei is a scholar working on Molecular Biology, Cardiology and Cardiovascular Medicine, Cellular and Molecular Neuroscience, Pathology and Forensic Medicine and Pediatrics, Perinatology and Child Health, having authored 15 papers that have together received 634 indexed citations. Recurring topics across this work include Cardiac electrophysiology and arrhythmias (11 papers), Ion channel regulation and function (10 papers), Neuroscience and Neural Engineering (4 papers), Heart Failure Treatment and Management (3 papers), Cardiac pacing and defibrillation studies (2 papers), Neuroscience and Neuropharmacology Research (2 papers), Pharmacovigilance and Adverse Drug Reactions (1 paper) and Pharmaceutical Practices and Patient Outcomes (1 paper). The work is most often cited by research in Cardiology and Cardiovascular Medicine (423 citations), Cellular and Molecular Neuroscience (176 citations), Molecular Biology (408 citations), Sensory Systems (16 citations) and Nutrition and Dietetics (43 citations). Shao-kui Wei has collaborated with scholars based in United States and United Kingdom. Frequent co-authors include Mark C. Haigney, David T. Yue, Stephen U. Hanlon, Howard S. Silverman, Christopher Ocampo, Michael D. Stern, Erich F. Wedam, A. Ruknudin, Dan H. Schulze and Elinor J. Griffiths. Their work appears in journals such as Circulation Research, Annals of the New York Academy of Sciences, Journal of the American College of Cardiology, Cell Calcium and Cardiovascular Research.

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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