Zhenyi Jin

518 total citations
35 papers, 363 citations indexed

About

Zhenyi Jin is a scholar working on Immunology, Oncology and Hematology. According to data from OpenAlex, Zhenyi Jin has authored 35 papers receiving a total of 363 indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Immunology, 15 papers in Oncology and 9 papers in Hematology. Recurrent topics in Zhenyi Jin's work include Immune Cell Function and Interaction (21 papers), T-cell and B-cell Immunology (13 papers) and CAR-T cell therapy research (12 papers). Zhenyi Jin is often cited by papers focused on Immune Cell Function and Interaction (21 papers), T-cell and B-cell Immunology (13 papers) and CAR-T cell therapy research (12 papers). Zhenyi Jin collaborates with scholars based in China, United States and Germany. Zhenyi Jin's co-authors include Xiuli Wu, Yangqiu Li, A. Jefferson Offutt, Shaohua Chen, Jing Lai, Ling Xu, Yun Zhao, Lijian Yang, Xianfeng Zha and Xueyun Zhong and has published in prestigious journals such as SHILAP Revista de lepidopterología, Blood and Scientific Reports.

In The Last Decade

Zhenyi Jin

34 papers receiving 361 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Zhenyi Jin China 12 240 155 73 52 34 35 363
Chinmoy K Bose India 10 27 0.1× 41 0.3× 30 0.4× 79 1.5× 8 0.2× 32 300
Jens Eberlein United States 9 224 0.9× 63 0.4× 9 0.1× 114 2.2× 16 408
Shuxin Huang China 13 184 0.8× 174 1.1× 74 1.0× 98 1.9× 28 362
Kenrick Semple United States 11 297 1.2× 108 0.7× 139 1.9× 54 1.0× 16 454
Biljana Smiljanovic Germany 9 158 0.7× 65 0.4× 41 0.6× 103 2.0× 17 313
Sylvia Chien United States 8 50 0.2× 68 0.4× 142 1.9× 131 2.5× 25 366
Claire Jennings United Kingdom 10 312 1.3× 27 0.2× 17 0.2× 230 4.4× 14 677
Tupitsyn Nn Russia 7 50 0.2× 87 0.6× 46 0.6× 43 0.8× 74 195
Ana Isabel Mendes Portugal 10 57 0.2× 34 0.2× 33 0.5× 69 1.3× 15 329

Countries citing papers authored by Zhenyi Jin

Since Specialization
Citations

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

Fields of papers citing papers by Zhenyi Jin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zhenyi Jin

This figure shows the co-authorship network connecting the top 25 collaborators of Zhenyi Jin. A scholar is included among the top collaborators of Zhenyi Jin 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 Zhenyi Jin. Zhenyi Jin 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.
Jiang, Siyuan, Shiyu Zheng, Chao Yao, et al.. (2025). Heterogeneity of γδ T-cell subsets and their clinical correlation in patients with AML. Frontiers in Immunology. 16. 1552235–1552235.
2.
Yu, Xibao, et al.. (2024). CD69 is a Promising Immunotherapy and Prognosis Prediction Target in Cancer. ImmunoTargets and Therapy. Volume 13. 1–14. 14 indexed citations
3.
Chen, Junjie, Chao Yao, Xiaodan Luo, et al.. (2024). Higher TIGIT+ γδ TCM cells may predict poor prognosis in younger adult patients with non-acute promyelocytic AML. Frontiers in Immunology. 15. 1321126–1321126. 5 indexed citations
4.
Yin, Ran, et al.. (2024). Utilizing exosomes as sparking clinical biomarkers and therapeutic response in acute myeloid leukemia. Frontiers in Immunology. 14. 1315453–1315453. 7 indexed citations
5.
Jiang, Xuan, et al.. (2023). The ectonucleotidases CD39 and CD73 on T cells: The new pillar of hematological malignancy. Frontiers in Immunology. 14. 1110325–1110325. 25 indexed citations
6.
Yang, Wentao, et al.. (2023). Identification of immune infiltration-related biomarkers in carotid atherosclerotic plaques. Scientific Reports. 13(1). 14153–14153. 6 indexed citations
7.
Jiang, Xuan, et al.. (2022). High TRGV 9 Subfamily Expression Marks an Improved Overall Survival in Patients With Acute Myeloid Leukemia. Frontiers in Immunology. 13. 823352–823352. 4 indexed citations
8.
Qiu, Dan, et al.. (2022). TIGIT axis: novel immune checkpoints in anti-leukemia immunity. Clinical and Experimental Medicine. 23(2). 165–174. 15 indexed citations
9.
Qiu, Dan, Xuan Jiang, Yun Zhao, et al.. (2022). Increased PD-1+Foxp3+ γδ T cells associate with poor overall survival for patients with acute myeloid leukemia. Frontiers in Oncology. 12. 1007565–1007565. 8 indexed citations
10.
Chen, Cunte, Yongsheng Li, Zhenyi Jin, et al.. (2021). Higher Expression of WT1 With Lower CD58 Expression may be Biomarkers for Risk Stratification of Patients With Cytogenetically Normal Acute Myeloid Leukemia. Technology in Cancer Research & Treatment. 20. 2203794040–2203794040. 7 indexed citations
11.
Xu, Ling, Lian Liu, Danlin Yao, et al.. (2021). PD-1 and TIGIT Are Highly Co-Expressed on CD8+ T Cells in AML Patient Bone Marrow. Frontiers in Oncology. 11. 686156–686156. 31 indexed citations
12.
Yao, Danlin, Ling Xu, Jing Lai, et al.. (2020). Increased Expression of TIGIT/CD57 in Peripheral Blood/Bone Marrow NK Cells in Patients with Chronic Myeloid Leukemia. BioMed Research International. 2020(1). 9531549–9531549. 14 indexed citations
13.
Jin, Zhenyi, Yun Zhao, Jie Chen, et al.. (2020). Higher TIGIT + CD226 - γδ T cells in Patients with Acute Myeloid Leukemia. Immunological Investigations. 51(1). 40–50. 34 indexed citations
14.
Jin, Zhenyi, Yun Zhao, Jie Chen, et al.. (2020). Characteristic of TIGIT and DNAM‐1 Expression on Foxp3+ γδ T Cells in AML Patients. BioMed Research International. 2020(1). 4612952–4612952. 29 indexed citations
15.
Xu, Yan, Ling Xu, Cunte Chen, et al.. (2020). Age‐Related Immune Profile of the T Cell Receptor Repertoire, Thymic Recent Output Function, and miRNAs. BioMed Research International. 2020(1). 5910823–5910823. 13 indexed citations
16.
Jin, Zhenyi, Ling Xu, & Yangqiu Li. (2018). Approaches for generation of anti-leukemia specific T cells. Cell Regeneration. 7(2). 40–44. 2 indexed citations
17.
Xu, Ling, Yuhong Lu, Jing Lai, et al.. (2015). Characteristics of the TCR Vβ repertoire in imatinib-resistant chronic myeloid leukemia patients with ABL mutations. Science China Life Sciences. 58(12). 1276–1281. 11 indexed citations
18.
Jin, Zhenyi, Xiuli Wu, Shaohua Chen, et al.. (2014). Distribution and Clonality of the Vα and Vβ T-Cell Receptor Repertoire of Regulatory T Cells in Leukemia Patients With and Without Graft Versus Host Disease. DNA and Cell Biology. 33(3). 182–188. 9 indexed citations
19.
Jin, Zhenyi & A. Jefferson Offutt. (2002). Integration testing based on software couplings. 13–23. 9 indexed citations
20.
Jin, Zhenyi & Soo Young Yang. (1990). Activation of CD8+ T cells by allogeneic class II‐deficient B‐cell lines derived from patients with bare lymphocyte syndrome. Tissue Antigens. 35(3). 136–143. 1 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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