Haiyan Xing

1.7k total citations
85 papers, 1.2k citations indexed

About

Haiyan Xing is a scholar working on Molecular Biology, Oncology and Hematology. According to data from OpenAlex, Haiyan Xing has authored 85 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 46 papers in Molecular Biology, 35 papers in Oncology and 33 papers in Hematology. Recurrent topics in Haiyan Xing's work include Acute Myeloid Leukemia Research (28 papers), CAR-T cell therapy research (23 papers) and Immune Cell Function and Interaction (15 papers). Haiyan Xing is often cited by papers focused on Acute Myeloid Leukemia Research (28 papers), CAR-T cell therapy research (23 papers) and Immune Cell Function and Interaction (15 papers). Haiyan Xing collaborates with scholars based in China and United States. Haiyan Xing's co-authors include Qing Rao, Jianxiang Wang, Min Wang, Tian Zheng, Kejing Tang, Yingxi Xu, Saisai Li, Ying Wang, Jia Liu and Yingchang Mi and has published in prestigious journals such as Blood, Journal of Molecular Biology and Cancer Research.

In The Last Decade

Haiyan Xing

78 papers receiving 1.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Haiyan Xing China 22 626 591 380 323 153 85 1.2k
Francis Mussai United Kingdom 18 510 0.8× 438 0.7× 591 1.6× 296 0.9× 128 0.8× 40 1.4k
Kevin Rouault‐Pierre United Kingdom 17 335 0.5× 520 0.9× 337 0.9× 550 1.7× 128 0.8× 37 1.2k
Yuki Kagoya Japan 18 944 1.5× 687 1.2× 574 1.5× 304 0.9× 246 1.6× 53 1.6k
Sanfang Tu China 16 582 0.9× 297 0.5× 201 0.5× 166 0.5× 154 1.0× 52 858
Frédéric Barabé Canada 20 286 0.5× 732 1.2× 348 0.9× 416 1.3× 78 0.5× 38 1.3k
Herschel Wallen United States 7 713 1.1× 580 1.0× 715 1.9× 107 0.3× 145 0.9× 7 1.4k
Brigitte Gerhard Canada 11 288 0.5× 385 0.7× 238 0.6× 419 1.3× 94 0.6× 13 855
Hind Medyouf Germany 13 298 0.5× 526 0.9× 220 0.6× 247 0.8× 41 0.3× 23 976
Xiaojian Zhu China 18 426 0.7× 535 0.9× 163 0.4× 162 0.5× 99 0.6× 68 959
Leo D. Wang United States 13 396 0.6× 336 0.6× 330 0.9× 170 0.5× 116 0.8× 25 924

Countries citing papers authored by Haiyan Xing

Since Specialization
Citations

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

Fields of papers citing papers by Haiyan Xing

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Haiyan Xing

This figure shows the co-authorship network connecting the top 25 collaborators of Haiyan Xing. A scholar is included among the top collaborators of Haiyan Xing 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 Haiyan Xing. Haiyan Xing 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.
Yu, Hong, Wenbing Liu, Junping Zhang, et al.. (2025). The Clinical and Molecular Characterization of Distinct Subtypes in Adult T Cell Acute Lymphoblastic Leukemia. Cancer Science. 116(4). 1126–1138.
2.
Xing, Haiyan, Wenbing Liu, Runxia Gu, et al.. (2025). U2AF1 mutation causes an oxidative stress and DNA repair defect in hematopoietic and leukemic cells. Free Radical Biology and Medicine. 228. 379–391.
3.
Xing, Haiyan, Wenbing Liu, Jiayuan Chen, et al.. (2025). The critical role of DNA damage‐inducible transcript 4 ( DDIT4 ) in stemness character of leukemia cells and leukemia initiation. Molecular Oncology. 19(11). 3156–3174.
4.
Chen, Yujie, Haiyan Xing, Rui Feng, et al.. (2024). Nanobody Mediated Atrazine Resistance in Plants. Journal of Agricultural and Food Chemistry. 72(29). 16368–16377. 2 indexed citations
5.
6.
Rao, Qing, Haiyan Xing, Runxia Gu, et al.. (2024). Targeting Fatty Acid Metabolism Abrogates the Differentiation Blockade in Preleukemic Cells. Cancer Research. 84(24). 4233–4245. 5 indexed citations
7.
Liu, Wenbing, Xiaoyu Liu, Shangshang Wang, et al.. (2024). Identifying ADGRG1 as a specific marker for tumor-reactive T cells in acute myeloid leukemia. Experimental Hematology and Oncology. 13(1). 92–92. 1 indexed citations
8.
Yan, Zhifeng, Runxia Gu, Haotian Ma, et al.. (2024). A dual-targeting approach with anti-IL10R CAR-T cells engineered to release anti-CD33 bispecific antibody in enhancing killing effect on acute myeloid leukemia cells. Cellular Oncology. 47(5). 1879–1895. 6 indexed citations
9.
Zhang, Yu, Saisai Li, Ying Wang, et al.. (2022). A novel and efficient CD22 CAR-T therapy induced a robust antitumor effect in relapsed/refractory leukemia patients when combined with CD19 CAR-T treatment as a sequential therapy. Experimental Hematology and Oncology. 11(1). 15–15. 23 indexed citations
10.
Xu, Yingxi, Qing Rao, Haiyan Xing, et al.. (2021). Targeting of IL-10R on acute myeloid leukemia blasts with chimeric antigen receptor-expressing T cells. Blood Cancer Journal. 11(8). 144–144. 27 indexed citations
11.
12.
Li, Yihui, Zhe Liu, Huan Li, et al.. (2019). Mitochondrial dysfunction and oxidative stress in bone marrow stromal cells induced by daunorubicin leads to DNA damage in hematopoietic cells. Free Radical Biology and Medicine. 146. 211–221. 16 indexed citations
13.
Li, Saisai, Yingxi Xu, Jia Liu, et al.. (2018). CD33-Specific Chimeric Antigen Receptor T Cells with Different Co-Stimulators Showed Potent Anti-Leukemia Efficacy and Different Phenotype. Human Gene Therapy. 29(5). 626–639. 61 indexed citations
14.
Xu, Yingxi, Saisai Li, Ying Wang, et al.. (2018). Induced CD20 Expression on B-Cell Malignant Cells Heightened the Cytotoxic Activity of Chimeric Antigen Receptor Engineered T Cells. Human Gene Therapy. 30(4). 497–510. 22 indexed citations
15.
Liu, Jia, Wenting Lu, Shuang Liu, et al.. (2018). ZFP36L2, a novel AML1 target gene, induces AML cells apoptosis and inhibits cell proliferation. Leukemia Research. 68. 15–21. 11 indexed citations
16.
Xu, Yingxi, Jia Liu, Ying Wang, et al.. (2017). Regulatory T Cells Promote the Stemness of Acute Myeloid Leukemia Cells through IL10 Cytokine Related Signaling Pathway. Blood. 130. 2727–2727. 3 indexed citations
17.
Qiu, Shaowei, Shuang Liu, Tengteng Yu, et al.. (2017). Sertad1 antagonizes iASPP function by hindering its entrance into nuclei to interact with P53 in leukemic cells. BMC Cancer. 17(1). 795–795. 2 indexed citations
18.
Wang, Jiying, Pei Yu, Shuying Chen, et al.. (2013). Activation of Rac1 GTPase promotes leukemia cell chemotherapy resistance, quiescence and niche interaction. Molecular Oncology. 7(5). 907–916. 35 indexed citations
19.
Wang, Cuicui, Cuiping Zhang, Qihui Li, et al.. (2012). Metformin induces differentiation in acute promyelocytic leukemia by activating the MEK/ERK signaling pathway. Biochemical and Biophysical Research Communications. 422(3). 398–404. 26 indexed citations
20.
Wang, Yang, Haiyan Xing, Tian Zheng, et al.. (2009). Overexpression of Midkine promotes the viability of BA/F3 cells. Biochemical and Biophysical Research Communications. 384(3). 341–346. 5 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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