Zhiling Qu

469 total citations
21 papers, 380 citations indexed

About

Zhiling Qu is a scholar working on Molecular Biology, Oncology and Cancer Research. According to data from OpenAlex, Zhiling Qu has authored 21 papers receiving a total of 380 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Molecular Biology, 8 papers in Oncology and 4 papers in Cancer Research. Recurrent topics in Zhiling Qu's work include Angiogenesis and VEGF in Cancer (5 papers), Chemokine receptors and signaling (4 papers) and Mesenchymal stem cell research (3 papers). Zhiling Qu is often cited by papers focused on Angiogenesis and VEGF in Cancer (5 papers), Chemokine receptors and signaling (4 papers) and Mesenchymal stem cell research (3 papers). Zhiling Qu collaborates with scholars based in China and United States. Zhiling Qu's co-authors include Qiurong Ruan, Jun Yu, Dan Yan, Juan Ni, Guoping Wang, Yan Li, Dujuan Li, Dan Yan, Xiaoyan Wang and Sheng Zhou and has published in prestigious journals such as Life Sciences, Journal of Vascular Surgery and Atherosclerosis.

In The Last Decade

Zhiling Qu

20 papers receiving 378 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Zhiling Qu China 11 156 119 89 75 69 21 380
Bo Pang China 13 142 0.9× 175 1.5× 50 0.6× 77 1.0× 41 0.6× 26 462
Kyu Hyun Han South Korea 11 154 1.0× 90 0.8× 118 1.3× 34 0.5× 92 1.3× 23 389
Zulong Sheng China 13 211 1.4× 47 0.4× 76 0.9× 31 0.4× 97 1.4× 24 429
Hikaru Matsuda Japan 9 269 1.7× 60 0.5× 36 0.4× 96 1.3× 99 1.4× 12 546
Rei Nakano Japan 14 182 1.2× 73 0.6× 46 0.5× 63 0.8× 34 0.5× 27 417
Sheng Hu China 9 143 0.9× 60 0.5× 31 0.3× 76 1.0× 52 0.8× 28 331
Xiaofei Yang China 11 178 1.1× 41 0.3× 30 0.3× 35 0.5× 84 1.2× 37 345
B.J.E. de Lange-Brokaar Netherlands 9 231 1.5× 194 1.6× 66 0.7× 128 1.7× 185 2.7× 11 1.0k
Bing‐Xi Yan China 10 156 1.0× 164 1.4× 59 0.7× 48 0.6× 41 0.6× 19 417
Bo Dai China 12 319 2.0× 48 0.4× 64 0.7× 66 0.9× 128 1.9× 34 547

Countries citing papers authored by Zhiling Qu

Since Specialization
Citations

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

Fields of papers citing papers by Zhiling Qu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zhiling Qu

This figure shows the co-authorship network connecting the top 25 collaborators of Zhiling Qu. A scholar is included among the top collaborators of Zhiling Qu 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 Zhiling Qu. Zhiling Qu 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.
Zheng, Yan, et al.. (2025). Adverse predictive value of ASPM on lung adenocarcinoma overall survival depended on chemotherapy status. Future Science OA. 11(1). 2489328–2489328.
2.
Shi, Qun, et al.. (2023). Longitudinal change of six common inflammatory cytokines and their relationship to anxiety, depression, and cognitive impairment in acute ischemic stroke patients. Brazilian Journal of Medical and Biological Research. 56. e13025–e13025. 3 indexed citations
3.
Dong, Yuting, et al.. (2022). INSM1 Expression in Mesenchymal Tumors and Its Clinicopathological Significance. BioMed Research International. 2022(1). 1580410–1580410. 2 indexed citations
4.
Qu, Zhiling, et al.. (2016). Novel Use for DOG1 in Discriminating Breast Invasive Carcinoma from Noninvasive Breast Lesions. Disease Markers. 2016. 1–8. 4 indexed citations
5.
Huang, Fei, Feng Zhao, Liping Liang, et al.. (2015). Optomizing Transfection Efficiency of Cervical Cancer Cells Transfected by Cationic Liposomes LipofectamineTM2000. Asian Pacific Journal of Cancer Prevention. 16(17). 7749–7754. 4 indexed citations
6.
Dai, Jun, Jinyu Wang, Lili Yang, et al.. (2014). Correlation of Forkhead Box c2 with subtypes and invasive ability of invasive breast cancer. Journal of Huazhong University of Science and Technology [Medical Sciences]. 34(6). 896–901. 5 indexed citations
7.
Jiang, Jianwei, Dan Yan, Dujuan Li, et al.. (2014). Pentraxin 3 promotes oxLDL uptake and inhibits cholesterol efflux from macrophage-derived foam cells. Experimental and Molecular Pathology. 96(3). 292–299. 25 indexed citations
8.
Qu, Zhiling, Jun Yu, & Qiurong Ruan. (2012). TGF-β1-induced LPP expression dependant on Rho kinase during differentiation and migration of bone marrow-derived smooth muscle progenitor cells. Journal of Huazhong University of Science and Technology [Medical Sciences]. 32(4). 459–465. 4 indexed citations
9.
Li, Dujuan, Dan Yan, Jun Yu, et al.. (2011). Foxc2 overexpression enhances benefit of endothelial progenitor cells for inhibiting neointimal formation by promoting CXCR4-dependent homing. Journal of Vascular Surgery. 53(6). 1668–1678. 12 indexed citations
10.
Yan, Dan, Xiaoyan Wang, Dujuan Li, Zhiling Qu, & Qiurong Ruan. (2011). Macrophages overexpressing VEGF, transdifferentiate into endothelial-like cells in vitro and in vivo. Biotechnology Letters. 33(9). 1751–1758. 21 indexed citations
11.
Yan, Dan, et al.. (2011). Macrophages overexpressing VEGF target to infarcted myocardium and improve neovascularization and cardiac function. International Journal of Cardiology. 164(3). 334–338. 19 indexed citations
12.
Li, Yan, Jun Yu, Mincai Li, Zhiling Qu, & Qiurong Ruan. (2010). Mouse mesenchymal stem cells from bone marrow differentiate into smooth muscle cells by induction of plaque-derived smooth muscle cells. Life Sciences. 88(3-4). 130–140. 12 indexed citations
13.
Yu, Jun, et al.. (2010). SDF-1/CXCR4-Mediated Migration of Transplanted Bone Marrow Stromal Cells Toward Areas of Heart Myocardial Infarction Through Activation of PI3K/Akt. Journal of Cardiovascular Pharmacology. 55(5). 496–505. 94 indexed citations
14.
Yu, Jun, et al.. (2009). CXCR4 positive bone mesenchymal stem cells migrate to human endothelial cell stimulated by ox-LDL via SDF-1α/CXCR4 signaling axis. Experimental and Molecular Pathology. 88(2). 250–255. 31 indexed citations
15.
Yu, Jun, et al.. (2009). Oxidized low density lipoprotein‐induced transdifferentiation of bone marrow‐derived smooth muscle‐like cells into foam‐like cells in vitro. International Journal of Experimental Pathology. 91(1). 24–33. 27 indexed citations
16.
Ren, Xinyu, et al.. (2007). Tetramethylpyrazine inhibits agiontensin II-induced nuclear factor-kappaB activation and bone morphogenetic protein-2 downregulation in rat vascular smooth muscle cells.. PubMed. 59(3). 339–44. 12 indexed citations
17.
Feng, Yan, et al.. (2004). Construction of eukaryotic expression plasmid of human PRX3 and its expression in HEK-293FT cells. Current Medical Science. 24(4). 311–313. 1 indexed citations
18.
Wu, Hua, et al.. (2003). Extraction, purification and identification of bone morphogenetic protein in conditioned medium of osteosarcoma cell (MG-63). The Chinese-German Journal of Clinical Oncology. 2(4). 234–236. 3 indexed citations
19.
20.
Deng, Ziwei, et al.. (1996). [Effects of oxidized low density lipoprotein and very low density lipoprotein on the expression of MCP-1 by monocytes].. PubMed. 25(4). 220–3. 1 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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