Junhao Mu

615 total citations
23 papers, 442 citations indexed

About

Junhao Mu is a scholar working on Molecular Biology, Pulmonary and Respiratory Medicine and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Junhao Mu has authored 23 papers receiving a total of 442 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Molecular Biology, 8 papers in Pulmonary and Respiratory Medicine and 4 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Junhao Mu's work include Epigenetics and DNA Methylation (12 papers), Cancer-related gene regulation (10 papers) and Wnt/β-catenin signaling in development and cancer (7 papers). Junhao Mu is often cited by papers focused on Epigenetics and DNA Methylation (12 papers), Cancer-related gene regulation (10 papers) and Wnt/β-catenin signaling in development and cancer (7 papers). Junhao Mu collaborates with scholars based in China, Hong Kong and United States. Junhao Mu's co-authors include Tingxiu Xiang, Weiyan Peng, Guosheng Ren, Qian Tao, Lili Li, Yixiao Feng, Xiang Qin, Jun Tang, Le Xin and Xiaoqian He and has published in prestigious journals such as SHILAP Revista de lepidopterología, Oncogene and Cellular and Molecular Life Sciences.

In The Last Decade

Junhao Mu

23 papers receiving 436 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Junhao Mu China 14 333 119 71 67 42 23 442
Chenfeng Wang China 13 259 0.8× 144 1.2× 70 1.0× 58 0.9× 41 1.0× 25 387
Ye Hu China 11 224 0.7× 96 0.8× 80 1.1× 75 1.1× 45 1.1× 19 374
Julian Musa Germany 8 334 1.0× 136 1.1× 113 1.6× 108 1.6× 39 0.9× 18 500
Chandrika Jeyamohan United States 6 224 0.7× 145 1.2× 89 1.3× 52 0.8× 35 0.8× 9 358
Byul A Jee South Korea 10 303 0.9× 128 1.1× 59 0.8× 60 0.9× 40 1.0× 10 445
Qiqi Shi China 9 322 1.0× 161 1.4× 89 1.3× 34 0.5× 57 1.4× 16 458
Wolong Zhou China 12 304 0.9× 157 1.3× 96 1.4× 79 1.2× 52 1.2× 21 427
Nicola Inzerilli Italy 5 302 0.9× 120 1.0× 99 1.4× 77 1.1× 30 0.7× 8 420
Yongsheng Li China 8 238 0.7× 151 1.3× 84 1.2× 56 0.8× 85 2.0× 14 385

Countries citing papers authored by Junhao Mu

Since Specialization
Citations

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

Fields of papers citing papers by Junhao Mu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Junhao Mu

This figure shows the co-authorship network connecting the top 25 collaborators of Junhao Mu. A scholar is included among the top collaborators of Junhao Mu 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 Junhao Mu. Junhao Mu 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.
Lan, Jie, Jing Huang, Weiyi Li, et al.. (2025). MoLPre: A Machine Learning Model to Predict Metastasis of cT1 Solid Lung Cancer. Clinical and Translational Science. 18(4). e70186–e70186. 1 indexed citations
2.
3.
Mu, Junhao, Kaiming Kuang, Min Ao, et al.. (2023). Deep learning predicts malignancy and metastasis of solid pulmonary nodules from CT scans. Frontiers in Medicine. 10. 1145846–1145846. 5 indexed citations
4.
He, Chunyan, Yishi Li, Rui Xiao, et al.. (2023). Recombinant Slit2 attenuates tracheal fibroblast activation in benign central airway obstruction by inhibiting the TGF-β1/Smad3 signaling pathway. Molecular and Cellular Probes. 73. 101947–101947. 1 indexed citations
5.
Gu, Lei, Chunyan He, Rui Xiao, et al.. (2023). Profibrotic role of the SOX9–MMP10–ECM biosynthesis axis in the tracheal fibrosis after injury and repair. Genes & Diseases. 11(5). 101040–101040. 1 indexed citations
6.
Gu, Lei, Junhao Mu, Yishi Li, et al.. (2023). GATA6 triggers fibroblast activation and tracheal fibrosis through the Wnt/β-catenin pathway. Cellular Signalling. 105. 110593–110593. 7 indexed citations
7.
Mu, Junhao, et al.. (2023). Advances in diagnosis and prediction for aggression of pure solid T1 lung cancer. Precision Clinical Medicine. 6(3). pbad020–pbad020. 6 indexed citations
8.
Mu, Junhao, et al.. (2022). Artificial intelligence assisted discrimination between pulmonary tuberculous nodules and solid lung cancer nodules. SHILAP Revista de lepidopterología. 5. 100–105. 1 indexed citations
9.
Li, Li, Jun Tang, Lili Li, et al.. (2022). ZBTB28 inhibits breast cancer by activating IFNAR and dual blocking CD24 and CD47 to enhance macrophages phagocytosis. Cellular and Molecular Life Sciences. 79(2). 83–83. 20 indexed citations
10.
Li, Li, Junhao Mu, Fan Wu, et al.. (2022). Disruption of ZNF334 promotes triple-negative breast carcinoma malignancy through the SFRP1/ Wnt/β-catenin signaling axis. Cellular and Molecular Life Sciences. 79(5). 280–280. 14 indexed citations
11.
Tang, Jun, Weiyan Peng, Yixiao Feng, et al.. (2021). Cancer cells escape p53’s tumor suppression through ablation of ZDHHC1-mediated p53 palmitoylation. Oncogene. 40(35). 5416–5426. 30 indexed citations
12.
He, Xiaoqian, Le Xin, Jialin Chen, et al.. (2021). Multiple targeted self-emulsifying compound RGO reveals obvious anti-tumor potential in hepatocellular carcinoma. Molecular Therapy — Oncolytics. 22. 604–616. 19 indexed citations
13.
Li, Li, Ke Xu, Weihong Chen, et al.. (2021). ZBTB28 induces autophagy by regulation of FIP200 and Bcl-XL facilitating cervical cancer cell apoptosis. Journal of Experimental & Clinical Cancer Research. 40(1). 150–150. 20 indexed citations
14.
Xin, Le, Junhao Mu, Weiyan Peng, et al.. (2020). DNA methylation downregulated ZDHHC1 suppresses tumor growth by altering cellular metabolism and inducing oxidative/ER stress-mediated apoptosis and pyroptosis. Theranostics. 10(21). 9495–9511. 80 indexed citations
15.
Yu, Fan, Junhao Mu, Mingquan Huang, et al.. (2019). Epigenetic Identification of ADCY4 as a Biomarker for Breast Cancer: an Integrated Analysis of Adenylate Cyclases. Epigenomics. 11(14). 1561–1579. 21 indexed citations
16.
Qin, Xiang, Xiaoqian He, Junhao Mu, et al.. (2019). The phosphoinositide hydrolase phospholipase C delta1 inhibits epithelial‐mesenchymal transition and is silenced in colorectal cancer. Journal of Cellular Physiology. 234(8). 13906–13916. 13 indexed citations
17.
Zhang, Yan, Junhao Mu, Xiaoqian He, et al.. (2018). TET1 exerts its anti-tumor functions via demethylating DACT2 and SFRP2 to antagonize Wnt/β-catenin signaling pathway in nasopharyngeal carcinoma cells. Clinical Epigenetics. 10(1). 103–103. 27 indexed citations
18.
19.
Mu, Junhao, Lili Li, Zhenfang Du, et al.. (2017). Dickkopf-related protein 2 induces G0/G1 arrest and apoptosis through suppressing Wnt/β-catenin signaling and is frequently methylated in breast cancer. Oncotarget. 8(24). 39443–39459. 28 indexed citations
20.
Yin, Xuedong, Tingxiu Xiang, Junhao Mu, et al.. (2016). Protocadherin 17 functions as a tumor suppressor suppressing Wnt/β-catenin signaling and cell metastasis and is frequently methylated in breast cancer. Oncotarget. 7(32). 51720–51732. 48 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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