Qing Jiang

3.9k total citations
82 papers, 3.0k citations indexed

About

Qing Jiang is a scholar working on Molecular Biology, Cell Biology and Oncology. According to data from OpenAlex, Qing Jiang has authored 82 papers receiving a total of 3.0k indexed citations (citations by other indexed papers that have themselves been cited), including 65 papers in Molecular Biology, 28 papers in Cell Biology and 13 papers in Oncology. Recurrent topics in Qing Jiang's work include Microtubule and mitosis dynamics (24 papers), Genomics and Chromatin Dynamics (15 papers) and Bone Metabolism and Diseases (12 papers). Qing Jiang is often cited by papers focused on Microtubule and mitosis dynamics (24 papers), Genomics and Chromatin Dynamics (15 papers) and Bone Metabolism and Diseases (12 papers). Qing Jiang collaborates with scholars based in China, Japan and United States. Qing Jiang's co-authors include Chuanmao Zhang, James K. Hurst, Sergei V. Lymar, Gang Wang, Toshihisa Komori, Xin Qin, Xiaoyan Zhang, Hisato Komori, Toshihiro Miyazaki and Boyan Zhang and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Nature Communications.

In The Last Decade

Qing Jiang

79 papers receiving 3.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Qing Jiang China 31 2.1k 811 382 373 338 82 3.0k
Melanie A. Simpson United States 36 3.1k 1.5× 1.1k 1.3× 451 1.2× 438 1.2× 279 0.8× 63 4.3k
Sandra E. Wiley United States 28 2.9k 1.4× 561 0.7× 372 1.0× 332 0.9× 453 1.3× 47 4.3k
Sakari Kellokumpu Finland 34 1.8k 0.8× 792 1.0× 218 0.6× 231 0.6× 251 0.7× 73 2.8k
Yue Huang China 34 2.1k 1.0× 249 0.3× 744 1.9× 267 0.7× 229 0.7× 101 3.6k
Jan Riemer Germany 39 3.4k 1.6× 970 1.2× 188 0.5× 166 0.4× 301 0.9× 85 4.5k
Bing Wang China 29 1.9k 0.9× 1.3k 1.6× 368 1.0× 183 0.5× 248 0.7× 109 3.4k
Dante Neculai China 34 1.7k 0.8× 626 0.8× 448 1.2× 156 0.4× 298 0.9× 71 3.9k
Jane-Jane Chen United States 30 2.4k 1.2× 976 1.2× 211 0.6× 223 0.6× 397 1.2× 43 3.5k
Monther Abu-Remaileh United States 25 3.2k 1.5× 585 0.7× 399 1.0× 340 0.9× 721 2.1× 40 4.8k
Jerónimo Bravo Spain 30 2.1k 1.0× 542 0.7× 417 1.1× 265 0.7× 238 0.7× 72 3.1k

Countries citing papers authored by Qing Jiang

Since Specialization
Citations

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

Fields of papers citing papers by Qing Jiang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Qing Jiang

This figure shows the co-authorship network connecting the top 25 collaborators of Qing Jiang. A scholar is included among the top collaborators of Qing Jiang 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 Qing Jiang. Qing Jiang 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.
Zhou, Yujie, Lei Li, Zhihui Tang, et al.. (2025). Rapid and sensitive detection of foodborne pathogens via nanoparticle-assisted ICP-MS and electrochemical multimodal analysis. Food Chemistry. 481. 144076–144076.
2.
Wei, Zongjie, et al.. (2025). Interpretable CT Radiomics-based Machine Learning Model for Preoperative Prediction of Ki-67 Expression in Clear Cell Renal Cell Carcinoma. Academic Radiology. 32(5). 2739–2750. 3 indexed citations
3.
Jiang, Qing, Kenichi Nagano, Takeshi Moriishi, et al.. (2024). Roles of Sp7 in osteoblasts for the proliferation, differentiation, and osteocyte process formation. Journal of Orthopaedic Translation. 47. 161–175. 9 indexed citations
4.
Xin, Guangwei, et al.. (2024). TIP60 acetylation of Bub1 regulates centromeric H2AT120 phosphorylation for faithful chromosome segregation. Science China Life Sciences. 67(9). 1957–1969. 2 indexed citations
5.
Wang, Yun, et al.. (2024). Deep learning system for malignancy risk prediction in cystic renal lesions: a multicenter study. Insights into Imaging. 15(1). 121–121. 2 indexed citations
6.
Li, Hongli, et al.. (2022). Characterization of ginsenoside structural isomers from mixtures using in situ methylation with direct analysis in real-time ionization tandem mass spectrometry. Analytical and Bioanalytical Chemistry. 415(5). 887–897. 5 indexed citations
7.
Zhang, Boyan, Fan Huang, Guangwei Xin, et al.. (2021). Sufu negatively regulates both initiations of centrosome duplication and DNA replication. Proceedings of the National Academy of Sciences. 118(28). 7 indexed citations
8.
Jiang, Qing, Xin Qin, Carolina A. Yoshida, et al.. (2020). Antxr1, Which is a Target of Runx2, Regulates Chondrocyte Proliferation and Apoptosis. International Journal of Molecular Sciences. 21(7). 2425–2425. 14 indexed citations
9.
Qin, Xin, Qing Jiang, Kenichi Nagano, et al.. (2020). Runx2 is essential for the transdifferentiation of chondrocytes into osteoblasts. PLoS Genetics. 16(11). e1009169–e1009169. 87 indexed citations
10.
Xin, Guangwei, et al.. (2020). Aurora B regulates PP1γ–Repo-Man interactions to maintain the chromosome condensation state. Journal of Biological Chemistry. 295(43). 14780–14788. 4 indexed citations
11.
Xu, Xiaowei, Guopeng Wang, Boyan Zhang, et al.. (2017). CDK4 protein is degraded by anaphase-promoting complex/cyclosome in mitosis and reaccumulates in early G1 phase to initiate a new cell cycle in HeLa cells. Journal of Biological Chemistry. 292(24). 10131–10141. 26 indexed citations
12.
13.
Jiang, Qing, et al.. (2013). Phosphorylation of Crm1 by CDK1-cyclin B promotes Ran-dependent mitotic spindle assembly. Journal of Cell Science. 126(Pt 15). 3417–28. 35 indexed citations
14.
Wang, Gang, Qiang Chen, Xiaoyan Zhang, et al.. (2013). PCM1 Recruits Plk1 to Pericentriolar Matrix to Promote Primary Cilia Disassembly before Mitotic Entry. Journal of Cell Science. 126(Pt 6). 1355–65. 124 indexed citations
15.
Fujimura, Sayoko, Qing Jiang, Chiyoko Kobayashi, & Ryuichi Nishinakamura. (2010). Notch2 Activation in the Embryonic Kidney Depletes Nephron Progenitors. Journal of the American Society of Nephrology. 21(5). 803–810. 58 indexed citations
16.
Shi, Yang, Quanlong Lü, Jia Luo, et al.. (2010). Requirement for Lamin B Receptor and Its Regulation by Importin β and Phosphorylation in Nuclear Envelope Assembly during Mitotic Exit. Journal of Biological Chemistry. 285(43). 33281–33293. 30 indexed citations
17.
Chen, Qiang, Xiaoyan Zhang, Qing Jiang, Paul R. Clarke, & Chuanmao Zhang. (2008). Cyclin B1 is localized to unattached kinetochores and contributes to efficient microtubule attachment and proper chromosome alignment during mitosis. Cell Research. 18(2). 268–280. 61 indexed citations
18.
19.
20.
Jiang, Qing & James K. Hurst. (1997). Relative Chlorinating, Nitrating, and Oxidizing Capabilities of Neutrophils Determined with Phagocytosable Probes. Journal of Biological Chemistry. 272(52). 32767–32772. 74 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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