Jun Qian

7.0k total citations
260 papers, 5.2k citations indexed

About

Jun Qian is a scholar working on Molecular Biology, Hematology and Cancer Research. According to data from OpenAlex, Jun Qian has authored 260 papers receiving a total of 5.2k indexed citations (citations by other indexed papers that have themselves been cited), including 146 papers in Molecular Biology, 108 papers in Hematology and 64 papers in Cancer Research. Recurrent topics in Jun Qian's work include Acute Myeloid Leukemia Research (97 papers), Epigenetics and DNA Methylation (43 papers) and MicroRNA in disease regulation (38 papers). Jun Qian is often cited by papers focused on Acute Myeloid Leukemia Research (97 papers), Epigenetics and DNA Methylation (43 papers) and MicroRNA in disease regulation (38 papers). Jun Qian collaborates with scholars based in China, United States and Canada. Jun Qian's co-authors include Jiang Lin, Zhaoqun Deng, Ji‐chun Ma, Dong‐ming Yao, Changyou Zhan, Xiang‐mei Wen, Juan Guan, Zhuxuan Jiang, Jing Yang and Jing‐dong Zhou and has published in prestigious journals such as Journal of Biological Chemistry, Nature Communications and SHILAP Revista de lepidopterología.

In The Last Decade

Jun Qian

248 papers receiving 5.1k 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 Qian China 39 3.1k 1.4k 1.1k 565 452 260 5.2k
Abdel Kareem Azab United States 36 3.1k 1.0× 1.7k 1.2× 1.4k 1.3× 368 0.7× 708 1.6× 129 5.8k
Bor‐Sheng Ko Taiwan 32 1.7k 0.6× 430 0.3× 1.3k 1.2× 379 0.7× 431 1.0× 141 3.8k
John Hood United States 30 4.2k 1.3× 938 0.7× 781 0.7× 378 0.7× 410 0.9× 56 7.2k
Qing‐Xiang Amy Sang United States 43 2.4k 0.8× 2.7k 1.9× 902 0.8× 210 0.4× 446 1.0× 123 6.0k
Jun Qian China 28 1.9k 0.6× 436 0.3× 309 0.3× 577 1.0× 514 1.1× 113 3.5k
Ciprian Tomuleasa Romania 26 1.3k 0.4× 675 0.5× 340 0.3× 244 0.4× 330 0.7× 181 2.6k
Achim Krüger Germany 45 2.6k 0.8× 2.2k 1.6× 486 0.4× 360 0.6× 432 1.0× 111 5.8k
Masahiro Abe Japan 40 2.0k 0.6× 347 0.3× 1.4k 1.3× 420 0.7× 599 1.3× 217 5.1k
Dwayne G. Stupack United States 46 4.4k 1.4× 1.2k 0.9× 370 0.3× 274 0.5× 402 0.9× 109 7.3k
Manohar Ratnam United States 31 2.8k 0.9× 395 0.3× 485 0.4× 813 1.4× 522 1.2× 103 5.5k

Countries citing papers authored by Jun Qian

Since Specialization
Citations

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

Fields of papers citing papers by Jun Qian

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jun Qian

This figure shows the co-authorship network connecting the top 25 collaborators of Jun Qian. A scholar is included among the top collaborators of Jun Qian 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 Qian. Jun Qian 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.
Zhao, Yangjing, Jiaxin Xu, Yue You, et al.. (2025). ID1 in hematopoiesis and hematologic disorders: novel potentials of a classic differentiation regulator. Cellular & Molecular Biology Letters. 30(1). 124–124.
3.
Jin, Ketao, et al.. (2024). Exosomes in cancer diagnosis based on the Latest Evidence: Where are We?. International Immunopharmacology. 142(Pt A). 113133–113133. 2 indexed citations
4.
Zhang, Ting‐juan, Zi‐jun Xu, Xiang‐mei Wen, et al.. (2022). SLIT2 promoter hypermethylation-mediated SLIT2-IT1/miR-218 repression drives leukemogenesis and predicts adverse prognosis in myelodysplastic neoplasm. Leukemia. 36(10). 2488–2498. 12 indexed citations
5.
Gu, Yu, Zi‐jun Xu, Jing‐dong Zhou, et al.. (2021). Abnormal expression and methylation of PRR34‐AS1 are associated with adverse outcomes in acute myeloid leukemia. Cancer Medicine. 10(15). 5283–5296. 5 indexed citations
6.
Jia, Yan, et al.. (2020). Effects of miR-26a on Osteogenic Differentiation of Bone Marrow Mesenchymal Stem Cells by a Mesoporous Silica Nanoparticle - PEI - Peptide System. SHILAP Revista de lepidopterología. 2 indexed citations
7.
Qian, Jun, Lijun Kuang, Lin Che, Fei Chen, & Xuebo Liu. (2020). Maximum blood glucose levels during hospitalisation to predict mortality in patients with acute coronary syndrome: a retrospective cohort study. BMJ Open. 10(12). e042316–e042316. 5 indexed citations
8.
Zhang, Ting‐juan, Xiang‐mei Wen, Jing‐dong Zhou, et al.. (2019). <p><em>SOX30</em> methylation correlates with disease progression in patients with chronic myeloid leukemia</p>. OncoTargets and Therapy. Volume 12. 4789–4794. 9 indexed citations
9.
Li, Xixi, Jing‐dong Zhou, Xiang‐mei Wen, et al.. (2019). <p>Increased <em>MCL-1</em> expression predicts poor prognosis and disease recurrence in acute myeloid leukemia</p>. OncoTargets and Therapy. Volume 12. 3295–3304. 32 indexed citations
10.
Acharya, Viral V., et al.. (2019). In the Shadow of Banks: Wealth Management Products and Issuing Banks’ Risk in China. SSRN Electronic Journal. 66 indexed citations
11.
Yang, Lan, Jing‐dong Zhou, Ting‐juan Zhang, et al.. (2018). Overexpression of lncRNA <em>PANDAR </em>predicts adverse prognosis in acute myeloid leukemia. Cancer Management and Research. Volume 10. 4999–5007. 30 indexed citations
12.
Zhang, Ting‐juan, Jing‐dong Zhou, Dongqin Yang, et al.. (2017). TET2 expression is a potential prognostic and predictive biomarker in cytogenetically normal acute myeloid leukemia. Journal of Cellular Physiology. 233(8). 5838–5846. 25 indexed citations
13.
Zhou, Jing‐dong, Jiang Lin, Ting‐juan Zhang, et al.. (2017). Hypomethylation‐mediated H19 overexpression increases the risk of disease evolution through the association with BCR‐ABL transcript in chronic myeloid leukemia. Journal of Cellular Physiology. 233(3). 2444–2450. 24 indexed citations
14.
Xu, Zi‐jun, Jing‐dong Zhou, Xi-xi Li, et al.. (2017). Methylation‐associated DOK1 and DOK2 down‐regulation: Potential biomarkers for predicting adverse prognosis in acute myeloid leukemia. Journal of Cellular Physiology. 233(9). 6604–6614. 15 indexed citations
15.
Chai, Hai‐yan, Jun Qian, Jiang Lin, et al.. (2013). [Expression of RAGE-1 gene in acute myeloid leukemia].. PubMed. 21(1). 20–4. 1 indexed citations
16.
Zhang, Chunling, Haojie Shi, Lei Chen, et al.. (2011). Harpin-induced expression and transgenic overexpression of the phloem protein gene AtPP2-A1 in Arabidopsis repress phloem feeding of the green peach aphid Myzus persicae. BMC Plant Biology. 11(1). 11–11. 95 indexed citations
17.
Qian, Jun, et al.. (2005). [Isolation and Sequence Analysis of the Xa21 Gene Wxon II Homologus from Different Species of Wild Rice in Yunnan.].. PubMed. 27(3). 382–286. 2 indexed citations
18.
Qian, Jun. (2005). Application of Bletilla striata in the interventional therapy of hepatocellular carcinoma: a comparative study in ACI rats. Chinese Journal of Hospital Pharmacy. 2 indexed citations
19.
Qian, Jun, Dong Li, Bicheng Zhang, et al.. (2002). Identification and Digitalized Expression Analysis of Murine UBAP1 Gene by Means of EST Database Searching. PROGRESS IN BIOCHEMISTRY AND BIOPHYSICS. 29(2). 323–327. 1 indexed citations
20.
Qian, Jun. (2002). Allogenic implantable rat model of hepatocellular carcinoma and its MRI-properties. Zhonghua fangshexian yixue zazhi.

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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