Li Tan

8.0k total citations · 2 hit papers
233 papers, 5.0k citations indexed

About

Li Tan is a scholar working on Molecular Biology, Oncology and Immunology. According to data from OpenAlex, Li Tan has authored 233 papers receiving a total of 5.0k indexed citations (citations by other indexed papers that have themselves been cited), including 96 papers in Molecular Biology, 30 papers in Oncology and 29 papers in Immunology. Recurrent topics in Li Tan's work include Melanoma and MAPK Pathways (8 papers), Diet and metabolism studies (8 papers) and Cervical Cancer and HPV Research (8 papers). Li Tan is often cited by papers focused on Melanoma and MAPK Pathways (8 papers), Diet and metabolism studies (8 papers) and Cervical Cancer and HPV Research (8 papers). Li Tan collaborates with scholars based in China, United States and United Kingdom. Li Tan's co-authors include Nathanael S. Gray, Hwan Geun Choi, Jieshou Li, Eric S. Fischer, Ellen Weisberg, Ying Li, James D. Griffin, Philip Cohen, Zainab M. Doctor and Steven P. Treon and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of the American Chemical Society and Journal of Biological Chemistry.

In The Last Decade

Li Tan

218 papers receiving 4.9k citations

Hit Papers

A Chemoproteomic Approach to Query the Degradable Kinome ... 2017 2026 2020 2023 2017 2024 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Li Tan China 37 2.6k 892 541 436 370 233 5.0k
Michal Masařík Czechia 41 2.5k 1.0× 836 0.9× 348 0.6× 315 0.7× 783 2.1× 175 6.1k
Suping Zhang China 40 3.2k 1.2× 885 1.0× 670 1.2× 305 0.7× 641 1.7× 163 5.4k
Yusuf Baran Türkiye 33 2.2k 0.8× 644 0.7× 338 0.6× 225 0.5× 420 1.1× 106 4.1k
Guan Wang China 40 3.2k 1.2× 924 1.0× 487 0.9× 431 1.0× 749 2.0× 216 5.9k
Koichi Ito Japan 59 4.8k 1.8× 1.4k 1.6× 815 1.5× 383 0.9× 449 1.2× 383 11.5k
Mingzhu Yin China 34 3.0k 1.2× 927 1.0× 854 1.6× 342 0.8× 801 2.2× 140 6.1k
Xiaoli Wang China 39 2.1k 0.8× 993 1.1× 733 1.4× 157 0.4× 581 1.6× 334 5.3k
Ruth Roberts United Kingdom 45 3.0k 1.2× 890 1.0× 554 1.0× 200 0.5× 826 2.2× 148 6.4k
Lin Zhao China 36 2.1k 0.8× 392 0.4× 352 0.7× 191 0.4× 314 0.8× 168 4.7k

Countries citing papers authored by Li Tan

Since Specialization
Citations

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

Fields of papers citing papers by Li Tan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Li Tan

This figure shows the co-authorship network connecting the top 25 collaborators of Li Tan. A scholar is included among the top collaborators of Li Tan 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 Li Tan. Li Tan 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.
Tan, Li, H. J. Yang, Yilong Chen, et al.. (2025). Gut microbiota dysbiosis and metabolic perturbations of bile/glyceric acids in major depressive disorder with IBS comorbidity. mBio. 16(11). e0244725–e0244725.
2.
Zhou, Yuzheng, Taijie Guo, Xiao Zhang, et al.. (2025). Discovery of SARS-CoV-2 PLpro inhibitors and RIPK1 inhibitors with synergistic antiviral efficacy in a mouse COVID-19 model. Acta Pharmaceutica Sinica B. 16(1). 387–405.
3.
Zhao, Long, Xiaoyu Zhang, Fuyan Wang, et al.. (2025). Artificial Cornea Substitute Based on Hydrogel Skeletons with Natural Stromal Hierarchical Structure and Extracellular Matrix for Sutureless Transplantation. Advanced Science. 12(19). e2411540–e2411540. 2 indexed citations
4.
Tan, Li, et al.. (2024). Predicting lncRNA-protein interactions using a hybrid deep learning model with dinucleotide-codon fusion feature encoding. BMC Genomics. 25(1). 1253–1253. 1 indexed citations
5.
Chen, Xinyi, Qiaoling Pan, Chenjie Huang, et al.. (2024). aCCIHBVACLF: A Novel Predictive Model for Hepatitis B Virus‐Related Acute‐On‐Chronic Liver Failure. Alimentary Pharmacology & Therapeutics. 61(2). 286–298. 3 indexed citations
6.
Yin, Qidong, et al.. (2024). Combining chain elongation and oleogel extraction for the production and recovery of caproate from beef cattle manure wastewater. Resources Conservation and Recycling. 202. 107405–107405. 7 indexed citations
7.
Cai, Mei‐Chun, Jin Liu, Pengfei Ma, et al.. (2024). YY1 downregulation underlies therapeutic response to molecular targeted agents. Cell Death and Disease. 15(11). 862–862. 3 indexed citations
8.
Liu, Guoying, Li Tan, Qingjun Zhou, et al.. (2023). Norepinephrine as an Enhancer Promoting Corneal Penetration of Riboflavin for Transepithelial Corneal Crosslinking. Translational Vision Science & Technology. 12(2). 21–21. 2 indexed citations
9.
Cheng, Yan, Lin Cheng, Ying Qin, et al.. (2023). Selective Covalent Targeting of Pyruvate Kinase M2 Using Arsenous Warheads. Journal of Medicinal Chemistry. 66(4). 2608–2621. 10 indexed citations
10.
Liu, Xin, Wei Jiang, Yali Li, et al.. (2023). FERONIA coordinates plant growth and salt tolerance via the phosphorylation of phyB. Nature Plants. 9(4). 645–660. 62 indexed citations
11.
Zhao, Long, Xin Wang, Hongwei Wang, et al.. (2022). Natural Dual‐Crosslinking Bioadhesive Hydrogel for Corneal Regeneration in Large‐Size Defects. Advanced Healthcare Materials. 11(21). e2201576–e2201576. 34 indexed citations
12.
Zhang, Yunong, Peng Xia, Jian Zou, et al.. (2022). Discovery of 3-Aminopyrazole Derivatives as New Potent and Orally Bioavailable AXL Inhibitors. Journal of Medicinal Chemistry. 65(22). 15374–15390. 15 indexed citations
13.
Cheng, Lin, Kaixuan Shi, Yan Cheng, et al.. (2022). Dual Inhibition of CDK12/CDK13 Targets Both Tumor and Immune Cells in Ovarian Cancer. Cancer Research. 82(19). 3588–3602. 25 indexed citations
14.
Bockorny, Bruno, Maria Rusan, Wankun Chen, et al.. (2018). RAS–MAPK Reactivation Facilitates Acquired Resistance in FGFR1 -Amplified Lung Cancer and Underlies a Rationale for Upfront FGFR–MEK Blockade. Molecular Cancer Therapeutics. 17(7). 1526–1539. 43 indexed citations
15.
Rosas‐Díaz, Tábata, Dan Zhang, Pengfei Fan, et al.. (2018). A virus-targeted plant receptor-like kinase promotes cell-to-cell spread of RNAi. Proceedings of the National Academy of Sciences. 115(6). 1388–1393. 168 indexed citations
16.
Brown, Wells S., Li Tan, Andrew Smith, Nathanael S. Gray, & Michael K. Wendt. (2016). Covalent Targeting of Fibroblast Growth Factor Receptor Inhibits Metastatic Breast Cancer. Molecular Cancer Therapeutics. 15(9). 2096–2106. 61 indexed citations
17.
Amato, Katherine, Shan Wang, Li Tan, et al.. (2016). EPHA2 Blockade Overcomes Acquired Resistance to EGFR Kinase Inhibitors in Lung Cancer. Cancer Research. 76(2). 305–318. 84 indexed citations
18.
Miao, Benchun, Zhenyu Ji, Li Tan, et al.. (2014). EPHA2 Is a Mediator of Vemurafenib Resistance and a Novel Therapeutic Target in Melanoma. Cancer Discovery. 5(3). 274–287. 96 indexed citations
19.
Beauchamp, Ellen M., Brittany A. Woods, Austin Dulak, et al.. (2013). Acquired Resistance to Dasatinib in Lung Cancer Cell Lines Conferred by DDR2 Gatekeeper Mutation and NF1 Loss. Molecular Cancer Therapeutics. 13(2). 475–482. 44 indexed citations
20.
Osaki, Makoto, et al.. (2001). PP35 BMPs stimulate cartilage matrix gene expression. Osteoarthritis and Cartilage. 9. S13–S13.

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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