Ming Ming Teh

886 citations
32 papers · 641 · h-index 12

Impact in

Papers in

Ming Ming Teh

28 papers receiving 624 citations

Peers

Ming Ming Teh
Comparison fields: 5 of 93
  • Endocrinology, Diabetes and Metabolism 96
  • Cancer Research 68
  • Health, Toxicology and Mutagenesis 51
  • Molecular Biology 215
  • Biochemistry 16
Replace Chan-Jung Liang with:
Chan-Jung Liang Taiwan
Mona Abdel Rahim Egypt
Αnila Duni Greece
Tingting Ye China
Kai Liang China
Shahnaz Ahmad Mir India
Heidar Tayebinia Iran
Ana Rosa Cunha Brazil
Yifei Le China
Chenxu Ge China
Ming Ming Teh relative to Chan-Jung Liang Taiwan Chan-Jung Liang's profile →
Citations per field
00.5×1.5×1.8×
Chan-Jung Liang · 1×
Citations per year

Countries citing papers authored by Ming Ming Teh

Since Specialization
Citations

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

Fields of papers citing papers by Ming Ming Teh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 32 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Dietary isothiocyanates, glutathione S-transferase -M1, -T1 polymorphisms and lung cancer risk among Chinese women in Singapore.
2001168
2
Fumes from meat cooking and lung cancer risk in Chinese women.
2000115
3 199760
4 201041
5 199939
6 200134
7 201027
8 200926
9 201124
10 201521
11 201814
12 201712
13 19989
14 20168
15 19967
16 20196
17 20175
18 20244
19 20224
20 20184

About Ming Ming Teh

Ming Ming Teh is a scholar working on Endocrinology, Diabetes and Metabolism, Pulmonary and Respiratory Medicine, Cardiology and Cardiovascular Medicine, Cancer Research and Surgery, having authored 32 papers that have together received 641 indexed citations. Recurring topics across this work include Diabetes Management and Research (8 papers), Hyperglycemia and glycemic control in critically ill and hospitalized patients (3 papers), Carcinogens and Genotoxicity Assessment (3 papers), Sarcoma Diagnosis and Treatment (2 papers), Diabetes Treatment and Management (2 papers), Cardiac tumors and thrombi (2 papers), Nutritional Studies and Diet (2 papers) and Potassium and Related Disorders (2 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (96 citations), Cancer Research (68 citations), Health, Toxicology and Mutagenesis (51 citations), Molecular Biology (215 citations) and Biochemistry (16 citations). Ming Ming Teh has collaborated with scholars based in Singapore, United Kingdom and Australia. Frequent co-authors include Adeline Seow, Philip Eng, Wee‐Teng Poh, Hin-Peng Lee, Mimi C. Yu, Bin Zhao, Yee‐Tang Wang, Steven T. F. Chan, Andrea Rajnakova and P. M. Y. Goh. Their work appears in journals such as Diabetic Medicine, Carcinogenesis, Diabetes Research and Clinical Practice, Therapeutic Advances in Endocrinology and Metabolism and Current Medical Research and Opinion.

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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