Li Ye

12.9k total citations · 4 hit papers
35 papers, 9.5k citations indexed

About

Li Ye is a scholar working on Epidemiology, Physiology and Molecular Biology. According to data from OpenAlex, Li Ye has authored 35 papers receiving a total of 9.5k indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Epidemiology, 11 papers in Physiology and 10 papers in Molecular Biology. Recurrent topics in Li Ye's work include Adipose Tissue and Metabolism (10 papers), Adipokines, Inflammation, and Metabolic Diseases (7 papers) and Autophagy in Disease and Therapy (4 papers). Li Ye is often cited by papers focused on Adipose Tissue and Metabolism (10 papers), Adipokines, Inflammation, and Metabolic Diseases (7 papers) and Autophagy in Disease and Therapy (4 papers). Li Ye collaborates with scholars based in China, United States and Italy. Li Ye's co-authors include Bruce M. Spiegelman, Jun Wu, Pontus Boström, Jang Hyun Choi, Hua Tu, James C. Lo, Saverio Cinti, Mark P. Jedrychowski, Steven P. Gygi and Melin J. Khandekar and has published in prestigious journals such as Nature, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

Li Ye

33 papers receiving 9.4k citations

Hit Papers

A PGC1-α-dependent myokine that drives brown-fat-like dev... 2009 2026 2014 2020 2012 2012 2013 2009 1000 2.0k 3.0k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Li Ye China 18 6.8k 3.6k 2.7k 1.5k 1.3k 35 9.5k
Jürgen Eckel Germany 59 5.1k 0.8× 3.6k 1.0× 4.0k 1.5× 892 0.6× 2.1k 1.7× 212 11.8k
Jöerg Heeren Germany 54 4.7k 0.7× 3.3k 0.9× 3.6k 1.3× 699 0.5× 1.9k 1.5× 169 10.6k
Francesc Villarroya Spain 64 8.2k 1.2× 4.6k 1.3× 6.2k 2.3× 1.1k 0.8× 1.9k 1.5× 308 15.3k
Paul Cohen United States 48 7.2k 1.1× 4.4k 1.2× 3.8k 1.4× 963 0.6× 1.6k 1.2× 83 12.7k
Qiong Wang China 44 3.7k 0.5× 2.8k 0.8× 2.6k 0.9× 426 0.3× 1.0k 0.8× 141 7.6k
Mark P. Jedrychowski United States 53 8.9k 1.3× 4.6k 1.3× 11.3k 4.1× 1.7k 1.1× 1.3k 1.0× 93 22.5k
Jing He United States 42 4.1k 0.6× 1.1k 0.3× 4.0k 1.5× 287 0.2× 573 0.5× 116 8.9k
Frédéric Picard Canada 35 3.5k 0.5× 1.7k 0.5× 3.6k 1.3× 219 0.1× 538 0.4× 92 8.3k
Stewart H. Lecker United States 37 4.2k 0.6× 1.8k 0.5× 10.5k 3.8× 1.7k 1.1× 1.1k 0.8× 63 13.4k
John N. Fain United States 61 5.1k 0.8× 3.0k 0.8× 5.0k 1.8× 230 0.2× 2.6k 2.1× 239 13.7k

Countries citing papers authored by Li Ye

Since Specialization
Citations

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

Fields of papers citing papers by Li Ye

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Li Ye

This figure shows the co-authorship network connecting the top 25 collaborators of Li Ye. A scholar is included among the top collaborators of Li Ye 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 Ye. Li Ye 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.
Pang, Zhengyuan, et al.. (2025). Mapping cellular targets of covalent cancer drugs in the entire mammalian body. Cell. 189(3). 725–738.e15.
2.
Kong, Yan, You‐Wen Qian, Haoyue Guo, et al.. (2024). Spatial heterogeneity of infiltrating immune cells in the tumor microenvironment of non-small cell lung cancer. Translational Oncology. 50. 102143–102143. 4 indexed citations
3.
Liu, Jiayang, et al.. (2023). Targeting collagen in tumor extracellular matrix as a novel targeted strategy in cancer immunotherapy. Frontiers in Oncology. 13. 1225483–1225483. 11 indexed citations
4.
Ye, Li, et al.. (2023). Surface-enhanced Raman scattering of a gold core–silver shell-sponge substrate for detection of thiram and diquat. Analytical Methods. 15(36). 4645–4655. 1 indexed citations
5.
Xu, Hongjuan, Hecheng Zhu, Weiren Luo, et al.. (2022). TBL1X and Flot2 form a positive feedback loop to promote metastasis in nasopharyngeal carcinoma. International Journal of Biological Sciences. 18(3). 1134–1149. 17 indexed citations
6.
Zhang, Hui, et al.. (2021). Disruption of Wnt/β-catenin Pathway Elevates the Sensitivity of Gastric Cancer Cells to PD-1 Antibody. Current Molecular Pharmacology. 15(3). 557–569. 13 indexed citations
8.
Peng, Cheng, et al.. (2020). Fungichromin production by Streptomyces sp. WP-1, an endophyte from Pinus dabeshanensis, and its antifungal activity against Fusarium oxysporum. Applied Microbiology and Biotechnology. 104(24). 10437–10449. 17 indexed citations
9.
Zhang, Xuyao, Yichen Wang, Jiajun Fan, et al.. (2019). Blocking CD47 efficiently potentiated therapeutic effects of anti-angiogenic therapy in non-small cell lung cancer. Journal for ImmunoTherapy of Cancer. 7(1). 346–346. 82 indexed citations
10.
Ye, Li. (2017). Plasma levels of miR-19-5p correlate with sFLT-1 levels in gestational diabetes mellitus. Biomedical Research-tokyo. 28(18). 7856–7861. 2 indexed citations
11.
Wang, Xiang, et al.. (2017). Peniproline A, a new 1-phenylamino-2-pyrrolidone metabolite from the endophytic fungusPenicillium decumbensCP-4. Natural Product Research. 31(15). 1772–1777. 7 indexed citations
12.
Ye, Li, Mengnan Xu, Min Hu, et al.. (2017). TRPV4 is involved in irisin-induced endothelium-dependent vasodilation. Biochemical and Biophysical Research Communications. 495(1). 41–45. 32 indexed citations
13.
Li, Jiyang, Weina Wang, Meiqing Feng, et al.. (2016). Human apolipoprotein A-I exerts a prophylactic effect on high-fat diet-induced atherosclerosis via inflammation inhibition in a rabbit model. Acta Biochimica et Biophysica Sinica. 49(2). 149–158. 12 indexed citations
14.
Shi, Xunlong, Haiyan Zhu, Li Ye, et al.. (2013). Pharmacokinetics and Pharmacodynamics of Recombinant Human EPO-Fc Fusion Protein In Vivo. PLoS ONE. 8(8). e72673–e72673. 8 indexed citations
15.
Wu, Jun, Pontus Boström, Lauren M. Sparks, et al.. (2012). Beige Adipocytes Are a Distinct Type of Thermogenic Fat Cell in Mouse and Human. Cell. 150(2). 366–376. 2608 indexed citations breakdown →
16.
Boström, Pontus, Jun Wu, Mark P. Jedrychowski, et al.. (2012). A PGC1-α-dependent myokine that drives brown-fat-like development of white fat and thermogenesis. Nature. 481(7382). 463–468. 3741 indexed citations breakdown →
17.
Ye, Li, Sandra Kleiner, Jun Wu, et al.. (2012). TRPV4 Is a Regulator of Adipose Oxidative Metabolism, Inflammation, and Energy Homeostasis. Cell. 151(1). 96–110. 279 indexed citations
18.
Wang, Weina, Wei Zhou, Baolong Wang, et al.. (2012). Antioxidant effect of apolipoprotein A-I on high-fat diet-induced non-alcoholic fatty liver disease in rabbits. Acta Biochimica et Biophysica Sinica. 45(2). 95–103. 21 indexed citations
19.
Gupta, Rana K., Rina J. Mepani, Sandra Kleiner, et al.. (2012). Zfp423 Expression Identifies Committed Preadipocytes and Localizes to Adipose Endothelial and Perivascular Cells. Cell Metabolism. 15(2). 230–239. 327 indexed citations
20.
Gupta, Rana K., Zoltàn Arany, Patrick Seale, et al.. (2010). Transcriptional control of preadipocyte determination by Zfp423. Nature. 464(7288). 619–623. 416 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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