Jun-Qiu Song

464 total citations
12 papers, 416 citations indexed

About

Jun-Qiu Song is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Cancer Research. According to data from OpenAlex, Jun-Qiu Song has authored 12 papers receiving a total of 416 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Molecular Biology, 4 papers in Cellular and Molecular Neuroscience and 4 papers in Cancer Research. Recurrent topics in Jun-Qiu Song's work include Extracellular vesicles in disease (6 papers), Neuropeptides and Animal Physiology (4 papers) and Signaling Pathways in Disease (3 papers). Jun-Qiu Song is often cited by papers focused on Extracellular vesicles in disease (6 papers), Neuropeptides and Animal Physiology (4 papers) and Signaling Pathways in Disease (3 papers). Jun-Qiu Song collaborates with scholars based in China and United States. Jun-Qiu Song's co-authors include Xu Teng, Yongfen Qi, Chaoshu Tang, Yan Cai, Chaoshu Tang, Ming‐Lin Liu, Yan Cai, Man Shang, Gaigai Zhang and Yanxia Liu and has published in prestigious journals such as Oncotarget, Journal of Molecular Medicine and Peptides.

In The Last Decade

Jun-Qiu Song

12 papers receiving 414 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jun-Qiu Song China 8 219 96 95 67 52 12 416
Pingping Xia China 13 298 1.4× 60 0.6× 126 1.3× 20 0.3× 125 2.4× 28 651
Chunjie Yang China 11 175 0.8× 21 0.2× 69 0.7× 85 1.3× 50 1.0× 28 372
Heying Zhou Japan 10 327 1.5× 43 0.4× 41 0.4× 90 1.3× 31 0.6× 18 602
Tianwen Han China 5 269 1.2× 21 0.2× 59 0.6× 57 0.9× 44 0.8× 8 476
Gianluca Gitti Italy 6 115 0.5× 37 0.4× 121 1.3× 94 1.4× 26 0.5× 6 390
Jian Zou China 13 208 0.9× 36 0.4× 33 0.3× 104 1.6× 29 0.6× 26 413
Marianna Murányi United States 10 191 0.9× 59 0.6× 21 0.2× 31 0.5× 21 0.4× 14 449
Chuanshi Xiao China 11 166 0.8× 21 0.2× 36 0.4× 77 1.1× 80 1.5× 24 390

Countries citing papers authored by Jun-Qiu Song

Since Specialization
Citations

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

Fields of papers citing papers by Jun-Qiu Song

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jun-Qiu Song

This figure shows the co-authorship network connecting the top 25 collaborators of Jun-Qiu Song. A scholar is included among the top collaborators of Jun-Qiu Song 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-Qiu Song. Jun-Qiu Song is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

12 of 12 papers shown
1.
Jia, Mei, Lin Li, Xiping Liu, Jun-Qiu Song, & Zhanbing Bai. (2019). A class of nonlocal problems of fractional differential equations with composition of derivative and parameters. Advances in Difference Equations. 2019(1). 4 indexed citations
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Zhāng, Qí, Man Shang, Mengxiao Zhang, et al.. (2016). Microvesicles derived from hypoxia/reoxygenation-treated human umbilical vein endothelial cells promote apoptosis and oxidative stress in H9c2 cardiomyocytes. BMC Cell Biology. 17(1). 25–25. 49 indexed citations
5.
Wang, Yilu, Miao Liu, Man Shang, et al.. (2016). [Effects of circulating microvesicles derived from myocardial ischemic preconditioning on myocardial ischemia/reperfusion injury in rats].. PubMed. 32(2). 97–101. 1 indexed citations
6.
Wang, Shaoxun, Qi Zhang, Man Shang, et al.. (2014). Microvesicles derived from hypoxia/reoxygenation-treated human umbilical vein endothelial cells impair relaxation of rat thoracic aortic rings.. PubMed. 30(6). 560–6. 4 indexed citations
7.
Shang, Man, Qi Zhang, Yao Wang, et al.. (2013). Effects of endothelial microvesicles induced by A23187 on H9c2 cardiomyocytes.. PubMed. 29(6). 559–64. 2 indexed citations
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Teng, Xu, Jun-Qiu Song, Gaigai Zhang, et al.. (2011). Inhibition of endoplasmic reticulum stress by intermedin1–53 protects against myocardial injury through a PI3 kinase–Akt signaling pathway. Journal of Molecular Medicine. 89(12). 1195–1205. 49 indexed citations
10.
Song, Jun-Qiu, Xu Teng, Yan Cai, Chaoshu Tang, & Yongfen Qi. (2009). Activation of Akt/GSK-3β signaling pathway is involved in intermedin1-53 protection against myocardial apoptosis induced by ischemia/reperfusion. APOPTOSIS. 14(9). 1061–1069. 51 indexed citations
11.
Zhang, Gaigai, Xu Teng, Yue Liu, et al.. (2009). Inhibition of endoplasm reticulum stress by ghrelin protects against ischemia/reperfusion injury in rat heart. Peptides. 30(6). 1109–1116. 47 indexed citations
12.
Song, Jun-Qiu, Xu Teng, Yan Cai, Chaoshu Tang, & Yongfen Qi. (2009). Activation of Akt/GSK-3β signaling pathway is involved in intermedin1–53 protection against myocardial apoptosis induced by ischemia/reperfusion. APOPTOSIS. 14(11). 1299–1307. 132 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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