Mengquan Li

625 total citations
20 papers, 513 citations indexed

About

Mengquan Li is a scholar working on Molecular Biology, Cancer Research and Oncology. According to data from OpenAlex, Mengquan Li has authored 20 papers receiving a total of 513 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Molecular Biology, 10 papers in Cancer Research and 7 papers in Oncology. Recurrent topics in Mengquan Li's work include Cancer-related molecular mechanisms research (5 papers), Cancer Treatment and Pharmacology (3 papers) and Breast Cancer Treatment Studies (3 papers). Mengquan Li is often cited by papers focused on Cancer-related molecular mechanisms research (5 papers), Cancer Treatment and Pharmacology (3 papers) and Breast Cancer Treatment Studies (3 papers). Mengquan Li collaborates with scholars based in China and Japan. Mengquan Li's co-authors include Xu Han, Keke Miao, Liuxing Wang, Qingxia Fan, Yan Sun, Feng Wang, Weijie Zhang, Jing Su, Xu Han and Jing Su and has published in prestigious journals such as Journal of Clinical Oncology, Experimental Cell Research and Journal of Cellular Biochemistry.

In The Last Decade

Mengquan Li

19 papers receiving 506 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mengquan Li China 12 390 297 89 35 33 20 513
Qiangling Sun China 12 469 1.2× 373 1.3× 47 0.5× 36 1.0× 51 1.5× 24 594
Zongli Ding China 11 321 0.8× 214 0.7× 59 0.7× 22 0.6× 43 1.3× 18 386
Xianju Qin China 12 260 0.7× 163 0.5× 70 0.8× 31 0.9× 39 1.2× 21 401
Meiyu Dai China 13 351 0.9× 339 1.1× 63 0.7× 17 0.5× 24 0.7× 16 497
Dan Tang China 10 352 0.9× 363 1.2× 65 0.7× 44 1.3× 67 2.0× 18 533
Fang Wu China 14 431 1.1× 178 0.6× 100 1.1× 48 1.4× 46 1.4× 28 528
Thasni Karedath Qatar 12 479 1.2× 346 1.2× 109 1.2× 63 1.8× 23 0.7× 15 648
Yiqian Liang China 14 329 0.8× 148 0.5× 76 0.9× 84 2.4× 61 1.8× 34 511
Wen‐Lian Chen China 10 262 0.7× 186 0.6× 74 0.8× 34 1.0× 50 1.5× 20 419

Countries citing papers authored by Mengquan Li

Since Specialization
Citations

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

Fields of papers citing papers by Mengquan Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mengquan Li

This figure shows the co-authorship network connecting the top 25 collaborators of Mengquan Li. A scholar is included among the top collaborators of Mengquan Li 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 Mengquan Li. Mengquan Li 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.
Hu, Xin, Hiroshi Hirano, Hirotake Tsukamoto, et al.. (2021). β-glucan from Aureobasidium pullulans augments the anti-tumor immune responses through activated tumor-associated dendritic cells. International Immunopharmacology. 101(Pt A). 108265–108265. 9 indexed citations
2.
3.
Li, Mengquan, et al.. (2019). Dual-Targeting of miR-124-3p and ABCC4 Promotes Sensitivity to Adriamycin in Breast Cancer Cells. Genetic Testing and Molecular Biomarkers. 23(3). 156–165. 29 indexed citations
4.
Li, Mengquan, et al.. (2019). <p>SNHG1 contributes to proliferation and invasion by regulating miR-382 in breast cancer</p>. Cancer Management and Research. Volume 11. 5589–5598. 38 indexed citations
5.
Li, Mengquan, et al.. (2019). lncRNA GAS5‐promoted apoptosis in triple‐negative breast cancer by targeting miR‐378a‐5p/SUFU signaling. Journal of Cellular Biochemistry. 121(3). 2225–2235. 97 indexed citations
6.
Su, Jing, et al.. (2019). Overexpression of CBX2 in breast cancer promotes tumor progression through the PI3K/AKT signaling pathway.. PubMed. 11(3). 1668–1682. 49 indexed citations
7.
Su, Jing, et al.. (2019). Silencing of the long non-coding RNA RHPN1-AS1 suppresses the epithelial-to-mesenchymal transition and inhibits breast cancer progression.. PubMed. 11(6). 3505–3517. 17 indexed citations
8.
Xu, Binghe, Zhimin Shao, Shui Wang, et al.. (2018). Treatment patterns for adjuvant docetaxel-based chemotherapy in early-stage breast cancer in China: A pooled retrospective analysis of four observational studies. Chinese Journal of Cancer Research. 30(3). 327–339. 4 indexed citations
9.
Ma, Dong, Mengquan Li, Jing Su, & Shuijun Zhang. (2017). BCA3 contributes to the malignant progression of hepatocellular carcinoma through AKT activation and NF-κB translocation. Experimental Cell Research. 362(1). 142–151. 12 indexed citations
10.
Xu, Binghe, Zhimin Shao, Shui Wang, et al.. (2017). Treatment patterns and patient profiles for docetaxel-based adjuvant chemotherapy in early-stage breast cancer in China: A pooled analysis of four observational studies.. Journal of Clinical Oncology. 35(15_suppl). e12017–e12017. 1 indexed citations
11.
Han, Xu, Mengquan Li, Yue Zhou, et al.. (2015). S100A4 participates in epithelial-mesenchymal transition in breast cancer via targeting MMP2. Tumor Biology. 37(3). 2925–2932. 31 indexed citations
12.
Su, Jing, et al.. (2015). [Value of FOXP3 Tregs predicting the effectiveness of neoadjuvant chemotherapy in patients with breast cancer].. PubMed. 95(8). 595–7. 1 indexed citations
13.
Han, Xu, Yan Sun, Weijie Zhang, et al.. (2014). Critical role of miR-10b in transforming growth factor-β1-induced epithelial–mesenchymal transition in breast cancer. Cancer Gene Therapy. 21(2). 60–67. 92 indexed citations
14.
Li, Mengquan, et al.. (2013). Cellular and Molecular Mechanisms in Vascular Smooth Muscle Cells by which Total Saponin Extracted from Tribulus Terrestris Protects Against Artherosclerosis. Cellular Physiology and Biochemistry. 32(5). 1299–1308. 17 indexed citations
15.
Su, Jing, et al.. (2012). [Effects of all trans retinoic acid on the expression alterations of beta-protein 1 in human breast cancer cell lines of MDA-MB-468 and MCF-7].. PubMed. 92(31). 2219–21. 1 indexed citations
16.
Su, Jing, et al.. (2011). [Clinical comparative study of neoadjuvant chemotherapy outcome in locally advanced breast cancer: docetaxel versus paclitaxel plus pirarubicin hydrochloride and cyclophosphamide].. PubMed. 91(26). 1837–9. 2 indexed citations
17.
Fan, Y. H., Yang Yang, Qiuliang Liu, et al.. (2010). Detection and identification of potential biomarkers of breast cancer. Journal of Cancer Research and Clinical Oncology. 136(8). 1243–1254. 54 indexed citations
18.
Li, Jingruo, et al.. (2009). Expression of BI-1 protein and its significance in breast cancer. The Chinese-German Journal of Clinical Oncology. 8(3). 160–163. 3 indexed citations
19.
Li, Mengquan, et al.. (2007). Effects of ouabain on proliferation, intracellular free calcium and c-myc mRNA expression in vascular smooth muscle cells. Journal of Comparative Physiology B. 177(5). 589–595. 17 indexed citations
20.
Li, Mengquan, et al.. (2007). Expression of telomerase gene and apoptosis related genes in benign and malignant breast lesion. The Chinese-German Journal of Clinical Oncology. 6(4). 361–364.

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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