Hai‐qin Tang

582 citations
26 papers · 468 indexed · h-index 12
Topics
Blood Pressure and Hypertension Studies (3 papers)Lipoproteins and Cardiovascular Health (2 papers)Cardiac Health and Mental Health (2 papers)
Partner nations
China

In The Last Decade

Hai‐qin Tang

25 papers receiving 463 citations

Peers

Hai‐qin Tang
Comparison fields: 5 of 89
  • Endocrinology, Diabetes and Metabolism 132
  • Cardiology and Cardiovascular Medicine 128
  • Molecular Biology 121
  • Surgery 81
  • Genetics 62
Replace Karina Thieme with:
Karina Thieme Brazil
Daniella Lent-Schochet United States
Jana Bělobrádková Czechia
Xiu Feng China
Yung‐Zu Tseng Taiwan
Yat-Ching Tong Taiwan
Shannon E. Campbell Canada
Ágota Vér Hungary
Letícia A. Brondani Brazil
Taisuke Ono Japan
Hai‐qin Tang relative to Karina Thieme Brazil Karina Thieme's profile →
Citations per field
00.5×1.7×
Karina Thieme · 1×
Citations per year

Countries citing papers authored by Hai‐qin Tang

Since Specialization
Citations

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

Fields of papers citing papers by Hai‐qin Tang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hai‐qin Tang. 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 Hai‐qin Tang. The network helps show where Hai‐qin Tang may publish in the future.

Co-authorship network of co-authors of Hai‐qin Tang

This figure shows the co-authorship network connecting the top 25 collaborators of Hai‐qin Tang. A scholar is included among the top collaborators of Hai‐qin Tang based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Hai‐qin Tang. Hai‐qin Tang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 6
2 3
3 40
4 11
5 15
6 73
7 29
8 51
9 38
10 8
11
Association analysis of GWAS and candidate gene loci in a Chinese population with coronary heart disease.
5
12 21
13 10
14 23
15 10
16 24
17 8
18 22
19 14
20
[Efficacy of enalapril combined with folic acid in lowering blood pressure and plasma homocysteine level].
4

About Hai‐qin Tang

Hai‐qin Tang is a scholar working on Aging, Clinical Biochemistry and Endocrinology, Diabetes and Metabolism, having authored 26 papers that have together received 468 indexed citations. Recurring topics across this work include Blood Pressure and Hypertension Studies (3 papers), Lipoproteins and Cardiovascular Health (2 papers) and Cardiac Health and Mental Health (2 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (132 citations), Cardiology and Cardiovascular Medicine (128 citations) and Clinical Biochemistry (33 citations). Hai‐qin Tang has collaborated with scholars based in China. Frequent co-authors include Songtao Tang, Qiu Zhang, Jiang Pin, Yuan Wang, Yong Zhang, Hongxia Cao, Huaqing Zhu, Changjiang Wang, Changjiang Wang and Wenjia Peng. Their work appears in journals such as Gene, Medicine and Materials & Design.

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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