Zhenjun Tian

2.4k total citations
87 papers, 1.8k citations indexed

About

Zhenjun Tian is a scholar working on Molecular Biology, Cardiology and Cardiovascular Medicine and Physiology. According to data from OpenAlex, Zhenjun Tian has authored 87 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 38 papers in Molecular Biology, 30 papers in Cardiology and Cardiovascular Medicine and 27 papers in Physiology. Recurrent topics in Zhenjun Tian's work include Adipose Tissue and Metabolism (18 papers), Cardiovascular Function and Risk Factors (12 papers) and Congenital Heart Disease Studies (11 papers). Zhenjun Tian is often cited by papers focused on Adipose Tissue and Metabolism (18 papers), Cardiovascular Function and Risk Factors (12 papers) and Congenital Heart Disease Studies (11 papers). Zhenjun Tian collaborates with scholars based in China, United States and Australia. Zhenjun Tian's co-authors include Mengxin Cai, Yue Xi, Jack Rychik, Jonathan R. Kaltman, Dandan Jia, Da‐Wei Gong, Bowen Li, Anita Szwast, Lili Feng and Lei Xi and has published in prestigious journals such as PLoS ONE, Diabetes and Scientific Reports.

In The Last Decade

Zhenjun Tian

79 papers receiving 1.7k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Zhenjun Tian China 25 671 524 474 429 235 87 1.8k
Amy L. Sindler United States 21 618 0.9× 774 1.5× 935 2.0× 387 0.9× 151 0.6× 36 2.3k
Jared J. Greiner United States 24 403 0.6× 729 1.4× 555 1.2× 216 0.5× 120 0.5× 77 1.7k
Norio Hotta Japan 27 459 0.7× 402 0.8× 637 1.3× 146 0.3× 171 0.7× 122 2.3k
Raffaele Napoli Italy 31 816 1.2× 749 1.4× 729 1.5× 172 0.4× 382 1.6× 84 2.8k
Paul R. Standley United States 30 619 0.9× 407 0.8× 590 1.2× 139 0.3× 312 1.3× 65 2.3k
Jia Liu China 26 612 0.9× 210 0.4× 392 0.8× 453 1.1× 287 1.2× 177 2.3k
Stephen M. Richards Australia 28 697 1.0× 739 1.4× 793 1.7× 206 0.5× 273 1.2× 88 2.3k
Rachel A. Gioscia‐Ryan United States 21 925 1.4× 497 0.9× 935 2.0× 242 0.6× 108 0.5× 44 2.2k
Anna M.D. Watson Australia 26 719 1.1× 558 1.1× 416 0.9× 231 0.5× 370 1.6× 48 2.5k
Jun‐ichi Oyama Japan 28 740 1.1× 482 0.9× 495 1.0× 169 0.4× 486 2.1× 75 2.3k

Countries citing papers authored by Zhenjun Tian

Since Specialization
Citations

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

Fields of papers citing papers by Zhenjun Tian

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zhenjun Tian

This figure shows the co-authorship network connecting the top 25 collaborators of Zhenjun Tian. A scholar is included among the top collaborators of Zhenjun Tian 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 Zhenjun Tian. Zhenjun Tian 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
1.
2.
Tian, Zhenjun, et al.. (2025). Exerkines: Potential regulators of diabetic cardiomyopathy. Ageing Research Reviews. 110. 102816–102816. 3 indexed citations
3.
Xi, Yue, et al.. (2025). Exerkine-mediated organ interactions: A new interpretation of exercise on cardiovascular function improvement. Life Sciences. 371. 123628–123628. 2 indexed citations
4.
Xu, Wen, et al.. (2024). The emerging role of exercise in Alzheimer’s disease: Focus on mitochondrial function. Ageing Research Reviews. 101. 102486–102486. 4 indexed citations
5.
Li, Xu‐Hui, et al.. (2024). Increased gene dosage of RFWD2 causes autistic-like behaviors and aberrant synaptic formation and function in mice. Molecular Psychiatry. 29(8). 2496–2509. 5 indexed citations
6.
Li, Bowen, et al.. (2024). Exercise and nutrition benefit skeletal muscle: From influence factor and intervention strategy to molecular mechanism. Sports Medicine and Health Science. 6(4). 302–314. 9 indexed citations
7.
Zhao, Yifang, et al.. (2024). Role of Irisin in exercise training-regulated endoplasmic reticulum stress, autophagy and myogenesis in the skeletal muscle after myocardial infarction. Journal of Physiology and Biochemistry. 80(4). 895–908. 3 indexed citations
8.
9.
Tang, Jie, et al.. (2023). Resistance training up-regulates Smyd1 expression and inhibits oxidative stress and endoplasmic reticulum stress in the heart of middle-aged mice. Free Radical Biology and Medicine. 210. 304–317. 4 indexed citations
10.
Yu, Mengyuan, et al.. (2023). FNDC5/Irisin Inhibits the Inflammatory Response and Mediates the Aerobic Exercise-Induced Improvement of Liver Injury after Myocardial Infarction. International Journal of Molecular Sciences. 24(4). 4159–4159. 16 indexed citations
11.
Li, Bowen, et al.. (2022). Effects of different modes of exercise on skeletal muscle mass and function and IGF-1 signaling during early aging in mice. Journal of Experimental Biology. 225(21). 23 indexed citations
12.
13.
Cai, Mengxin, Yufeng Si, Jianshe Zhang, Zhenjun Tian, & Shaojun Du. (2018). Zebrafish Embryonic Slow Muscle Is a Rapid System for Genetic Analysis of Sarcomere Organization by CRISPR/Cas9, but Not NgAgo. Marine Biotechnology. 20(2). 168–181. 12 indexed citations
14.
Lin, Qinqin, et al.. (2017). MiR-21 Regulates TNF-α-Induced CD40 Expression via the SIRT1-NF-κB Pathway in Renal Inner Medullary Collecting Duct Cells. Cellular Physiology and Biochemistry. 41(1). 124–136. 26 indexed citations
15.
Xiao, Li, et al.. (2017). Effects of miR-29a and miR-101a Expression on Myocardial Interstitial Collagen Generation After Aerobic Exercise in Myocardial-infarcted Rats. Archives of Medical Research. 48(1). 27–34. 35 indexed citations
16.
Szwast, Anita, et al.. (2014). Maternal hyperoxygenation improves left heart filling in fetuses with atrial septal aneurysm causing impediment to left ventricular inflow. Ultrasound in Obstetrics and Gynecology. 45(6). 664–669. 47 indexed citations
17.
Rychik, Jack, Margaret McCann, Zhenjun Tian, Michael Bebbington, & Mark P. Johnson. (2010). Fetal cardiovascular effects of lower urinary tract obstruction with giant bladder. Ultrasound in Obstetrics and Gynecology. 36(6). 682–686. 10 indexed citations
18.
Hu, Hao, Shengpeng Wang, Zhenjun Tian, et al.. (2009). Exercise benefits cardiovascular health in hyperlipidemia rats correlating with changes of the cardiac vagus nerve. European Journal of Applied Physiology. 108(3). 459–468. 14 indexed citations
19.
Li, Qiuxia, Zhenjun Tian, Haifeng Zhang, et al.. (2008). Aging-associated insulin resistance predisposes to hypertension and its reversal by exercise: the role of vascular vasorelaxation to insulin. Basic Research in Cardiology. 104(3). 269–284. 35 indexed citations
20.
Kaltman, Jonathan R., et al.. (2004). Impact of congenital heart disease on cerebrovascular blood flow dynamics in the fetus. Ultrasound in Obstetrics and Gynecology. 25(1). 32–36. 189 indexed citations

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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