Fang Zhao

3.1k total citations
57 papers, 1.8k citations indexed

About

Fang Zhao is a scholar working on Immunology, Molecular Biology and Oncology. According to data from OpenAlex, Fang Zhao has authored 57 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Immunology, 24 papers in Molecular Biology and 21 papers in Oncology. Recurrent topics in Fang Zhao's work include Immunotherapy and Immune Responses (16 papers), Immune Cell Function and Interaction (8 papers) and CAR-T cell therapy research (7 papers). Fang Zhao is often cited by papers focused on Immunotherapy and Immune Responses (16 papers), Immune Cell Function and Interaction (8 papers) and CAR-T cell therapy research (7 papers). Fang Zhao collaborates with scholars based in China, Germany and United States. Fang Zhao's co-authors include Dirk Schadendorf, Annette Paschen, Wenjing Luo, Tongjian Cai, Zipeng Cao, Yi Zhang, Michael Aschner, Jianbin Zhang, Antje Sucker and Wenkai Jiang and has published in prestigious journals such as The Journal of Experimental Medicine, Blood and The Journal of Immunology.

In The Last Decade

Fang Zhao

55 papers receiving 1.8k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Fang Zhao China 23 746 733 557 370 169 57 1.8k
Anthos Christofides United States 10 663 0.9× 879 1.2× 545 1.0× 268 0.7× 111 0.7× 21 1.7k
Kimberly J. Krager United States 19 990 1.3× 362 0.5× 255 0.5× 213 0.6× 179 1.1× 42 2.1k
Annalisa Camporeale Italy 21 617 0.8× 466 0.6× 389 0.7× 183 0.5× 88 0.5× 28 1.4k
Govind Gawdi United States 23 828 1.1× 242 0.3× 230 0.4× 318 0.9× 139 0.8× 37 1.6k
Baisakhi Raychaudhuri United States 22 501 0.7× 622 0.8× 302 0.5× 174 0.5× 109 0.6× 28 1.6k
Norifumi Urao United States 26 1.1k 1.5× 439 0.6× 210 0.4× 240 0.6× 99 0.6× 49 2.3k
Brian M. Necela United States 24 1.1k 1.4× 366 0.5× 691 1.2× 592 1.6× 110 0.7× 52 2.2k
Fatouma Alimirah United States 25 851 1.1× 362 0.5× 296 0.5× 290 0.8× 142 0.8× 32 1.9k
Uma Kant Misra United States 23 1.2k 1.6× 367 0.5× 195 0.4× 264 0.7× 290 1.7× 49 2.2k
Hua You China 23 605 0.8× 262 0.4× 313 0.6× 282 0.8× 76 0.4× 70 1.5k

Countries citing papers authored by Fang Zhao

Since Specialization
Citations

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

Fields of papers citing papers by Fang Zhao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Fang Zhao

This figure shows the co-authorship network connecting the top 25 collaborators of Fang Zhao. A scholar is included among the top collaborators of Fang Zhao 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 Fang Zhao. Fang Zhao 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.
Hua, Yichao, et al.. (2025). SeuratExtend: streamlining single-cell RNA-seq analysis through an integrated and intuitive framework. GigaScience. 14. 6 indexed citations
2.
Xiao, Nan, Fang Zhao, Jizhou Gou, et al.. (2025). Comparing acute versus AIDS ART initiation on HIV-1 integration sites and clonal expansion. Signal Transduction and Targeted Therapy. 10(1). 23–23. 1 indexed citations
3.
Liu, Mengjie, Chaofan Li, Jingkun Qu, et al.. (2023). Baicalein enhances immune response in TNBC by inhibiting leptin expression of adipocytes. Cancer Science. 114(10). 3834–3847. 12 indexed citations
4.
Zaremba, Anne, Antje Sucker, Gennadiy Zelinskyy, et al.. (2023). HLA Class II Loss and JAK1/2 Deficiency Coevolve in Melanoma Leading to CD4 T-cell and IFNγ Cross-Resistance. Clinical Cancer Research. 29(15). 2894–2907. 9 indexed citations
5.
Sun, Wei, Kunyan Liu, Hongyu Zhou, et al.. (2023). Whole-exome sequencing reveals mutational profiles of anorectal and gynecological melanoma. Medical Oncology. 40(11). 330–330. 5 indexed citations
6.
Wang, Jing, et al.. (2023). Sirt3 regulates NLRP3 and participates in the effects of plantainoside D on acute lung injury sepsis. Aging. 15(14). 6710–6720. 5 indexed citations
7.
Yang, Wanlin, Jiefang Huang, Miao Xiang, et al.. (2021). Inhibition of Dot1L Alleviates Fulminant Hepatitis Through Myeloid-Derived Suppressor Cells. Cellular and Molecular Gastroenterology and Hepatology. 12(1). 81–98. 3 indexed citations
8.
Chauvistré, Heike, Pietro Crivello, Katharina Fleischhauer, et al.. (2021). Melanoma Differentiation Trajectories Determine Sensitivity toward Pre-Existing CD8+ Tumor-Infiltrating Lymphocytes. Journal of Investigative Dermatology. 141(10). 2480–2489. 7 indexed citations
9.
10.
Fang, Liang, Fang Zhao, Stephen Iwanowycz, et al.. (2019). Anticancer activity of emodin is associated with downregulation of CD155. International Immunopharmacology. 75. 105763–105763. 22 indexed citations
11.
Shi, Hongbing, et al.. (2018). Tanshinone IIA inhibits cervix carcinoma stem cells migration and invasion via inhibiting YAP transcriptional activity. Biomedicine & Pharmacotherapy. 105. 758–765. 26 indexed citations
12.
Zhao, Fang, Antje Sucker, Susanne Horn, et al.. (2016). Melanoma Lesions Independently Acquire T-cell Resistance during Metastatic Latency. Cancer Research. 76(15). 4347–4358. 57 indexed citations
13.
Sucker, Antje, Fang Zhao, Birgit Real, et al.. (2014). Genetic Evolution of T-cell Resistance in the Course of Melanoma Progression. Clinical Cancer Research. 20(24). 6593–6604. 127 indexed citations
14.
Cai, Tongjian, Honglei Che, Tao Yu, et al.. (2014). The changes of miRNA expression in rat hippocampus following chronic lead exposure. Toxicology Letters. 229(1). 158–166. 54 indexed citations
15.
Zhang, Yi, Yi Zhang, Wei Cai, et al.. (2013). Mesenchymal Stem Cells Alleviate Bacteria-Induced Liver Injury in Mice by Inducing Regulatory Dendritic Cells. Hepatology. 59(2). 671–682. 106 indexed citations
16.
Zhao, Fang, et al.. (2013). MicroRNA-34a regulates high glucose-induced apoptosis in H9c2 cardiomyocytes. Journal of Huazhong University of Science and Technology [Medical Sciences]. 33(6). 834–839. 39 indexed citations
17.
Heinemann, Anja, Fang Zhao, Sonali Pechlivanis, et al.. (2011). Tumor Suppressive MicroRNAs miR-34a/c Control Cancer Cell Expression of ULBP2, a Stress-Induced Ligand of the Natural Killer Cell Receptor NKG2D. Cancer Research. 72(2). 460–471. 167 indexed citations
18.
Zhao, Fang, Yi Zhang, Yi Zhang, et al.. (2010). Blockade of osteopontin reduces alloreactive CD8+ T cell–mediated graft-versus-host disease. Blood. 117(5). 1723–1733. 34 indexed citations
19.
Wang, Ming, Yuhua Qiu, Xuelei Wang, et al.. (2010). Role of HLA‐G and NCR in protection of umbilical cord blood haematopoietic stem cells from NK cell mediated cytotoxicity. Journal of Cellular and Molecular Medicine. 15(10). 2040–2045. 3 indexed citations
20.
Fang, Liang, Xinhai Zhang, Jun Miao, et al.. (2009). Expression of CD226 Antagonizes Apoptotic Cell Death in Murine Thymocytes. The Journal of Immunology. 182(9). 5453–5460. 15 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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