Naijun Han

1.2k total citations
31 papers, 689 citations indexed

About

Naijun Han is a scholar working on Molecular Biology, Cancer Research and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Naijun Han has authored 31 papers receiving a total of 689 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Molecular Biology, 11 papers in Cancer Research and 5 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Naijun Han's work include RNA modifications and cancer (7 papers), Cancer-related molecular mechanisms research (5 papers) and Cancer, Hypoxia, and Metabolism (4 papers). Naijun Han is often cited by papers focused on RNA modifications and cancer (7 papers), Cancer-related molecular mechanisms research (5 papers) and Cancer, Hypoxia, and Metabolism (4 papers). Naijun Han collaborates with scholars based in China, United Kingdom and United States. Naijun Han's co-authors include Yanning Gao, Ting Xiao, Shujun Cheng, Xuebing Di, Kaitai Zhang, Suping Guo, Wenyue Sun, Ying Ma, Dongmei Lin and Lin Feng and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and JNCI Journal of the National Cancer Institute.

In The Last Decade

Naijun Han

31 papers receiving 680 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Naijun Han China 15 400 222 202 111 83 31 689
Antònia Obrador‐Hevia Spain 15 440 1.1× 141 0.6× 214 1.1× 104 0.9× 29 0.3× 25 676
Magdalena M. Grabowska United States 14 333 0.8× 114 0.5× 135 0.7× 231 2.1× 30 0.4× 19 602
Guoyu Yu United States 16 408 1.0× 193 0.9× 315 1.6× 195 1.8× 22 0.3× 39 779
Jupeng Yuan China 18 633 1.6× 275 1.2× 139 0.7× 82 0.7× 27 0.3× 31 837
Anna Aspesi Italy 19 743 1.9× 85 0.4× 177 0.9× 109 1.0× 61 0.7× 36 1.1k
Marian L. Burr United Kingdom 11 541 1.4× 110 0.5× 116 0.6× 38 0.3× 88 1.1× 13 860
Anjian Xu China 18 547 1.4× 167 0.8× 173 0.9× 107 1.0× 17 0.2× 53 941
Yeon-Su Lee South Korea 18 495 1.2× 218 1.0× 191 0.9× 189 1.7× 24 0.3× 42 827
Junshan Hao United States 7 299 0.7× 94 0.4× 103 0.5× 141 1.3× 32 0.4× 8 538
Anuhar Chaturvedi Germany 18 665 1.7× 167 0.8× 127 0.6× 50 0.5× 25 0.3× 33 1.1k

Countries citing papers authored by Naijun Han

Since Specialization
Citations

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

Fields of papers citing papers by Naijun Han

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Naijun Han

This figure shows the co-authorship network connecting the top 25 collaborators of Naijun Han. A scholar is included among the top collaborators of Naijun 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 Naijun Han. Naijun 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.
Ge, Shengqiang, Jin Cui, Naijun Han, et al.. (2024). Thoughts on the research of African swine fever live-attenuated vaccines. Vaccine. 42(25). 126052–126052. 7 indexed citations
2.
Wang, Zhenzhong, Shengqiang Ge, Yongxin Hu, et al.. (2022). Genetic variation and evolution of attenuated African swine fever virus strain isolated in the field. Virus Research. 319. 198874–198874. 26 indexed citations
3.
Wang, Minghui, Lin Feng, Ping Li, et al.. (2016). [Hsp90AB1 Protein is Overexpressed in Non-small Cell Lung Cancer Tissues 
and Associated with Poor Prognosis in Lung Adenocarcinoma Patients].. SHILAP Revista de lepidopterología. 19(2). 64–9. 14 indexed citations
4.
Cao, Bangrong, Lin Feng, Dan Lü, et al.. (2016). Prognostic value of molecular events from negative surgical margin of non-small-cell lung cancer. Oncotarget. 8(32). 53642–53653. 10 indexed citations
5.
Zhang, Susu, Jinjing Tan, Lin Li, et al.. (2016). [Up-regulation of DLK1 in non-small cell lung cancer and the relevant molecular mechanism].. PubMed. 38(7). 510–4. 1 indexed citations
6.
Cao, Yan, Yu Liu, Xin Yang, et al.. (2015). Estimation of the Survival of Patients With Lung Squamous Cell Carcinoma Using Genomic Copy Number Aberrations. Clinical Lung Cancer. 17(1). 68–74.e5. 1 indexed citations
7.
8.
Li, Lin, Ying Zhang, Ning Li, et al.. (2014). Nidogen-1: a candidate biomarker for ovarian serous cancer. Japanese Journal of Clinical Oncology. 45(2). 176–182. 22 indexed citations
9.
Li, Lin, Jinjing Tan, Ying E. Zhang, et al.. (2014). DLK1 Promotes Lung Cancer Cell Invasion through Upregulation of MMP9 Expression Depending on Notch Signaling. PLoS ONE. 9(3). e91509–e91509. 57 indexed citations
10.
Li, Meng, Ting Xiao, Jinjing Tan, et al.. (2014). Sp1 transcriptionally regulates BRK1 expression in non-small cell lung cancer cells. Gene. 542(2). 134–140. 5 indexed citations
11.
Zhou, Xin‐Fu, Ying Zhang, Naijun Han, et al.. (2013). [α-Enolase (ENO1) inhibits epithelial-mesenchymal transition in the A549 cell line
by suppressing ERK1/2 phosphorylation].. SHILAP Revista de lepidopterología. 16(5). 221–6. 7 indexed citations
12.
Zheng, Hongwei, Guobin Fu, Jingsong Yuan, et al.. (2012). Suppression of non-small cell lung cancer proliferation and tumorigenicity by DENND2D. Lung Cancer. 79(2). 104–110. 17 indexed citations
13.
Liu, Yu, Dongmei Lin, Ting Xiao, et al.. (2011). An immunohistochemical analysis‐based decision tree model for estimating the risk of lymphatic metastasis in pN0 squamous cell carcinomas of the lung. Histopathology. 59(5). 882–891. 7 indexed citations
14.
Liu, Yu, Lin Li, Shuo Li, et al.. (2010). Study on the Molecular Mechanisms of dlk1 Stimulated Lung Cancer Cell Proliferation. SHILAP Revista de lepidopterología. 1 indexed citations
15.
Zhang, Ying, Min Li, Yu Liu, et al.. (2010). ENO1 Protein Levels in the Tumor Tissues and Circulating Plasma Samples of Non-small Cell Lung Cancer Patients. SHILAP Revista de lepidopterología. 6 indexed citations
16.
Li, Min, Ting Xiao, Ying Zhang, et al.. (2010). Prognostic significance of matrix metalloproteinase-1 levels in peripheral plasma and tumour tissues of lung cancer patients. Lung Cancer. 69(3). 341–347. 49 indexed citations
17.
Li, Lin, Yu Liu, Minghui Wei, et al.. (2010). [DNA microarrays-based microRNA expression profiles derived from formalin-fixed paraffin-embedded tissue blocks of squammous cell carcinoma of larynx].. PubMed. 39(6). 391–5. 7 indexed citations
18.
Cai, Xiongwei, Ting Xiao, Sharon Y. James, et al.. (2009). Metastatic potential of lung squamous cell carcinoma associated with HSPC300 through its interaction with WAVE2. Lung Cancer. 65(3). 299–305. 17 indexed citations
19.
Yuan, Jingsong, Jinfang Ma, Hongwei Zheng, et al.. (2008). Overexpression of OLC1, Cigarette Smoke, and Human Lung Tumorigenesis. JNCI Journal of the National Cancer Institute. 100(22). 1592–1605. 19 indexed citations
20.
Liu, Yan, Wenyue Sun, Kaitai Zhang, et al.. (2007). Identification of genes differentially expressed in human primary lung squamous cell carcinoma. Lung Cancer. 56(3). 307–317. 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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