Norman C.W. Wong
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- Growth Hormone and Insulin-like Growth Factors 13
- Diabetes, Cardiovascular Risks, and Lipoproteins 11
- Molecular Biology top 2%
- Protein Degradation and Inhibitors 33
- Peroxisome Proliferator-Activated Receptors 18
- Metabolism, Diabetes, and Cancer 14
- Genetics top 2%
- Hematology top 2%
- Cancer Research top 5%
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- Cholesterol and Lipid Metabolism 18
- Lipoproteins and Cardiovascular Health 16
- Pancreatic function and diabetes 14
- Co-authors
- Arshag D. MooradianMichael J. HaasDaniel A. MuruveGordon H. DixonEwelina KulikowskiJack H. OppenheimerKoji MuraoHarold L. Schwartz
- Partner nations
- CanadaUnited StatesJapan
In The Last Decade
Norman C.W. Wong
142 papers receiving 5.3k citations
Peers
Comparison fields: 5 of 135
- Endocrinology, Diabetes and Metabolism 1.4k
- Molecular Biology 2.9k
- Genetics 1.1k
- Hematology 399
- Cancer Research 511
Countries citing papers authored by Norman C.W. Wong
This map shows the geographic impact of Norman C.W. 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 Norman C.W. Wong with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Norman C.W. Wong more than expected).
Fields of papers citing papers by Norman C.W. Wong
This network shows the impact of papers produced by Norman C.W. 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 Norman C.W. Wong. The network helps show where Norman C.W. Wong may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Norman C.W. Wong, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 21 | |
| 2 | 2021 | 56 | |
| 3 | Abstract 671: Hepatic Expression of C-Reactive Protein is Epigenetically Regulated by BET Proteins and Inhibited by Apabetalone (RVX-208) in vitro and in CVD Patients | 2019 | 1 |
| 4 | 2019 | 1 | |
| 5 | 2018 | 7 | |
| 6 | 2017 | 48 | |
| 7 | 2016 | 15 | |
| 8 | 2014 | 4 | |
| 9 | 2014 | 2 | |
| 10 | 2013 | 11 | |
| 11 | 2013 | 26 | |
| 12 | 2012 | 14 | |
| 13 | 2012 | 10 | |
| 14 | 2010 | 181 | |
| 15 | 2006 | 20 | |
| 16 | 2004 | 7 | |
| 17 | 2002 | 52 | |
| 18 | 2001 | 25 | |
| 19 | 1991 | 22 | |
| 20 | 1991 | 21 |
About Norman C.W. Wong
Norman C.W. Wong is a scholar working on Endocrinology, Diabetes and Metabolism, Molecular Biology and Virology, having authored 144 papers that have together received 5.5k indexed citations. Recurring topics across this work include Protein Degradation and Inhibitors (33 papers), Cholesterol and Lipid Metabolism (18 papers), Peroxisome Proliferator-Activated Receptors (18 papers), Lipoproteins and Cardiovascular Health (16 papers), Metabolism, Diabetes, and Cancer (14 papers), Pancreatic function and diabetes (14 papers), Growth Hormone and Insulin-like Growth Factors (13 papers) and Diabetes, Cardiovascular Risks, and Lipoproteins (11 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (1.4k citations), Molecular Biology (2.9k citations) and Genetics (1.1k citations). Norman C.W. Wong has collaborated with scholars based in Canada, United States and Japan. Frequent co-authors include Arshag D. Mooradian, Michael J. Haas, Daniel A. Muruve, Gordon H. Dixon, Ewelina Kulikowski, Jack H. Oppenheimer, Koji Murao, Harold L. Schwartz, Michael Sweeney and Hitomi Imachi. Their work appears in journals such as Journal of Biological Chemistry, Atherosclerosis, Metabolism, Journal of the American College of Cardiology and Endocrinology.
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.