Tai Ma

56 papers receiving 1.1k citations

Peers

Tai Ma
Comparison fields: 5 of 121
  • Endocrine and Autonomic Systems 163
  • Endocrinology, Diabetes and Metabolism 385
  • Pediatrics, Perinatology and Child Health 229
  • Biological Psychiatry 22
  • Obstetrics and Gynecology 54
Replace Stéphane Cauchi with:
Stéphane Cauchi France
Reiko Sakurai United States
Kun‐san Xiang China
Paúl Cordero United Kingdom
Masayo Yamada Japan
Gustavo Castaño Argentina
Francine Einstein United States
Mary C. Playdon United States
Andrzej S. Januszewski Australia
Yue Zhao China
Tai Ma relative to Stéphane Cauchi France Stéphane Cauchi's profile →
Citations per field
00.5×3.5×
Stéphane Cauchi · 1×
Citations per year

Countries citing papers authored by Tai Ma

Since Specialization
Citations

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

Fields of papers citing papers by Tai Ma

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 60 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1994324
2 1997102
3 201368
4 201167
5 200266
6 201362
7 201353
8 199333
9 201333
10 201327
11 199325
12 201325
13 201921
14 201618
15 201717
16 202016
17 202016
18 201815
19 201913
20 201913

About Tai Ma

Tai Ma is a scholar working on Pulmonary and Respiratory Medicine, Molecular Biology, Epidemiology, Surgery and Endocrinology, Diabetes and Metabolism, having authored 60 papers that have together received 1.2k indexed citations. Recurring topics across this work include Gastric Cancer Management and Outcomes (10 papers), Thyroid Disorders and Treatments (6 papers), Endoplasmic Reticulum Stress and Disease (4 papers), Hepatitis B Virus Studies (3 papers), Neonatal Health and Biochemistry (3 papers), Autophagy in Disease and Therapy (3 papers), Liver Disease Diagnosis and Treatment (3 papers) and Thyroid Cancer Diagnosis and Treatment (3 papers). The work is most often cited by research in Endocrine and Autonomic Systems (163 citations), Endocrinology, Diabetes and Metabolism (385 citations), Pediatrics, Perinatology and Child Health (229 citations), Biological Psychiatry (22 citations) and Obstetrics and Gynecology (54 citations). Tai Ma has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include G. Robert DeLong, Guoping Sun, Fei Zhong, Lulu Fan, Wei Wei, Karen O’Donnell, Xiaoqiu Li, Paul W. Leslie, Jun Guo and Hua Wang. Their work appears in journals such as Journal of Pineal Research, PLoS ONE, Journal of Cancer, International Immunopharmacology and Developmental Medicine & Child Neurology.

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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