Gengshu Wu

854 citations
22 papers · 671 indexed · h-index 17
Topics
Lipid metabolism and disorders (9 papers)Diabetes, Cardiovascular Risks, and Lipoproteins (6 papers)Growth Hormone and Insulin-like Growth Factors (4 papers)

In The Last Decade

Gengshu Wu

21 papers receiving 657 citations

Peers

Gengshu Wu
Comparison fields: 5 of 76
  • Molecular Biology 315
  • Cardiology and Cardiovascular Medicine 201
  • Endocrinology, Diabetes and Metabolism 188
  • Physiology 92
  • Biochemistry 87
Replace Yumiko Nakagawa-Toyama with:
Yumiko Nakagawa-Toyama Japan
Leighton R. James United States
Sandra A. Schreyer Sweden
Laura Blinderman United States
Tetsu Ebara Japan
Angelika Freudenthaler Austria
Shogo Kurebayashi Japan
Curtis C. Hughey United States
Mathilde Di Filippo France
John A. Krawiec United States
Gengshu Wu relative to Yumiko Nakagawa-Toyama Japan Yumiko Nakagawa-Toyama's profile →
Citations per field
00.5×1.5×2.3×
Yumiko Nakagawa-Toyama · 1×
Citations per year

Countries citing papers authored by Gengshu Wu

Since Specialization
Citations

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

Fields of papers citing papers by Gengshu Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Gengshu Wu

This figure shows the co-authorship network connecting the top 25 collaborators of Gengshu Wu. A scholar is included among the top collaborators of Gengshu Wu based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Gengshu Wu. Gengshu Wu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 23
2 23
3 29
4 24
5 35
6 43
7 15
8 39
9 78
10 27
11 15
12 3
13 56
14 37
15 21
16 55
17 23
18 37
19 67
20 19

About Gengshu Wu

Gengshu Wu is a scholar working on Endocrinology, Diabetes and Metabolism, Biochemistry and Cardiology and Cardiovascular Medicine, having authored 22 papers that have together received 671 indexed citations. Recurring topics across this work include Lipid metabolism and disorders (9 papers), Diabetes, Cardiovascular Risks, and Lipoproteins (6 papers) and Growth Hormone and Insulin-like Growth Factors (4 papers). The work is most often cited by research in Biochemistry (87 citations), Endocrinology, Diabetes and Metabolism (188 citations) and Cardiology and Cardiovascular Medicine (201 citations). Gengshu Wu has collaborated with scholars based in Canada, Sweden and United States. Frequent co-authors include Dennis E. Vance, Thomas Olivecrona, Gunilla Olivecrona, Stephen G. Young, Chieko Aoyama, Aivar Lõokene, Liyan Zhang, Toralph Ruge, Martin O. Bergö and Gregory A. Cox. Their work appears in journals such as Journal of Biological Chemistry, PLoS ONE and The FASEB Journal.

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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