Pingqing Tan

937 total citations
27 papers, 641 citations indexed

About

Pingqing Tan is a scholar working on Molecular Biology, Oncology and Cancer Research. According to data from OpenAlex, Pingqing Tan has authored 27 papers receiving a total of 641 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Molecular Biology, 7 papers in Oncology and 7 papers in Cancer Research. Recurrent topics in Pingqing Tan's work include Cancer-related gene regulation (8 papers), Cancer-related molecular mechanisms research (6 papers) and RNA modifications and cancer (4 papers). Pingqing Tan is often cited by papers focused on Cancer-related gene regulation (8 papers), Cancer-related molecular mechanisms research (6 papers) and RNA modifications and cancer (4 papers). Pingqing Tan collaborates with scholars based in China, Saudi Arabia and United States. Pingqing Tan's co-authors include Yuanzheng Qiu, Donghai Huang, Junjun Li, Yongquan Tian, Mei Yi, Jing Cai, Yixin Tan, Bo Xiang, Guiyuan Li and Xiayu Li and has published in prestigious journals such as Journal of Clinical Oncology, Cellular and Molecular Life Sciences and European Journal of Cancer.

In The Last Decade

Pingqing Tan

25 papers receiving 640 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Pingqing Tan China 13 460 300 105 65 61 27 641
Ulrike Hopfer Germany 9 288 0.6× 172 0.6× 112 1.1× 30 0.5× 63 1.0× 11 532
Baoxin Qian China 9 345 0.8× 221 0.7× 113 1.1× 43 0.7× 13 0.2× 18 512
Yanmei Cui China 13 450 1.0× 333 1.1× 138 1.3× 28 0.4× 17 0.3× 16 641
Zengli Liu China 16 444 1.0× 253 0.8× 210 2.0× 240 3.7× 22 0.4× 48 739
Leilei Tao China 11 407 0.9× 306 1.0× 358 3.4× 51 0.8× 21 0.3× 18 765
Yu Yin China 13 329 0.7× 254 0.8× 106 1.0× 47 0.7× 12 0.2× 30 525
Weimin Mao China 12 335 0.7× 272 0.9× 93 0.9× 72 1.1× 30 0.5× 28 558
Tamako Konkin United States 7 319 0.7× 213 0.7× 233 2.2× 126 1.9× 32 0.5× 8 762
Stéphane Flamant France 14 393 0.9× 265 0.9× 122 1.2× 44 0.7× 31 0.5× 29 721
Fang Zhu China 14 428 0.9× 251 0.8× 214 2.0× 29 0.4× 19 0.3× 41 692

Countries citing papers authored by Pingqing Tan

Since Specialization
Citations

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

Fields of papers citing papers by Pingqing Tan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pingqing Tan

This figure shows the co-authorship network connecting the top 25 collaborators of Pingqing Tan. A scholar is included among the top collaborators of Pingqing Tan 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 Pingqing Tan. Pingqing Tan 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.
Tan, Pingqing, et al.. (2023). Tolerance limit of external beam radiotherapy combined with low-dose rate brachytherapy in normal rabbit tissue. Journal of Radiation Research. 64(4). 651–660.
3.
He, Zhiying, Yitao Mao, Shanhong Lu, et al.. (2022). Machine learning–based radiomics for histological classification of parotid tumors using morphological MRI: a comparative study. European Radiology. 32(12). 8099–8110. 24 indexed citations
4.
Lu, Shanhong, Juan Chen, Yan Gao, et al.. (2022). MRI-based radiomics analysis for preoperative evaluation of lymph node metastasis in hypopharyngeal squamous cell carcinoma. Frontiers in Oncology. 12. 936040–936040. 8 indexed citations
5.
Chen, Juan, Shanhong Lu, Yitao Mao, et al.. (2021). An MRI-based radiomics-clinical nomogram for the overall survival prediction in patients with hypopharyngeal squamous cell carcinoma: a multi-cohort study. European Radiology. 32(3). 1548–1557. 29 indexed citations
6.
He, Yanjuan, Chao Liu, Li Guo, et al.. (2020). miR-93-5p enhances migration and invasion by targeting RGMB in squamous cell carcinoma of the head and neck. Journal of Cancer. 11(13). 3871–3881. 29 indexed citations
7.
Yi, Mei, Yixin Tan, Li Wang, et al.. (2020). TP63 links chromatin remodeling and enhancer reprogramming to epidermal differentiation and squamous cell carcinoma development. Cellular and Molecular Life Sciences. 77(21). 4325–4346. 60 indexed citations
8.
Guo, Li, Xiyu Chen, Chao Liu, et al.. (2019). Wnt3a protein overexpression predicts worse overall survival in laryngeal squamous cell carcinoma. Journal of Cancer. 10(19). 4633–4638. 8 indexed citations
9.
Guo, Li, Xiyu Chen, Chao Liu, et al.. (2019). Wnt3a promotes radioresistance via autophagy in squamous cell carcinoma of the head and neck. Journal of Cellular and Molecular Medicine. 23(7). 4711–4722. 36 indexed citations
10.
Wang, Juncheng, Yuexiang Qin, Gangcai Zhu, et al.. (2019). High serum CCL18 predicts a poor prognosis in patients with laryngeal squamous cell carcinoma. Journal of Cancer. 10(27). 6910–6914. 7 indexed citations
11.
Guo, Li, Chao Liu, Shanhong Lu, et al.. (2019). miR‐30e‐5p represses angiogenesis and metastasis by directly targeting AEG‐1 in squamous cell carcinoma of the head and neck. Cancer Science. 111(2). 356–368. 40 indexed citations
12.
Zhu, Gangcai, Li She, Ming Wei, et al.. (2017). MiR-98 inhibits malignant progression via targeting MTDH in squamous cell carcinoma of the head and neck.. PubMed. 7(12). 2554–2565. 23 indexed citations
13.
Tan, Pingqing, et al.. (2015). [Application of improved submental island flap in hypopharyngeal cancer reserved laryngeal function surgery].. PubMed. 29(15). 1342–5. 1 indexed citations
14.
15.
Wang, Yunyun, Yong Liu, Li Guo, et al.. (2014). Ephrin type-A receptor 2 regulates sensitivity to paclitaxel in nasopharyngeal carcinoma via the phosphoinositide 3-kinase/Akt signalling pathway. Molecular Medicine Reports. 11(2). 924–930. 11 indexed citations
16.
Tan, Pingqing, Yong Liu, Zhongwu Su, et al.. (2012). EphA2 silencing in nasopharyngeal carcinoma leads to decreased proliferation, invasion and increased sensitization to paclitaxel. Oncology Letters. 4(3). 429–434. 10 indexed citations
17.
Guo, Ying, Yong Liu, Pingqing Tan, et al.. (2012). [Expressions and clinical significance of high mobility group box-1 mRNA and protein in laryngeal squamous cell carcinoma tissues and serum].. PubMed. 47(6). 487–90. 3 indexed citations
18.
Qi, Lin, Ping Wu, Xin Zhang, et al.. (2011). Inhibiting ERp29 expression enhances radiosensitivity in human nasopharyngeal carcinoma cell lines. Medical Oncology. 29(2). 721–728. 27 indexed citations
19.
Huang, Donghai, Yong Liu, Lijun Liu, et al.. (2011). Analysis of Transcriptional Factors and Regulation Networks in Laryngeal Squamous Cell Carcinoma Patients with Lymph Node Metastasis. Journal of Proteome Research. 11(2). 1100–1107. 11 indexed citations
20.
Liu, Yong, Xin Zhang, Donghai Huang, et al.. (2010). Elevated expression of HMGB1 in squamous-cell carcinoma of the head and neck and its clinical significance. European Journal of Cancer. 46(16). 3007–3015. 68 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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