Jun Tai

2.2k total citations
118 papers, 1.4k citations indexed

About

Jun Tai is a scholar working on Physiology, Pulmonary and Respiratory Medicine and Molecular Biology. According to data from OpenAlex, Jun Tai has authored 118 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Physiology, 26 papers in Pulmonary and Respiratory Medicine and 25 papers in Molecular Biology. Recurrent topics in Jun Tai's work include Obstructive Sleep Apnea Research (24 papers), Neuroscience of respiration and sleep (17 papers) and Thyroid Cancer Diagnosis and Treatment (12 papers). Jun Tai is often cited by papers focused on Obstructive Sleep Apnea Research (24 papers), Neuroscience of respiration and sleep (17 papers) and Thyroid Cancer Diagnosis and Treatment (12 papers). Jun Tai collaborates with scholars based in China, United States and Australia. Jun Tai's co-authors include Xin Ni, Yi Wang, Shengcai Wang, Xiong Zhu, Yongli Guo, Shijun Li, Zhifei Xu, Jieqiong Li, Wentong Ge and Xiaodan Li and has published in prestigious journals such as Environmental Science & Technology, PLoS ONE and Advanced Functional Materials.

In The Last Decade

Jun Tai

109 papers receiving 1.4k citations

Peers

Jun Tai
Comparison fields: 5 of 144
  • Molecular Biology 522
  • Physiology 276
  • Endocrine and Autonomic Systems 185
  • Biomedical Engineering 184
  • Pulmonary and Respiratory Medicine 159
Replace Giampietro Farronato with:
Giampietro Farronato Italy
Li‐Da Chen China
James Deschner Germany
Toshihide Noguchi Japan
Letizia Perillo Italy
Yuzheng Zhang China
Er Chen United States
D Lauritano Italy
Philippe Humbert France
Stefania Cantore Italy
Giampietro Farronato Italy View profile →
Citations per field, relative to Jun Tai
Jun Tai · 1×
Citations per year, relative to Jun Tai
Jun Tai · 1×

Countries citing papers authored by Jun Tai

Since Specialization
Citations

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

Fields of papers citing papers by Jun Tai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jun Tai

This figure shows the co-authorship network connecting the top 25 collaborators of Jun Tai. A scholar is included among the top collaborators of Jun Tai 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 Jun Tai. Jun Tai 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
# Work Indexed citations
1 1
2 2
3 13
4 18
5 5
6 34
7 7
8 70
9 99
10 65
11 0
12 5
13 22
14 11
15 28
16 17
17 9
18 5
19
[Relationship of alcohol drinking and tea consumption with the risk of nasopharynx cancer among Chinese population: a meta-analysis].
1
20 4

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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