Duojiao Wu

3.0k total citations · 1 hit paper
70 papers, 1.8k citations indexed

About

Duojiao Wu is a scholar working on Molecular Biology, Immunology and Oncology. According to data from OpenAlex, Duojiao Wu has authored 70 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Molecular Biology, 24 papers in Immunology and 19 papers in Oncology. Recurrent topics in Duojiao Wu's work include Cancer Immunotherapy and Biomarkers (12 papers), Immune Cell Function and Interaction (11 papers) and Immune cells in cancer (11 papers). Duojiao Wu is often cited by papers focused on Cancer Immunotherapy and Biomarkers (12 papers), Immune Cell Function and Interaction (11 papers) and Immune cells in cancer (11 papers). Duojiao Wu collaborates with scholars based in China, United States and Australia. Duojiao Wu's co-authors include Xiangdong Wang, Xiangdong Wang, Geng Chen, Yunjin Li, Yunfeng Cheng, David E. Sanin, Fangming Liu, Qiongyu Chen, Jing Qiu and Annette Patterson and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Clinical Investigation and SHILAP Revista de lepidopterología.

In The Last Decade

Duojiao Wu

69 papers receiving 1.8k citations

Hit Papers

CD36+ cancer-associated fibroblasts provide immunosuppres... 2023 2026 2024 2025 2023 50 100 150 200

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Duojiao Wu China 24 839 561 406 405 208 70 1.8k
Max Levin Sweden 21 914 1.1× 337 0.6× 301 0.7× 321 0.8× 211 1.0× 56 1.8k
Michael Slifker United States 24 984 1.2× 389 0.7× 423 1.0× 567 1.4× 251 1.2× 54 1.9k
Lan Wang China 25 905 1.1× 367 0.7× 338 0.8× 274 0.7× 148 0.7× 74 1.8k
Peijun He United States 19 1.1k 1.4× 440 0.8× 670 1.7× 784 1.9× 258 1.2× 25 2.3k
Zhao‐Yang Lu China 23 779 0.9× 366 0.7× 387 1.0× 439 1.1× 89 0.4× 64 1.7k
Carl E. Freter United States 20 1.0k 1.2× 246 0.4× 465 1.1× 514 1.3× 224 1.1× 52 2.2k
Joan Montero Spain 20 1.4k 1.6× 284 0.5× 387 1.0× 657 1.6× 194 0.9× 43 2.3k
Claudio Celeghini Italy 26 1.3k 1.5× 621 1.1× 391 1.0× 497 1.2× 106 0.5× 73 2.3k
Feng Xie China 23 682 0.8× 403 0.7× 469 1.2× 287 0.7× 159 0.8× 86 1.6k
Tonya C. Walser United States 23 846 1.0× 473 0.8× 423 1.0× 840 2.1× 407 2.0× 41 2.1k

Countries citing papers authored by Duojiao Wu

Since Specialization
Citations

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

Fields of papers citing papers by Duojiao Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Duojiao Wu

This figure shows the co-authorship network connecting the top 25 collaborators of Duojiao Wu. A scholar is included among the top collaborators of Duojiao Wu 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 Duojiao Wu. Duojiao Wu 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.
Sun, Lu, Xiaoyan Li, Feixiang Xu, et al.. (2025). A critical role of N4-acetylation of cytidine in mRNA by NAT10 in T cell expansion and antiviral immunity. Nature Immunology. 26(4). 619–634. 6 indexed citations
2.
Wang, Han, Fangming Liu, Xiaoling Wu, et al.. (2024). Cancer-associated fibroblasts contributed to hepatocellular carcinoma recurrence and metastasis via CD36-mediated fatty-acid metabolic reprogramming. Experimental Cell Research. 435(2). 113947–113947. 23 indexed citations
3.
Liu, Fangming, Yifei Liu, Xiaoxia Liu, et al.. (2024). Deciphering the heterogeneity of neutrophil cells within circulation and the lung cancer microenvironment pre- and post-operation. Cell Biology and Toxicology. 40(1). 11–11. 1 indexed citations
4.
Zhu, Guiqi, Zheng Tang, Run Huang, et al.. (2023). CD36+ cancer-associated fibroblasts provide immunosuppressive microenvironment for hepatocellular carcinoma via secretion of macrophage migration inhibitory factor. Cell Discovery. 9(1). 25–25. 209 indexed citations breakdown →
5.
Sun, Lu, Zhouyi Chen, Fangming Liu, et al.. (2023). The immune-metabolic crosstalk between CD3+C1q+TAM and CD8+T cells associated with relapse-free survival in HCC. Frontiers in Immunology. 14. 8 indexed citations
6.
Ma, Mingyue, Ying Yang, Zhouyi Chen, et al.. (2023). T-cell senescence induced by peripheral phospholipids. Cell Biology and Toxicology. 39(6). 2937–2952. 2 indexed citations
8.
Li, Yunjin, et al.. (2020). Exploring Additional Valuable Information From Single-Cell RNA-Seq Data. Frontiers in Cell and Developmental Biology. 8. 593007–593007. 13 indexed citations
9.
Liu, Fangming, Jiahui Wang, Mingyue Ma, et al.. (2020). Chromatin accessibility of CD8 T cell differentiation and metabolic regulation. Cell Biology and Toxicology. 37(3). 367–378. 7 indexed citations
10.
Song, Dongli, Menglin Xu, Ruihua Ma, et al.. (2019). Influence of gene modification in biological behaviors and responses of mouse lung telocytes to inflammation. Journal of Translational Medicine. 17(1). 158–158. 19 indexed citations
11.
Hou, Jiayun, Lingyan Wang, & Duojiao Wu. (2017). The root of Actinidia chinensis inhibits hepatocellular carcinomas cells through LAMB3. Cell Biology and Toxicology. 34(4). 321–332. 22 indexed citations
12.
Wu, Duojiao, David E. Sanin, Bart Everts, et al.. (2016). Type 1 Interferons Induce Changes in Core Metabolism that Are Critical for Immune Function. Immunity. 44(6). 1325–1336. 254 indexed citations
13.
Xu, Jianzhong, Duojiao Wu, Yan Yang, Kaida Ji, & Pingjin Gao. (2016). Endothelial-like cells differentiated from mesenchymal stem cells attenuate neointimal hyperplasia after vascular injury. Molecular Medicine Reports. 14(5). 4830–4836. 10 indexed citations
14.
Liu, Zexian, Zhicheng Pan, Mengjia Qian, et al.. (2016). A new method for classifying different phenotypes of kidney transplantation. Cell Biology and Toxicology. 32(4). 323–332. 12 indexed citations
15.
Wu, Duojiao, Xiaoping Liu, Chen Liu, et al.. (2014). Network analysis reveals roles of inflammatory factors in different phenotypes of kidney transplant patients. Journal of Theoretical Biology. 362. 62–68. 10 indexed citations
16.
Sun, Pan, Duojiao Wu, Andrew E. Teschendorff, et al.. (2014). JAK2-Centered Interactome Hotspot Identified by an Integrative Network Algorithm in Acute Stanford Type A Aortic Dissection. PLoS ONE. 9(2). e89406–e89406. 25 indexed citations
17.
Zheng, Yonghua, Tongyu Zhu, Miao Lin, Duojiao Wu, & Xiangdong Wang. (2012). Telocytes in the urinary system. Journal of Translational Medicine. 10(1). 188–188. 73 indexed citations
18.
Kuscu, Emin, et al.. (2011). Clinical data integration of distributed data sources using Health Level Seven (HL7) v3-RIM mapping. PubMed. 1(1). 32–32. 20 indexed citations
19.
Wu, Duojiao, Bijun Zhu, & Xiangdong Wang. (2011). Metabonomics-based omics study and atherosclerosis. PubMed. 1(1). 30–30. 11 indexed citations
20.
Wu, Duojiao, Huashan Hong, & Qiong Jiang. (2005). [Effect of shexiang baoxin pill in alleviating myocardial fibrosis in spontaneous hypertensive rats].. PubMed. 25(4). 350–3. 11 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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