G. William Wong

15.8k citations
132 papers · 6.9k indexed · h-index 49
Topics
Adipose Tissue and Metabolism (56 papers)Adipokines, Inflammation, and Metabolic Diseases (47 papers)Regulation of Appetite and Obesity (21 papers)

In The Last Decade

G. William Wong

128 papers receiving 6.8k citations

Peers

G. William Wong
Comparison fields: 5 of 134
  • Physiology 2.7k
  • Epidemiology 2.6k
  • Molecular Biology 2.3k
  • Immunology 1.2k
  • Cardiology and Cardiovascular Medicine 1.1k
Replace Kaori Sato with:
Kaori Sato Japan
Lawrence Chan United States
Koji Maemura Japan
Shoshana Yakar United States
Ez‐Zoubir Amri France
James C. Lo United States
Narendra N. Tandon United States
Christopher Hug United States
Brant E. Isakson United States
D. Margriet Ouwens Germany
G. William Wong relative to Kaori Sato Japan Kaori Sato's profile →
Citations per field
00.5×1.5×2.4×
Kaori Sato · 1×
Citations per year

Countries citing papers authored by G. William Wong

Since Specialization
Citations

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

Fields of papers citing papers by G. William Wong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by G. William Wong. 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 G. William Wong. The network helps show where G. William Wong may publish in the future.

Co-authorship network of co-authors of G. William Wong

This figure shows the co-authorship network connecting the top 25 collaborators of G. William Wong. A scholar is included among the top collaborators of G. William Wong 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 G. William Wong. G. William Wong 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 1
2 0
3 2
4 6
5 1
6 2
7 4
8 12
9 5
10 12
11 25
12 56
13 30
14 78
15 27
16 77
17 1
18 7
19 369
20 20

About G. William Wong

G. William Wong is a scholar working on Endocrine and Autonomic Systems, Physiology and Epidemiology, having authored 132 papers that have together received 6.9k indexed citations. Recurring topics across this work include Adipose Tissue and Metabolism (56 papers), Adipokines, Inflammation, and Metabolic Diseases (47 papers) and Regulation of Appetite and Obesity (21 papers). The work is most often cited by research in Physiology (2.7k citations), Endocrine and Autonomic Systems (535 citations) and Epidemiology (2.6k citations). G. William Wong has collaborated with scholars based in United States, Australia and Canada. Frequent co-authors include Zhikui Wei, Jonathan M. Peterson, Marcus Seldin, Xia Lei, Richard L Stevens, Harvey F. Lodish, Stefanie Y. Tan, Mardi S. Byerly, Susan Aja and Christopher Hug. Their work appears in journals such as Nature, Proceedings of the National Academy of Sciences and Journal of Biological Chemistry.

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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