T Ng

1.3k citations
27 papers · 1.0k · h-index 17

Impact in

Papers in

T Ng

27 papers receiving 1.0k citations

Peers

T Ng
Comparison fields: 5 of 91
  • Endocrinology, Diabetes and Metabolism 234
  • Epidemiology 256
  • Endocrine and Autonomic Systems 46
  • Physiology 160
  • Cardiology and Cardiovascular Medicine 124
Replace Zoran Gluvić with:
Zoran Gluvić Serbia
Kuang‐Chung Shih Taiwan
Gerard T. Chew Australia
Katsuya Yamazaki Japan
Hongyun Yan Canada
Gaia Chiara Mannino Italy
Núbia S. Lobato Brazil
Şehri Elbeğ Türkiye
Yuko Chiba Japan
Weiqiong Gu China
T Ng relative to Zoran Gluvić Serbia Zoran Gluvić's profile →
Citations per field
00.5×3.2×
Zoran Gluvić · 1×
Citations per year

Countries citing papers authored by T Ng

Since Specialization
Citations

This map shows the geographic impact of T Ng'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 T Ng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites T Ng more than expected).

Fields of papers citing papers by T Ng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 27 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2004119
2 2015103
3 200597
4 200587
5 200780
6 201464
7 201753
8 200852
9 201149
10 200647
11 201241
12 201139
13 201335
14 200925
15 201624
16 201524
17 201516
18 201316
19 201214
20 200913

About T Ng

T Ng is a scholar working on Endocrinology, Diabetes and Metabolism, Epidemiology, Surgery, Molecular Biology and Physiology, having authored 27 papers that have together received 1.0k indexed citations. Recurring topics across this work include Diabetes, Cardiovascular Risks, and Lipoproteins (10 papers), Adipokines, Inflammation, and Metabolic Diseases (6 papers), Diet and metabolism studies (3 papers), Fatty Acid Research and Health (3 papers), Peroxisome Proliferator-Activated Receptors (2 papers), Lipid metabolism and biosynthesis (2 papers), Lipoproteins and Cardiovascular Health (2 papers) and Metabolomics and Mass Spectrometry Studies (2 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (234 citations), Epidemiology (256 citations), Endocrine and Autonomic Systems (46 citations), Physiology (160 citations) and Cardiology and Cardiovascular Medicine (124 citations). T Ng has collaborated with scholars based in Australia, Japan and Iran. Frequent co-authors include Gerald F. Watts, P. Hugh R. Barrett, Dick C. Chan, Esther Ooi, Maryam S. Farvid, Peter J. Meikle, Shizuya Yamashita, Kerry‐Anne Rye, Aliki A. Rasmiena and Naohiko Sakai. Their work appears in journals such as Diabetes Obesity and Metabolism, Clinical Science, The Journal of Clinical Endocrinology & Metabolism, Current Opinion in Lipidology and Journal of Lipid 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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