Zhimin Shao

5.7k total citations
96 papers, 1.3k citations indexed

About

Zhimin Shao is a scholar working on Cancer Research, Oncology and Molecular Biology. According to data from OpenAlex, Zhimin Shao has authored 96 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 45 papers in Cancer Research, 43 papers in Oncology and 25 papers in Molecular Biology. Recurrent topics in Zhimin Shao's work include Breast Cancer Treatment Studies (36 papers), Estrogen and related hormone effects (16 papers) and HER2/EGFR in Cancer Research (14 papers). Zhimin Shao is often cited by papers focused on Breast Cancer Treatment Studies (36 papers), Estrogen and related hormone effects (16 papers) and HER2/EGFR in Cancer Research (14 papers). Zhimin Shao collaborates with scholars based in China, United Kingdom and United States. Zhimin Shao's co-authors include Jiong Wu, Joseph A. Fontana, Anton M. Jetten, Zhenzhou Shen, Peirong Yu, Ying Chen, Jiong Wu, Clara Nervi, Gen‐Hong Di and Jingyi Cheng and has published in prestigious journals such as Journal of Biological Chemistry, Journal of Clinical Oncology and SHILAP Revista de lepidopterología.

In The Last Decade

Zhimin Shao

90 papers receiving 1.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Zhimin Shao China 19 506 449 409 189 170 96 1.3k
Woo Chul Noh South Korea 22 467 0.9× 479 1.1× 516 1.3× 204 1.1× 106 0.6× 89 1.3k
Massimiliano D’Aiuto Italy 22 449 0.9× 453 1.0× 563 1.4× 184 1.0× 144 0.8× 78 1.4k
Neill Patani United Kingdom 26 612 1.2× 625 1.4× 442 1.1× 81 0.4× 148 0.9× 60 1.5k
Cuizhi Geng China 24 689 1.4× 579 1.3× 579 1.4× 141 0.7× 62 0.4× 133 1.6k
Marc Díez Spain 6 459 0.9× 431 1.0× 510 1.2× 98 0.5× 85 0.5× 15 1.1k
Angel Rodriguez United States 21 494 1.0× 609 1.4× 770 1.9× 193 1.0× 109 0.6× 49 1.4k
Jong Han Yu South Korea 22 499 1.0× 576 1.3× 859 2.1× 196 1.0× 105 0.6× 61 1.5k
Eileen P. Connolly United States 20 364 0.7× 354 0.8× 298 0.7× 180 1.0× 39 0.2× 68 1.2k
Eun‐Kyu Kim South Korea 24 443 0.9× 819 1.8× 637 1.6× 244 1.3× 193 1.1× 114 1.7k
Han‐Byoel Lee South Korea 20 723 1.4× 956 2.1× 782 1.9× 199 1.1× 128 0.8× 134 1.9k

Countries citing papers authored by Zhimin Shao

Since Specialization
Citations

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

Fields of papers citing papers by Zhimin Shao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zhimin Shao

This figure shows the co-authorship network connecting the top 25 collaborators of Zhimin Shao. A scholar is included among the top collaborators of Zhimin 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 Zhimin Shao. Zhimin 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
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Liu, Yinan, Liang Tang, Zhimin Shao, et al.. (2025). Gastric cancer adapts high lipid microenvironment via suppressing PPARG-FABP1 axis after arriving in the lymph node. Redox Biology. 85. 103759–103759. 1 indexed citations
3.
Liu, Yanling, Zhongshao Chen, Zhimin Shao, et al.. (2025). Spliceosomal GTPase EFTUD2 mediates DDX41 intron retention to promote the malignant progression of ovarian cancer. British Journal of Cancer. 133(4). 508–523.
4.
Zhang, Xiaomeng, Li Zhang, Shi Wei, et al.. (2024). Post-mastectomy hypofractionated versus conventionally fractionated radiation therapy for patients receiving immediate breast reconstruction: Subgroup analysis of a phase III randomized trial. Clinical and Translational Radiation Oncology. 50. 100882–100882. 1 indexed citations
5.
O’Shaughnessy, Joyce, P. Schmid, Zhimin Shao, et al.. (2024). 436TiP DYNASTY-Breast02: A phase III trial of BNT323/DB-1303 vs investigator's choice chemotherapy in HER2-low, hormone receptor positive, metastatic breast cancer. Annals of Oncology. 35. S403–S403. 1 indexed citations
6.
Chen, Jiajian, Shuang Hao, Bingqiu Xiu, et al.. (2023). Abstract P1-05-31: A single center retrospective analysis of 259 cases of metaplastic breast cancer. Cancer Research. 83(5_Supplement). P1–5. 1 indexed citations
7.
Jin, Meng, Xiaomeng Zhang, Li Zhang, et al.. (2023). The Role of Radiotherapy for Patients with Unresectable Locally Advanced Breast Cancer following Neoadjuvant Systemic Therapy. Journal of Oncology. 2023. 1–10. 5 indexed citations
8.
Wang, Xuanyi, Kairui Jin, Jurui Luo, et al.. (2022). Molecular subtypes predict second breast events of ductal carcinoma in situ after breast‐conserving surgery. Cancer Medicine. 11(14). 2755–2766. 3 indexed citations
9.
Wuerstlein, Rachel, Peter Ellis, Filippo Montemurro, et al.. (2022). Final results of the global and Asia cohorts of KAMILLA, a phase IIIB safety trial of trastuzumab emtansine in patients with HER2-positive advanced breast cancer. ESMO Open. 7(5). 100561–100561. 14 indexed citations
10.
Li, Xiaoqiang, Miao Mo, Fei Wu, et al.. (2018). Artificial neural network models based on questionnaire survey for prediction of breast cancer risk among Chinese women in Shanghai. Tumori. 38(9). 883–893. 3 indexed citations
11.
Wu, Siyu, Miao Mo, Yujie Wang, et al.. (2016). Local recurrence following mastectomy and autologous breast reconstruction: incidence, risk factors, and management. OncoTargets and Therapy. Volume 9. 6829–6834. 9 indexed citations
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Tripathy, Debu, Aditya Bardia, Sara A. Hurvitz, et al.. (2015). Phase III, randomized, double-blind, placebo-controlled study of ribociclib (LEE011) in combination with either tamoxifen and goserelin or a non-steroidal aromatase inhibitor (NSAI) and goserelin for the treatment of premenopausal women with HR+, HER2- advanced breast cancer (aBC): MONALEESA-7.. Journal of Clinical Oncology. 33. 6 indexed citations
14.
Mo, Miao, Ying Zheng, Guang‐Yu Liu, et al.. (2015). [Cost-effectiveness analysis of two breast cancer screening modalities in Shanghai, China].. PubMed. 37(12). 944–51. 3 indexed citations
15.
Jia, Xiaoqing, Hong Qi, Jingyi Cheng, et al.. (2015). Indispensability of Chemotherapy in Estrogen Receptor–Negative Early Breast Cancer in Elderly Women with Diabetes Mellitus. Diabetes Technology & Therapeutics. 17(4). 248–254. 1 indexed citations
16.
Sun, Sanyuan, Lili Tang, Jian Zhang, et al.. (2014). Cisplatin improves antitumor activity of weekly nab-paclitaxel in patients with metastatic breast cancer. SHILAP Revista de lepidopterología. 1 indexed citations
17.
Chen, Xingxing, Xiaoli Yu, Jiayi Chen, et al.. (2013). Analysis in early stage triple‐negative breast cancer treated with mastectomy without adjuvant radiotherapy: Patterns of failure and prognostic factors. Cancer. 119(13). 2366–2374. 26 indexed citations
18.
19.
Jiang, Yiwei, Liheng Zhou, Tingting Yan, et al.. (2010). Association of sulfotransferase SULT1A1 with breast cancer risk: a meta-analysis of case-control studies with subgroups of ethnic and menopausal statue. Journal of Experimental & Clinical Cancer Research. 29(1). 101–101. 16 indexed citations
20.
Shao, Zhimin, et al.. (2001). [Establishment and characterization of human inflammatory breast carcinoma neoplasm transplantation in nude mice].. PubMed. 39(10). 796–8. 2 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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