Changfei Mao

461 total citations
12 papers, 364 citations indexed

About

Changfei Mao is a scholar working on Molecular Biology, Oncology and Cancer Research. According to data from OpenAlex, Changfei Mao has authored 12 papers receiving a total of 364 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 7 papers in Oncology and 6 papers in Cancer Research. Recurrent topics in Changfei Mao's work include DNA Repair Mechanisms (3 papers), HER2/EGFR in Cancer Research (3 papers) and Effects and risks of endocrine disrupting chemicals (2 papers). Changfei Mao is often cited by papers focused on DNA Repair Mechanisms (3 papers), HER2/EGFR in Cancer Research (3 papers) and Effects and risks of endocrine disrupting chemicals (2 papers). Changfei Mao collaborates with scholars based in China, South Korea and Bangladesh. Changfei Mao's co-authors include Jinhai Tang, Jian Wu, He-Da Zhang, Haixia Cao, Dawei Sun, Wei Chen, Ling Mao, Meng Cui, Rong Ma and Zhuo Wang and has published in prestigious journals such as Nature Communications, Toxicology and Breast Cancer Research and Treatment.

In The Last Decade

Changfei Mao

11 papers receiving 359 citations

Peers

Changfei Mao
Stacy L. Gelhaus United States
Jeong-Woo Kang South Korea
Bonnie Sharratt United States
S Asami Japan
Ivana Velic Germany
M. C. Liu United States
Changfei Mao
Citations per year, relative to Changfei Mao Changfei Mao (= 1×) peers Masako Muguruma

Countries citing papers authored by Changfei Mao

Since Specialization
Citations

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

Fields of papers citing papers by Changfei Mao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Changfei Mao

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

All Works

12 of 12 papers shown
1.
Yun, Wen, Changfei Mao, & Yuan Yuan. (2025). E2F7 transcriptionally upregulates SPC24 to mediate aerobic Glycolysis and facilitate stemness of breast cancer. Journal of Bioenergetics and Biomembranes. 57(4-5). 303–313.
2.
Sheng, Yuan, et al.. (2024). Combined transcriptome and proteome analysis reveals MSN and ARFIP2 as biomarkers for trastuzumab resistance of breast cancer. Breast Cancer Research and Treatment. 207(1). 187–201. 2 indexed citations
3.
Zhu, Ying, Zhixian Liu, Changfei Mao, et al.. (2023). Inhibition of CXorf56 promotes PARP inhibitor-induced cytotoxicity in triple-negative breast cancer. npj Breast Cancer. 9(1). 34–34. 3 indexed citations
4.
Zhang, Wenjun, Feifei Xu, Yao Jiang, et al.. (2023). Single-cell metabolic fingerprints discover a cluster of circulating tumor cells with distinct metastatic potential. Nature Communications. 14(1). 2485–2485. 34 indexed citations
5.
Mao, Changfei, et al.. (2022). Circulating metabolites serve as diagnostic biomarkers for HER2‐positive breast cancer and have predictive value for trastuzumab therapy outcomes. Journal of Clinical Laboratory Analysis. 36(2). e24212–e24212. 13 indexed citations
6.
Yang, Ting, Ziyi Fu, Yin Zhang, et al.. (2020). Serum proteomics analysis of candidate predictive biomarker panel for the diagnosis of trastuzumab-based therapy resistant breast cancer. Biomedicine & Pharmacotherapy. 129. 110465–110465. 22 indexed citations
7.
Zhang, He-Da, Linhong Jiang, Junchen Hou, et al.. (2018). Circular RNA Hsa_Circ_0072995 Promotes Breast Cancer Cell Migration and Invasion Through Sponge for Mir-30c-2-3p. Epigenomics. 10(9). 1229–1242. 58 indexed citations
8.
Qian, Wenyi, Yixin Wang, Jingying Zhu, et al.. (2015). The toxic effects of Bisphenol A on the mouse spermatocyte GC‐2 cell line: the role of the Ca2+‐calmodulin‐Ca2+/calmodulin‐dependent protein kinase II axis. Journal of Applied Toxicology. 35(11). 1271–1277. 26 indexed citations
9.
Sun, Dawei, He-Da Zhang, Ling Mao, et al.. (2015). Luteolin Inhibits Breast Cancer Development and Progression In Vitro and In Vivo by Suppressing Notch Signaling and Regulating MiRNAs. Cellular Physiology and Biochemistry. 37(5). 1693–1711. 122 indexed citations
10.
Zhu, Ying, Changfei Mao, Jian Wu, et al.. (2014). Improved ataxia telangiectasia mutated kinase inhibitor KU60019 provides a promising treatment strategy for non-invasive breast cancer. Oncology Letters. 8(5). 2043–2048. 14 indexed citations
11.
Mao, Changfei, et al.. (2014). Association between the XRCC3 Thr241Met Polymorphism and Breast Cancer Risk: an Updated Meta-analysis of 36 Case-control Studies. Asian Pacific Journal of Cancer Prevention. 15(16). 6613–6618. 16 indexed citations
12.
Qian, Wenyi, Jingying Zhu, Changfei Mao, et al.. (2014). Involvement of CaM-CaMKII-ERK in bisphenol A-induced Sertoli cell apoptosis. Toxicology. 324. 27–34. 54 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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