Mingzi Tan

794 citations
28 papers · 615 · h-index 16

Impact in

Papers in

    • Glycosylation and Glycoproteins Research 3
    • S100 Proteins and Annexins 3
    • Signaling Pathways in Disease 2

Mingzi Tan

27 papers receiving 609 citations

Peers

Mingzi Tan
Comparison fields: 5 of 65
  • Reproductive Medicine 145
  • Cancer Research 176
  • Immunology 160
  • Obstetrics and Gynecology 57
  • Molecular Biology 339
Replace Rui Gou with:
Rui Gou China
Evangelos Bournakis Greece
Gemma Toledo Spain
Shogo Shigeta Japan
Steven W. Remmenga United States
Sofia Genta Canada
Yuexin Hu China
Assaad Semaan United States
Phil Rolland United Kingdom
Sundersingh Shirley India
Mingzi Tan relative to Rui Gou China Rui Gou's profile →
Citations per field
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Citations per year

Countries citing papers authored by Mingzi Tan

Since Specialization
Citations

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

Fields of papers citing papers by Mingzi Tan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Mingzi Tan, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Mingzi Tan Line = papers co-authored together Mingzi Tan links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 28 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201564
2 201458
3 201447
4 201543
5 201541
6
Membranous expressions of Lewis y and CAM-DR-related markers are independent factors of chemotherapy resistance and poor prognosis in epithelial ovarian cancer.
201537
7 201532
8 201431
9 201430
10
Lewis Y antigen modified CD47 is an independent risk factor for poor prognosis and promotes early ovarian cancer metastasis.
201528
11 201427
12 201520
13 201618
14 202017
15 201316
16 202016
17 201715
18 201414
19 201714
20 201511

About Mingzi Tan

Mingzi Tan is a scholar working on Molecular Biology, Oncology, Reproductive Medicine, Cancer Research and Immunology, having authored 28 papers that have together received 615 indexed citations. Recurring topics across this work include Ovarian cancer diagnosis and treatment (7 papers), Galectins and Cancer Biology (3 papers), Glycosylation and Glycoproteins Research (3 papers), S100 Proteins and Annexins (3 papers), Autophagy in Disease and Therapy (3 papers), Signaling Pathways in Disease (2 papers), Phagocytosis and Immune Regulation (2 papers) and Cancer, Lipids, and Metabolism (2 papers). The work is most often cited by research in Reproductive Medicine (145 citations), Cancer Research (176 citations), Immunology (160 citations), Obstetrics and Gynecology (57 citations) and Molecular Biology (339 citations). Mingzi Tan has collaborated with scholars based in China, United States and Germany. Frequent co-authors include Bei Lin, Juanjuan Liu, Liancheng Zhu, Zhenhua Hu, Jian Gao, Huiyu Zhuang, Dawo Liu, Mingbo Cai, Yingying Hao and Huimin Wang. Their work appears in journals such as Oncology Reports, International Journal of Molecular Sciences, Tumor Biology, Oncotarget and Journal of Experimental & Clinical Cancer Research.

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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