Zhi-Ming Shao

2.8k total citations · 1 hit paper
29 papers, 855 citations indexed

About

Zhi-Ming Shao is a scholar working on Oncology, Cancer Research and Immunology. According to data from OpenAlex, Zhi-Ming Shao has authored 29 papers receiving a total of 855 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Oncology, 15 papers in Cancer Research and 7 papers in Immunology. Recurrent topics in Zhi-Ming Shao's work include Cancer Immunotherapy and Biomarkers (9 papers), Breast Cancer Treatment Studies (7 papers) and Cancer Genomics and Diagnostics (6 papers). Zhi-Ming Shao is often cited by papers focused on Cancer Immunotherapy and Biomarkers (9 papers), Breast Cancer Treatment Studies (7 papers) and Cancer Genomics and Diagnostics (6 papers). Zhi-Ming Shao collaborates with scholars based in China, United States and United Kingdom. Zhi-Ming Shao's co-authors include Ding Ma, Yi‐Zhou Jiang, Guan-Hua Su, Yi Xiao, Ying Xu, Xin Hu, Xi Jin, Yi Xiao, Yonglin Wu and Yuan Zhou and has published in prestigious journals such as ACS Nano, PLoS ONE and Cell Metabolism.

In The Last Decade

Zhi-Ming Shao

28 papers receiving 850 citations

Hit Papers

The microbial metabolite trimethylamine N-oxide promotes ... 2022 2026 2023 2024 2022 50 100 150 200 250

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Zhi-Ming Shao China 13 376 344 215 169 136 29 855
Huimin Tian China 18 313 0.8× 448 1.3× 143 0.7× 360 2.1× 166 1.2× 34 1.0k
Н. В. Литвяков Russia 18 405 1.1× 417 1.2× 270 1.3× 154 0.9× 143 1.1× 110 955
Si-Qi Qiu China 14 303 0.8× 420 1.2× 313 1.5× 281 1.7× 161 1.2× 35 966
Nina Radosevic‐Robin France 21 528 1.4× 627 1.8× 352 1.6× 209 1.2× 223 1.6× 55 1.3k
Euphemia W. Mu United States 13 262 0.7× 449 1.3× 179 0.8× 147 0.9× 77 0.6× 31 822
Shane O’Grady Ireland 12 611 1.6× 365 1.1× 222 1.0× 81 0.5× 125 0.9× 19 996
David A. Moore United Kingdom 16 266 0.7× 337 1.0× 190 0.9× 105 0.6× 123 0.9× 30 737
Zongjuan Li China 16 384 1.0× 259 0.8× 182 0.8× 188 1.1× 189 1.4× 29 783
Antje‐Christine Walz Switzerland 15 402 1.1× 349 1.0× 84 0.4× 153 0.9× 89 0.7× 34 892

Countries citing papers authored by Zhi-Ming Shao

Since Specialization
Citations

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

Fields of papers citing papers by Zhi-Ming Shao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Zhi-Ming Shao. 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 Zhi-Ming Shao. The network helps show where Zhi-Ming Shao may publish in the future.

Co-authorship network of co-authors of Zhi-Ming Shao

This figure shows the co-authorship network connecting the top 25 collaborators of Zhi-Ming Shao. A scholar is included among the top collaborators of Zhi-Ming Shao 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 Zhi-Ming Shao. Zhi-Ming Shao 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.
Liu, Xiyu, Chao Chen, Zhiqiang Wang, et al.. (2025). MORF4L2 induces immunosuppressive microenvironment and immunotherapy resistance through GRHL2/MORF4L2/H4K12Ac/CSF1 axis in triple-negative breast cancer. Biomarker Research. 13(1). 6–6. 1 indexed citations
2.
Shao, Zhi-Ming, et al.. (2024). Intratumor heterogeneity in breast cancer: Tracing its origins and translating findings into clinical practice. 1(1). 100006–100006. 8 indexed citations
4.
Gong, Yue, Peng Ji, Huailiang Wu, et al.. (2024). Abstract PO1-14-06: Integrated analysis reveals the impact of obesity on triple-negative breast cancer. Cancer Research. 84(9_Supplement). PO1–14.
6.
Xie, Xiaoqing, Yi Yang, Qiang Wang, et al.. (2023). Targeting ATAD3A-PINK1-mitophagy axis overcomes chemoimmunotherapy resistance by redirecting PD-L1 to mitochondria. Cell Research. 33(3). 215–228. 66 indexed citations
7.
Wu, Siyu, Yujie Wang, Kairui Jin, et al.. (2023). Clinical feasibility and oncological safety of non-radioactive targeted axillary dissection after neoadjuvant chemotherapy in biopsy-proven node-positive breast cancer: a prospective diagnostic and prognostic study. International Journal of Surgery. Publish Ahead of Print(7). 1863–1870. 16 indexed citations
8.
Wu, Song‐Yang, Ding Ma, Yi Xiao, et al.. (2023). CCL19+ dendritic cells potentiate clinical benefit of anti-PD-(L)1 immunotherapy in triple-negative breast cancer. Med. 4(6). 373–393.e8. 27 indexed citations
9.
Wu, Chunyu, Guang‐Yu Liu, Xiaohong Xue, et al.. (2022). Effectiveness of the Sanyin Formula Plus Chemotherapy on Survival in Women With Triple-Negative Breast Cancer: A Randomized Controlled Trial. Frontiers in Oncology. 12. 850155–850155. 4 indexed citations
10.
Su, Guan-Hua, Lin Jiang, Yi Xiao, et al.. (2022). A Multiomics Signature Highlights Alterations Underlying Homologous Recombination Deficiency in Triple-Negative Breast Cancer. Annals of Surgical Oncology. 29(11). 7165–7175. 6 indexed citations
11.
Wang, Han, et al.. (2022). Bidirectional crosstalk between therapeutic cancer vaccines and the tumor microenvironment: Beyond tumor antigens. Fundamental Research. 3(6). 1005–1024. 12 indexed citations
12.
Ji, Peng, et al.. (2022). 23P In vivo multi-dimensional CRISPR screens identify LGALS2 as an immunotherapy target in triple-negative breast cancer. Annals of Oncology. 33. S133–S133. 1 indexed citations
13.
Chen, Chao, et al.. (2022). Identification of a novel signature with prognostic value in triple-negative breast cancer through clinico-transcriptomic analysis. Annals of Translational Medicine. 10(20). 1095–1095. 1 indexed citations
14.
Jiang, Lin, Chao You, Yi Xiao, et al.. (2022). Radiogenomic analysis reveals tumor heterogeneity of triple-negative breast cancer. Cell Reports Medicine. 3(7). 100694–100694. 60 indexed citations
15.
Wu, Song‐Yang, Ying Xu, Li Chen, et al.. (2022). Combined angiogenesis and PD-1 inhibition for immunomodulatory TNBC: concept exploration and biomarker analysis in the FUTURE-C-Plus trial. Molecular Cancer. 21(1). 84–84. 65 indexed citations
16.
Su, Guan-Hua, Yi Xiao, Lin Jiang, et al.. (2022). Radiomics features for assessing tumor-infiltrating lymphocytes correlate with molecular traits of triple-negative breast cancer. Journal of Translational Medicine. 20(1). 471–471. 44 indexed citations
17.
Yu, Tian‐Jian, Ding Ma, Yingying Liu, et al.. (2021). Bulk and single-cell transcriptome profiling reveal the metabolic heterogeneity in human breast cancers. Molecular Therapy. 29(7). 2350–2365. 84 indexed citations
19.
Yao, Ling, Kai Li, Wenting Peng, et al.. (2014). An aberrant spliced transcript of focal adhesion kinase is exclusively expressed in human breast cancer. Journal of Translational Medicine. 12(1). 136–136. 17 indexed citations
20.
Liu, Yi‐Rong, et al.. (2013). Immediate Postmastectomy Breast Reconstruction Showed Limited Advantage in Patient Survival after Stratifying by Family Income. PLoS ONE. 8(12). e82807–e82807. 9 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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