Junqing Han

1.6k total citations · 1 hit paper
39 papers, 1.2k citations indexed

About

Junqing Han is a scholar working on Molecular Biology, Oncology and Cancer Research. According to data from OpenAlex, Junqing Han has authored 39 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Molecular Biology, 11 papers in Oncology and 11 papers in Cancer Research. Recurrent topics in Junqing Han's work include Cancer-related molecular mechanisms research (6 papers), MicroRNA in disease regulation (5 papers) and Lung Cancer Treatments and Mutations (4 papers). Junqing Han is often cited by papers focused on Cancer-related molecular mechanisms research (6 papers), MicroRNA in disease regulation (5 papers) and Lung Cancer Treatments and Mutations (4 papers). Junqing Han collaborates with scholars based in China, United States and Malaysia. Junqing Han's co-authors include Ling Zhang, Bo Zhang, Zhixue Wang, Lin Zhao, Anyuan Li, Fanghua Qi, Rong Shen, Weibo Wang, Chuanxi Wang and Jianpeng Chen and has published in prestigious journals such as Biochemical and Biophysical Research Communications, Food Hydrocolloids and International Journal of Biological Macromolecules.

In The Last Decade

Junqing Han

36 papers receiving 1.2k citations

Hit Papers

The advantages of using traditional Chinese medicine as a... 2015 2026 2018 2022 2015 100 200 300
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. The advantages of using traditional Chinese medicine as an adjunctive therapy in the whole course of cancer treatment instead of only terminal stage of cancer
    2015 359 citations Junqing Han et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Junqing Han China 17 683 494 238 135 106 39 1.2k
Lei Dong China 15 812 1.2× 453 0.9× 158 0.7× 134 1.0× 124 1.2× 34 1.3k
Junhua Zheng China 22 638 0.9× 327 0.7× 192 0.8× 285 2.1× 91 0.9× 70 1.3k
Huayao Li China 22 731 1.1× 422 0.9× 199 0.8× 178 1.3× 54 0.5× 55 1.2k
Youcheng Zhang China 16 666 1.0× 269 0.5× 237 1.0× 137 1.0× 105 1.0× 65 1.1k
Constantin Ștefani Romania 12 673 1.0× 320 0.6× 320 1.3× 222 1.6× 88 0.8× 38 1.2k
Cheng Hu China 21 584 0.9× 321 0.6× 134 0.6× 297 2.2× 133 1.3× 71 1.1k
Qipeng Xie China 19 690 1.0× 428 0.9× 146 0.6× 94 0.7× 131 1.2× 53 974

Countries citing papers authored by Junqing Han

Since Specialization
Citations

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

Fields of papers citing papers by Junqing Han

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Junqing Han

This figure shows the co-authorship network connecting the top 25 collaborators of Junqing Han. A scholar is included among the top collaborators of Junqing Han 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 Junqing Han. Junqing Han 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.
Gu, Bin, Junqing Han, Yahui Gao, et al.. (2025). Preparation, characterization, and solubility enhancement of octenyl succinate anhydride debranched starch/1-Octacosanol nanocomplex. Food Bioscience. 66. 106174–106174. 1 indexed citations
2.
3.
Wang, Haoran, Junqing Han, Yuying Wu, & Jinchuan Jie. (2025). Effect of boron on the microstructure and properties of Cu–15Ni–8Sn alloy. Journal of Materials Research and Technology. 36. 7387–7398.
4.
Wang, Haoran, Yuying Wu, Junqing Han, et al.. (2025). A honeycomb-like crystalline-amorphous nanostructure in Cu-B alloy with high corrosion resistance. Surfaces and Interfaces. 58. 105861–105861. 1 indexed citations
5.
Han, Junqing, et al.. (2024). Effect of the degree of substitution on water solubility of OSA-debranched starch and its potential use as a 1-Octacosanol carrier. International Journal of Biological Macromolecules. 289. 138715–138715. 3 indexed citations
6.
7.
Han, Xiao, et al.. (2019). Long noncoding RNA OIP5-AS1 in cancer. Clinica Chimica Acta. 499. 75–80. 39 indexed citations
8.
Lei, Cong, Zhiyong Qiu, Yang Zhao, et al.. (2017). Loss of β-arrestin-2 and Activation of CXCR2 Correlate with Lymph Node Metastasis in Non-small Cell Lung Cancer. Journal of Cancer. 8(14). 2785–2792. 10 indexed citations
9.
Wang, Shuai, et al.. (2016). Long Noncoding RNA ROR Regulates Proliferation, Invasion, and Stemness of Gastric Cancer Stem Cell. Cellular Reprogramming. 18(5). 319–326. 44 indexed citations
10.
Han, Junqing, Jian Zhang, Guanzhen Li, et al.. (2016). The long noncoding RNAs PVT1 and uc002mbe.2 in sera provide a new supplementary method for hepatocellular carcinoma diagnosis. Medicine. 95(31). e4436–e4436. 67 indexed citations
11.
Yuan, Baoying, Xingwen Wang, Dan Wang, et al.. (2015). High scavenger receptor class B type I expression is related to tumor aggressiveness and poor prognosis in breast cancer. Tumor Biology. 37(3). 3581–3588. 57 indexed citations
12.
13.
Yang, Fan, et al.. (2015). MicroRNA-19a mediates gastric carcinoma cell proliferation through the activation of nuclear factor-κB. Molecular Medicine Reports. 12(4). 5780–5786. 14 indexed citations
14.
Han, Junqing, et al.. (2015). E-cadherin mediates adhesion of Aspergillus fumigatus to non-small cell lung cancer cells. Tumor Biology. 37(12). 15593–15599. 11 indexed citations
15.
Ding, Xiao, Meng Jiang, Haiyan Jing, et al.. (2014). Analysis of serum levels of 15 trace elements in breast cancer patients in Shandong, China. Environmental Science and Pollution Research. 22(10). 7930–7935. 65 indexed citations
16.
Zhang, Qiong, Honghai Dai, Hongyun Dong, et al.. (2014). EGFR mutations and clinical outcomes of chemotherapy for advanced non-small cell lung cancer: A meta-analysis. Lung Cancer. 85(3). 339–345. 19 indexed citations
17.
Li, Xiaohui, Xin Zhao, Hongmin Wang, Junqing Han, & Li Liu. (2014). A polysaccharide from the fruiting bodies of Agaricus blazei Murill induces caspase-dependent apoptosis in human leukemia HL-60 cells. Tumor Biology. 35(9). 8963–8968. 16 indexed citations
18.
Wang, Chuanxi, Bao Song, Wei Song, et al.. (2011). Underexpressed microRNA‐199b‐5p targets Hypoxia‐Inducible Factor‐1α in hepatocellular carcinoma and predicts prognosis of hepatocellular carcinoma patients. Journal of Gastroenterology and Hepatology. 26(11). 1630–1637. 56 indexed citations
19.
Ding, Xiao, Junqing Han, & Sheng Wei. (2009). Associations between serum levels of trace elements and breast cancer.. Journal of Shandong University. 47(7). 96–98. 2 indexed citations
20.
Han, Junqing. (2004). Efficacy of different radiotherapy methods in treatment of brain metastasis from lung cancer.

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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