Xingxing Yu

1.4k total citations · 1 hit paper
54 papers, 1.0k citations indexed

About

Xingxing Yu is a scholar working on Immunology, Oncology and Hematology. According to data from OpenAlex, Xingxing Yu has authored 54 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Immunology, 14 papers in Oncology and 14 papers in Hematology. Recurrent topics in Xingxing Yu's work include Immune Cell Function and Interaction (20 papers), Hematopoietic Stem Cell Transplantation (11 papers) and T-cell and B-cell Immunology (9 papers). Xingxing Yu is often cited by papers focused on Immune Cell Function and Interaction (20 papers), Hematopoietic Stem Cell Transplantation (11 papers) and T-cell and B-cell Immunology (9 papers). Xingxing Yu collaborates with scholars based in China, United States and Sweden. Xingxing Yu's co-authors include Ying Wang, Yi Zhou, Yanchun Li, Jing Du, Xiangmin Tong, Qiaojuan Zhu, Weidong Sun, Tongtong Wang, Weimin Fan and Yi‐Long Wu and has published in prestigious journals such as SHILAP Revista de lepidopterología, Blood and The Journal of Immunology.

In The Last Decade

Xingxing Yu

48 papers receiving 1.0k citations

Hit Papers

DHA inhibits proliferatio... 2018 2026 2020 2023 2018 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Xingxing Yu China 15 365 330 295 292 247 54 1.0k
Yasuhisa Yokoyama Japan 19 401 1.1× 301 0.9× 185 0.6× 135 0.5× 130 0.5× 108 1.2k
Jinghe Li China 20 511 1.4× 141 0.4× 269 0.9× 131 0.4× 232 0.9× 58 976
Xiaojiang Wu China 24 560 1.5× 564 1.7× 721 2.4× 721 2.5× 288 1.2× 75 2.1k
Jun Liang China 24 550 1.5× 138 0.4× 402 1.4× 316 1.1× 285 1.2× 104 1.8k
Xingguo Song China 23 982 2.7× 98 0.3× 219 0.7× 139 0.5× 760 3.1× 59 1.3k
Yuqiang Ji China 15 405 1.1× 256 0.8× 179 0.6× 37 0.1× 274 1.1× 46 883
Aurora Castellano Italy 23 484 1.3× 457 1.4× 621 2.1× 131 0.4× 321 1.3× 64 1.6k
Ming Jin China 20 643 1.8× 201 0.6× 452 1.5× 225 0.8× 351 1.4× 79 1.5k
Chika Iwamoto Japan 18 357 1.0× 316 1.0× 449 1.5× 83 0.3× 152 0.6× 41 1.0k
Jianming Zheng China 22 627 1.7× 137 0.4× 378 1.3× 166 0.6× 452 1.8× 86 1.5k

Countries citing papers authored by Xingxing Yu

Since Specialization
Citations

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

Fields of papers citing papers by Xingxing Yu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xingxing Yu

This figure shows the co-authorship network connecting the top 25 collaborators of Xingxing Yu. A scholar is included among the top collaborators of Xingxing Yu 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 Xingxing Yu. Xingxing Yu 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.
Zhou, Hui, Jie Zhou, Shuman Jia, et al.. (2025). Therapeutic Activation of PPARα Inhibits Transformed Follicular Lymphoma Tumorigenesis via the FOXM1 Signaling Pathway. International Journal of Biological Sciences. 21(12). 5411–5427.
2.
Yu, Xingxing, et al.. (2025). Innovative gene targeted treatments for osteosarcoma: a mini review of current clinical evidence and future prospects. Frontiers in Medicine. 12. 1699287–1699287.
3.
Liu, Xuefei, Zhou Tong, Long Liu, et al.. (2025). Overexpressing natural killer group 2 member A drives natural killer cell exhaustion in relapsed acute myeloid leukemia. Signal Transduction and Targeted Therapy. 10(1). 143–143. 5 indexed citations
4.
Zhang, Yining, Yueting Huang, Hong Yan, et al.. (2024). Lactate acid promotes PD-1+ Tregs accumulation in the bone marrow with high tumor burden of Acute myeloid leukemia. International Immunopharmacology. 130. 111765–111765. 15 indexed citations
5.
Lin, Feng, Xingxing Yu, Caiyan Wang, et al.. (2024). Changes of T cell subsets across treatments associated with prognosis in newly diagnosed follicular lymphoma. Scientific Reports. 14(1). 27576–27576.
6.
Zhao, Dongbing, et al.. (2024). Association of the SNPs in CCL2 and CXCL12 genes with the susceptibility to breast cancer: a case-control study in China. Frontiers in Oncology. 14. 1475979–1475979. 1 indexed citations
7.
Lin, Yuxiang, et al.. (2023). Genetic and lifestyle factors for breast cancer risk assessment in Southeast China. Cancer Medicine. 12(14). 15504–15514. 2 indexed citations
8.
Zhong, Mengya, et al.. (2023). High-Throughput Drug Screen for Potential Combinations With Venetoclax Guides the Treatment of Transformed Follicular Lymphoma. International Journal of Toxicology. 42(5). 386–406. 1 indexed citations
9.
Yu, Xingxing, Zhengli Xu, Yu‐Hong Chen, et al.. (2023). Expanded clinical-grade NK cells exhibit stronger effects than primary NK cells against HCMV infection. Cellular and Molecular Immunology. 20(8). 895–907. 9 indexed citations
11.
Yu, Xingxing, Xuefei Liu, Mei He, et al.. (2022). Donor NKG2C homozygosity contributes to CMV clearance after haploidentical transplantation. JCI Insight. 7(3). 14 indexed citations
12.
Wang, Xiang, Xingxing Yu, Zeying Fan, et al.. (2021). Donor activating killer cell immunoglobulin‐like receptors genes correlated with Epstein–Barr virus reactivation after haploidentical haematopoietic stem cell transplantation. British Journal of Haematology. 196(4). 1007–1017. 5 indexed citations
13.
Tian, Yue, et al.. (2021). Detailed numerical simulation and experimental investigation on micromixers with serpentine Koch fractal microchannels. International Journal of Modern Physics B. 35(22). 2 indexed citations
15.
Yu, Xingxing, et al.. (2021). Research Progress on Treatment of Ulcerative Colitis with Baitouweng Decoction. Journal of Clinical and Nursing Research. 5(4). 204–208. 1 indexed citations
16.
Fei, Qinglin, et al.. (2020). Serum biomarker CD163 predicts overall survival in patients with pancreatic ductal adenocarcinoma. SHILAP Revista de lepidopterología. 3(3). 147–153. 1 indexed citations
17.
Zhao, Xiang‐Yu, Xuying Pei, Ying‐Jun Chang, et al.. (2019). First-line Therapy With Donor-derived Human Cytomegalovirus (HCMV)–specific T Cells Reduces Persistent HCMV Infection by Promoting Antiviral Immunity After Allogenic Stem Cell Transplantation. Clinical Infectious Diseases. 70(7). 1429–1437. 32 indexed citations
18.
Cui, Lei, et al.. (2019). The relationship between cognitive function and having diabetes in patients treated with hemodialysis. International Journal of Nursing Sciences. 7(1). 60–65. 6 indexed citations
19.
Hu, Lijuan, Xingxing Yu, Xuefei Liu, et al.. (2019). NK cell reconstitution following unmanipulated HLA-mismatched/haploidentical transplantation compared with matched sibling transplantation. Science China Life Sciences. 63(5). 781–784. 6 indexed citations
20.
Zhao, Xiaosu, Xiaosu Zhao, Xingxing Yu, et al.. (2018). The impact of donor characteristics on the invariant natural killer T cells of granulocyte-colony-stimulating factor-mobilized marrow grafts and peripheral blood grafts. Transplant Immunology. 48. 55–59. 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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