Gangli An

599 total citations
24 papers, 490 citations indexed

About

Gangli An is a scholar working on Oncology, Immunology and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Gangli An has authored 24 papers receiving a total of 490 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Oncology, 11 papers in Immunology and 7 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Gangli An's work include CAR-T cell therapy research (13 papers), Immune Cell Function and Interaction (8 papers) and Monoclonal and Polyclonal Antibodies Research (6 papers). Gangli An is often cited by papers focused on CAR-T cell therapy research (13 papers), Immune Cell Function and Interaction (8 papers) and Monoclonal and Polyclonal Antibodies Research (6 papers). Gangli An collaborates with scholars based in China, United States and United Kingdom. Gangli An's co-authors include Lin Yang, Huimin Meng, Fengtao You, Licui Jiang, Xuejun Zhu, Dan Chen, Xing‐Ding Zhang, Yinyan Wang, Lei Yuan and Jialu Li and has published in prestigious journals such as SHILAP Revista de lepidopterología, Cancer Research and Polymer.

In The Last Decade

Gangli An

23 papers receiving 485 citations

Peers

Gangli An

ONCOL

IMMUN

RNMI

HEMAT

Tiffany A. Coupet United States

Dirk Hönemann Australia

Irene Michalk Germany

James Dongjoo Ham United States

Kevin M. Friedman United States

Dana L. Schalk United States

Amy K. Erbe United States

Margot J. Pont United States

Karen Dengel United States

Christian Augsberger Germany

Tiffany A. Coupet United States

Gangli An

323 ×0.9

ONCOL

204 ×0.8

IMMUN

128 ×0.9

160 ×2.0

RNMI

50 ×0.6

HEMAT

Citations per year, relative to Gangli An Gangli An (= 1×) peers Tiffany A. Coupet

Countries citing papers authored by Gangli An

Since Specialization

Citations

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

Fields of papers citing papers by Gangli An

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Gangli An

This figure shows the co-authorship network connecting the top 25 collaborators of Gangli An. A scholar is included among the top collaborators of Gangli An 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 Gangli An. Gangli An is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Jiang, Licui, Fengtao You, Changsong Qi, et al.. (2024). B7-H3–Targeted CAR-Vδ1T Cells Exhibit Potent Broad-Spectrum Activity against Solid Tumors. Cancer Research. 84(23). 4066–4080. 7 indexed citations

Wang, Tian, Fengtao You, Tingting Zhang, et al.. (2023). B7-H3 chimeric antigen receptor-modified T cell shows potential for targeted treatment of acute myeloid leukaemia. European journal of medical research. 28(1). 129–129. 8 indexed citations

An, Gangli, et al.. (2023). Enhanced efficacy of CD19/CD22 bispecific CAR‐T cells with EAAAK linker on B‐cell malignancies. European Journal Of Haematology. 112(1). 64–74. 6 indexed citations

Zhang, Kailu, Zixuan Li, Tian Wang, et al.. (2023). CD7 protein plays a crucial role in T cell infiltration in tumors. Heliyon. 9(6). e16961–e16961. 3 indexed citations

Wang, Tian, et al.. (2023). Preconditioning of radiotherapy enhances efficacy of B7-H3-CAR-T in treating solid tumor models. Life Sciences. 331. 122024–122024. 14 indexed citations

Zhang, Tingting, Tian Wang, Fengtao You, et al.. (2022). Nanobody-based anti-CD22-chimeric antigen receptor T cell immunotherapy exhibits improved remission against B-cell acute lymphoblastic leukemia. Transplant Immunology. 71. 101538–101538. 13 indexed citations

Li, Zixuan, Zhou Zhou, Kailu Zhang, et al.. (2022). RPRM deletion preserves hematopoietic regeneration by promoting EGFR‐dependent DNA repair and hematopoietic stem cell proliferation post ionizing radiation. Cell Biology International. 46(12). 2158–2172. 7 indexed citations

Li, Zixuan, Tingting Zhang, Tian Wang, et al.. (2021). Zkscan3 affects erythroblast development by regulating the transcriptional activity of GATA1 and KLF1 in mice. Journal of Molecular Histology. 53(2). 423–436. 3 indexed citations

You, Fengming, Shan Xiang, Yinyan Wang, et al.. (2021). Chimeric antigen receptor T cells derived from CD7 nanobody exhibit robust antitumor potential against CD7-positive malignancies.. PubMed. 11(11). 5263–5281. 10 indexed citations

10.

Ji, Cheng, Fengtao You, Tingting Zhang, et al.. (2020). Novel anti-GD2 CAR-T cells exhibit superior cytotoxicity against neuroblastoma. SHILAP Revista de lepidopterología. 18. 3254696951–3254696951. 2 indexed citations

11.

Yang, Nan, Jing Yu, Yelin Jiang, et al.. (2020). The zinc finger transcription factor ZKSCAN3 promotes prostate cancer cell migration. UNC Libraries.

12.

You, Fengtao, Yinyan Wang, Licui Jiang, et al.. (2019). A novel CD7 chimeric antigen receptor-modified NK-92MI cell line targeting T-cell acute lymphoblastic leukemia.. PubMed. 9(1). 64–78. 116 indexed citations

13.

Li, Zixuan, Jialu Li, Huimin Meng, et al.. (2019). Zkscan3 gene is a potential negative regulator of plasma cell differentiation. SHILAP Revista de lepidopterología. 17. 2 indexed citations

14.

Meng, Huimin, et al.. (2018). La/SSB chimeric autoantibody receptor modified NK92MI cells for targeted therapy of autoimmune disease. Clinical Immunology. 192. 40–49. 32 indexed citations

15.

Wu, Chao‐Liang, Jialu Li, Zixuan Li, et al.. (2018). Effects of Csf1R-Targeted Chimeric Antigen Receptor-Modified Nk92Mi & T Cells on Tumor-Associated Macrophages. Immunotherapy. 10(11). 935–949. 38 indexed citations

16.

Chen, Ying, Fengtao You, Licui Jiang, et al.. (2017). Gene-modified NK-92MI cells expressing a chimeric CD16-BB-ζ or CD64-BB-ζ receptor exhibit enhanced cancer-killing ability in combination with therapeutic antibody. Oncotarget. 8(23). 37128–37139. 37 indexed citations

17.

Chen, Dan, et al.. (2016). Anti-human CD138 monoclonal antibodies and their bispecific formats: generation and characterization. Immunopharmacology and Immunotoxicology. 38(3). 175–183. 25 indexed citations

18.

Tang, Jinle, Jialu Li, Xuejun Zhu, et al.. (2016). Novel CD7-specific nanobody-based immunotoxins potently enhanced apoptosis of CD7-positive malignant cells. Oncotarget. 7(23). 34070–34083. 36 indexed citations

19.

Chu, Fuliang, Songbing He, Jing Yu, et al.. (2014). Abstract 4094: Identification of co-inhibitory receptor expression on T cells from gastric cancer patients. Cancer Research. 74(19_Supplement). 4094–4094. 1 indexed citations

20.

Zhang, Xing‐Ding, Jing Yu, Sally A. Hunsucker, et al.. (2012). The zinc finger transcription factor ZKSCAN3 promotes prostate cancer cell migration. The International Journal of Biochemistry & Cell Biology. 44(7). 1166–1173. 36 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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