Jinle Tang

854 total citations · 1 hit paper
20 papers, 521 citations indexed

About

Jinle Tang is a scholar working on Molecular Biology, Immunology and Oncology. According to data from OpenAlex, Jinle Tang has authored 20 papers receiving a total of 521 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 5 papers in Immunology and 3 papers in Oncology. Recurrent topics in Jinle Tang's work include SARS-CoV-2 and COVID-19 Research (2 papers), interferon and immune responses (2 papers) and Multiple Myeloma Research and Treatments (2 papers). Jinle Tang is often cited by papers focused on SARS-CoV-2 and COVID-19 Research (2 papers), interferon and immune responses (2 papers) and Multiple Myeloma Research and Treatments (2 papers). Jinle Tang collaborates with scholars based in China, United States and Canada. Jinle Tang's co-authors include Hao Huang, Zhihong Liu, Yuxin Ye, Ziyang Fu, Huan Zhou, Bin Huang, Dan Cao, Yong Zhao, Xiaogang Niu and Jihui Li and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and The Journal of Immunology.

In The Last Decade

Jinle Tang

19 papers receiving 515 citations

Hit Papers

The complex structure of GRL0617 and SARS-CoV-2 PLpro rev... 2021 2026 2022 2024 2021 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
Jinle Tang China 10 215 165 134 126 66 20 521
Praveen K. Madala Australia 9 328 1.5× 74 0.4× 264 2.0× 39 0.3× 70 1.1× 14 728
Brian M. Beyer United States 12 221 1.0× 134 0.8× 54 0.4× 93 0.7× 81 1.2× 19 558
Jacintha Shenton United States 13 253 1.2× 73 0.4× 179 1.3× 49 0.4× 153 2.3× 18 753
Tiancen Hu China 14 546 2.5× 142 0.9× 107 0.8× 139 1.1× 140 2.1× 18 778
Levon Halabelian Canada 15 438 2.0× 100 0.6× 56 0.4× 48 0.4× 102 1.5× 28 626
Yibei Xiao China 16 377 1.8× 90 0.5× 134 1.0× 70 0.6× 250 3.8× 60 766
Sajjan Rajpoot India 12 289 1.3× 142 0.9× 156 1.2× 110 0.9× 47 0.7× 17 567
Payal R. Sheth United States 12 243 1.1× 166 1.0× 80 0.6× 30 0.2× 45 0.7× 24 474
Eijiro Honjo Japan 13 342 1.6× 46 0.3× 176 1.3× 23 0.2× 73 1.1× 18 580
Benjamin S. Gully Australia 14 345 1.6× 142 0.9× 291 2.2× 61 0.5× 140 2.1× 22 743

Countries citing papers authored by Jinle Tang

Since Specialization
Citations

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

Fields of papers citing papers by Jinle Tang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jinle Tang

This figure shows the co-authorship network connecting the top 25 collaborators of Jinle Tang. A scholar is included among the top collaborators of Jinle Tang 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 Jinle Tang. Jinle Tang 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.
2.
Chen, Wenyue, Zhengqiang Li, Jinle Tang, & Shuguang Liu. (2025). Dendritic cell-based immunotherapy for head and neck squamous cell carcinoma: advances and challenges. Frontiers in Immunology. 16. 1573635–1573635.
3.
Dai, Jiyan, Huiyu Xu, Tao Chen, et al.. (2025). Artificial intelligence for medicine 2025: Navigating the endless frontier. 3(1). 100120–100120. 3 indexed citations
4.
Zhang, Bo, Xiaojie Sun, & Jinle Tang. (2024). Ultrasound-assisted green synthesis of gold nanoparticles mediated by Staghorn sumac for the treatment of lung cancer: Introducing a novel chemotherapeutic drug. Inorganic Chemistry Communications. 170. 113146–113146. 2 indexed citations
6.
Cao, Li, Jiayin Guo, Xue Zhang, et al.. (2023). Engineering RsDddA as mitochondrial base editor with wide target compatibility and enhanced activity. Molecular Therapy — Nucleic Acids. 34. 102028–102028. 9 indexed citations
7.
Xu, Yunxia, Ke Chen, Danting Zhang, et al.. (2021). Repurposing clinically approved drugs for COVID-19 treatment targeting SARS-CoV-2 papain-like protease. International Journal of Biological Macromolecules. 188. 137–146. 34 indexed citations
8.
Fu, Ziyang, Bin Huang, Jinle Tang, et al.. (2021). The complex structure of GRL0617 and SARS-CoV-2 PLpro reveals a hot spot for antiviral drug discovery. Nature Communications. 12(1). 488–488. 217 indexed citations breakdown →
9.
Tang, Jinle, Beihua Dong, Ming Liu, et al.. (2021). Identification of Small Molecule Inhibitors of RNase L by Fragment-Based Drug Discovery. Journal of Medicinal Chemistry. 65(2). 1445–1457. 7 indexed citations
10.
Daou, Salima, Manisha Talukdar, Jinle Tang, et al.. (2020). A phenolic small molecule inhibitor of RNase L prevents cell death from ADAR1 deficiency. Proceedings of the National Academy of Sciences. 117(40). 24802–24812. 21 indexed citations
11.
Tang, Jinle, Yingjie Wang, Huan Zhou, et al.. (2020). Sunitinib inhibits RNase L by destabilizing its active dimer conformation. Biochemical Journal. 477(17). 3387–3399. 11 indexed citations
12.
Palaniyandi, Senthilkumar, Iowis Zhu, Jinle Tang, et al.. (2019). Human cytomegalovirus evades antibody-mediated immunity through endoplasmic reticulum-associated degradation of the FcRn receptor. Nature Communications. 10(1). 3020–3020. 32 indexed citations
13.
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
14.
Zou, Jing, et al.. (2015). BiTE-hIgFc-based Immunotherapy as a New Therapeutic Strategy in Multiple Myeloma.. Cancer Science. 1 indexed citations
15.
Palaniyandi, Senthilkumar, Xiaoming Liu, Sivakumar Periasamy, et al.. (2015). Inhibition of CD23-mediated IgE transcytosis suppresses the initiation and development of allergic airway inflammation. Mucosal Immunology. 8(6). 1262–1274. 37 indexed citations
16.
Qi, Lin, Xue Sun, Frank Braun, et al.. (2015). HMGB1 Promotes Mitochondrial Dysfunction–Triggered Striatal Neurodegeneration via Autophagy and Apoptosis Activation. PLoS ONE. 10(11). e0142901–e0142901. 29 indexed citations
17.
Palaniyandi, Senthilkumar, Xiaoyang Liu, Sivakumar Periasamy, et al.. (2015). Inhibition of CD23-mediated IgE transcytosis suppresses the initiation and development of airway allergic inflammation (HYP4P.308). The Journal of Immunology. 194(1_Supplement). 123.7–123.7. 1 indexed citations
18.
Chen, Dan, Sisi Ye, Jinle Tang, et al.. (2015). Immunotherapy based on bispecific T‐cell engager with hIgG1 Fc sequence as a new therapeutic strategy in multiple myeloma. Cancer Science. 106(5). 512–521. 46 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.
Tang, Jinle, et al.. (1996). Nck inhibits NGF and basic FGF induced PC12 cell differentiation via mitogen-activated protein kinase-independent pathway.. PubMed. 12(11). 2351–9. 27 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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