Gerard Wong

40 papers receiving 2.7k citations

Peers

Gerard Wong
Comparison fields: 5 of 125
  • Biochemistry 159
  • Physiology 524
  • Molecular Biology 1.3k
  • Endocrinology, Diabetes and Metabolism 255
  • Obstetrics and Gynecology 104
Replace Jacquelyn M. Weir with:
Jacquelyn M. Weir Australia
Anahita Ghorbani United States
Isobel D. Stewart United Kingdom
Hans‐Ulrich Häring Germany
Roger Gaedigk United States
Johannes Raffler Germany
Ville‐Petteri Mäkinen Finland
Philippe Lettéron France
Henna Cederberg Finland
Gerard Wong relative to Jacquelyn M. Weir Australia Jacquelyn M. Weir's profile →
Citations per field
00.5×2×2.5×
Jacquelyn M. Weir · 1×
Citations per year

Countries citing papers authored by Gerard Wong

Since Specialization
Citations

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

Fields of papers citing papers by Gerard Wong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 41 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2013321
2 2019282
3 2011274
4 2013257
5 2016213
6 2014158
7 2011149
8 2018126
9 201573
10 201370
11 201367
12 201559
13 201759
14 201558
15 201356
16 201556
17 202052
18 201450
19 201649
20 201539

About Gerard Wong

Gerard Wong is a scholar working on Obstetrics and Gynecology, Endocrinology, Diabetes and Metabolism, Molecular Biology, Pediatrics, Perinatology and Child Health and Public Health, Environmental and Occupational Health, having authored 41 papers that have together received 2.8k indexed citations. Recurring topics across this work include Metabolomics and Mass Spectrometry Studies (9 papers), Diabetes, Cardiovascular Risks, and Lipoproteins (5 papers), Gestational Diabetes Research and Management (4 papers), Lipoproteins and Cardiovascular Health (3 papers), Birth, Development, and Health (3 papers), Sphingolipid Metabolism and Signaling (3 papers), Lipid metabolism and disorders (2 papers) and Nutritional Studies and Diet (2 papers). The work is most often cited by research in Biochemistry (159 citations), Physiology (524 citations), Molecular Biology (1.3k citations), Endocrinology, Diabetes and Metabolism (255 citations) and Obstetrics and Gynecology (104 citations). Gerard Wong has collaborated with scholars based in Australia, Singapore and United States. Frequent co-authors include Peter J. Meikle, Christopher K. Barlow, Jacquelyn M. Weir, Bronwyn A. Kingwell, Adam Kowalczyk, Jonathan Edward Shaw, John Blangero, Joanne E. Curran, Michael C. Mahaney and Anthony Gean Comuzzie. Their work appears in journals such as PLoS ONE, Bioinformatics, Atherosclerosis, Arteriosclerosis Thrombosis and Vascular Biology and JCI Insight.

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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