Qingqing Mo

429 total citations
12 papers, 175 citations indexed

About

Qingqing Mo is a scholar working on Molecular Biology, Oncology and Cell Biology. According to data from OpenAlex, Qingqing Mo has authored 12 papers receiving a total of 175 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 4 papers in Oncology and 3 papers in Cell Biology. Recurrent topics in Qingqing Mo's work include Ubiquitin and proteasome pathways (3 papers), Microtubule and mitosis dynamics (3 papers) and Cancer, Hypoxia, and Metabolism (2 papers). Qingqing Mo is often cited by papers focused on Ubiquitin and proteasome pathways (3 papers), Microtubule and mitosis dynamics (3 papers) and Cancer, Hypoxia, and Metabolism (2 papers). Qingqing Mo collaborates with scholars based in China, Hong Kong and Spain. Qingqing Mo's co-authors include Pingbo Chen, Ding Ma, Qinglei Gao, Xin Jin, Beibei Wang, Yue Gao, Yuan Wu, Peng Wu, Yong Fang and Gang Chen and has published in prestigious journals such as PLoS ONE, Cell Death and Disease and Clinical & Experimental Immunology.

In The Last Decade

Qingqing Mo

11 papers receiving 174 citations

Peers

Qingqing Mo

MB

CR

ONCOL

CB

IMMUN

Hamed Yari Australia

Sahar Mazhar United States

Edward Grimley United States

Trupti Lingaraj United States

Thippeswamy Gulappa United States

Dominika Czaplińska Poland

Rushil Desai United States

Boer Deng China

Hamed Yari Australia

Qingqing Mo

135 ×1.1

MB

41 ×0.7

CR

43 ×1.1

ONCOL

23 ×0.8

CB

28 ×1.5

IMMUN

Citations per year, relative to Qingqing Mo Qingqing Mo (= 1×) peers Hamed Yari

Countries citing papers authored by Qingqing Mo

Since Specialization

Citations

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

Fields of papers citing papers by Qingqing Mo

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Qingqing Mo

This figure shows the co-authorship network connecting the top 25 collaborators of Qingqing Mo. A scholar is included among the top collaborators of Qingqing Mo 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 Qingqing Mo. Qingqing Mo is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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12 of 12 papers shown

1.

Ni, Jie, et al.. (2024). Hydrothermal variations of active layer in permafrost regions and the influence of vegetation in the Qinghai-Tibetan Plateau. Theoretical and Applied Climatology. 156(1).

2.

Wu, Yuan, Yue Gao, Lingxi Chen, et al.. (2021). Prognostic implications of tumour-infiltrating lymphocytes for recurrence in epithelial ovarian cancer. Clinical & Experimental Immunology. 206(1). 36–46. 4 indexed citations

3.

Chen, Pingbo, Beibei Wang, Qingqing Mo, et al.. (2019). The LIV-1-GRPEL1 axis adjusts cell fate during anti-mitotic agent-damaged mitosis. EBioMedicine. 49. 26–39. 5 indexed citations

4.

Han, Yingyan, Peng Wu, Zhi Wang, et al.. (2019). Ubiquinol-cytochrome C reductase core protein II promotes tumorigenesis by facilitating p53 degradation. EBioMedicine. 40. 92–105. 13 indexed citations

5.

Ma, Xiaoli, Jia Liu, Qingqing Mo, et al.. (2017). Targeting CD146 in combination with vorinostat for the treatment of ovarian cancer cells. Oncology Letters. 13(3). 1681–1687. 17 indexed citations

6.

Liu, Jia, Yingyan Han, Pingbo Chen, et al.. (2017). Loss of the novel mitochondrial protein FAM210B promotes metastasis via PDK4-dependent metabolic reprogramming. Cell Death and Disease. 8(6). e2870–e2870. 44 indexed citations

7.

Jin, Xin, Qingqing Mo, Yu Zhang, et al.. (2016). The p38 MAPK inhibitor BIRB796 enhances the antitumor effects of VX680 in cervical cancer. Cancer Biology & Therapy. 17(5). 566–576. 36 indexed citations

8.

Mo, Qingqing, Yu Zhang, Xin Jin, et al.. (2016). Geldanamycin, an inhibitor of Hsp90, increases paclitaxel-mediated toxicity in ovarian cancer cells through sustained activation of the p38/H2AX axis. Tumor Biology. 37(11). 14745–14755. 14 indexed citations

9.

Ma, Xiaoli, et al.. (2014). Effect of LIV1 on the sensitivity of ovarian cancer cells to trichostatin A. Oncology Reports. 33(2). 893–898. 4 indexed citations

10.

Mo, Qingqing, Pingbo Chen, Xin Jin, et al.. (2013). Inhibition of Hec1 expression enhances the sensitivity of human ovarian cancer cells to paclitaxel. Acta Pharmacologica Sinica. 34(4). 541–548. 15 indexed citations

11.

Tian, Yuan, Wencheng Ding, Yingying Wang, et al.. (2013). Ubiquitin B in Cervical Cancer: Critical for the Maintenance of Cancer Stem-Like Cell Characters. PLoS ONE. 8(12). e84457–e84457. 16 indexed citations

12.

Chen, Pingbo, Qingqing Mo, Beibei Wang, et al.. (2012). Breast cancer associated fibroblasts promote MCF-7 invasion in vitro by secretion of HGF. Journal of Huazhong University of Science and Technology [Medical Sciences]. 32(1). 92–96. 7 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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