Lei Sun

6.3k total citations · 1 hit paper
89 papers, 4.6k citations indexed

About

Lei Sun is a scholar working on Physiology, Molecular Biology and Cancer Research. According to data from OpenAlex, Lei Sun has authored 89 papers receiving a total of 4.6k indexed citations (citations by other indexed papers that have themselves been cited), including 45 papers in Physiology, 39 papers in Molecular Biology and 21 papers in Cancer Research. Recurrent topics in Lei Sun's work include Adipose Tissue and Metabolism (45 papers), Adipokines, Inflammation, and Metabolic Diseases (18 papers) and Cancer-related molecular mechanisms research (18 papers). Lei Sun is often cited by papers focused on Adipose Tissue and Metabolism (45 papers), Adipokines, Inflammation, and Metabolic Diseases (18 papers) and Cancer-related molecular mechanisms research (18 papers). Lei Sun collaborates with scholars based in Singapore, China and United States. Lei Sun's co-authors include Harvey F. Lodish, Kinyui Alice Lo, Mirko Trajkovski, Marko Knoll, Bingbing Yuan, Peng Chen, Ryan Alexander, Loyal A. Goff, Martin Sauvageau and David R. Kelley and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Nature Communications.

In The Last Decade

Lei Sun

86 papers receiving 4.6k citations

Hit Papers

Topological organization of multichromosomal regions by t... 2014 2026 2018 2022 2014 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Lei Sun Singapore 38 2.6k 1.6k 1.5k 834 445 89 4.6k
Dolors Serra Spain 37 2.3k 0.9× 839 0.5× 1.8k 1.2× 957 1.1× 267 0.6× 114 4.7k
Étienne Lefai France 35 3.1k 1.2× 1.2k 0.7× 1.4k 0.9× 922 1.1× 341 0.8× 81 5.2k
Qiwei Zhai China 37 3.0k 1.2× 914 0.6× 1.5k 1.0× 1.1k 1.4× 182 0.4× 86 6.0k
Sébastien Herzig Switzerland 15 4.4k 1.7× 869 0.5× 1.2k 0.8× 1.5k 1.8× 199 0.4× 21 6.3k
Thilo Hagen Singapore 30 2.7k 1.0× 875 0.5× 2.0k 1.3× 466 0.6× 209 0.5× 74 4.7k
Michael J. Wolfgang United States 41 2.3k 0.9× 556 0.3× 1.6k 1.0× 790 0.9× 199 0.4× 84 4.8k
Qiang Tong United States 33 2.5k 1.0× 447 0.3× 2.2k 1.4× 1.7k 2.0× 265 0.6× 72 5.8k
Martina Wallace United States 25 1.9k 0.7× 741 0.4× 892 0.6× 570 0.7× 98 0.2× 47 3.4k
Joshua Wollam United States 19 1.6k 0.6× 636 0.4× 707 0.5× 630 0.8× 324 0.7× 21 3.0k
Jae Myoung Suh United States 23 2.4k 0.9× 392 0.2× 1.6k 1.0× 1.2k 1.4× 347 0.8× 42 4.7k

Countries citing papers authored by Lei Sun

Since Specialization
Citations

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

Fields of papers citing papers by Lei Sun

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lei Sun

This figure shows the co-authorship network connecting the top 25 collaborators of Lei Sun. A scholar is included among the top collaborators of Lei Sun 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 Lei Sun. Lei Sun 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.
Li, Jia, Wei Wen Teo, Ko‐Hsin Chin, et al.. (2025). Isoform usage as a distinct regulatory layer driving nutrient-responsive metabolic adaptation. Cell Metabolism. 37(3). 772–787.e6.
2.
Sun, Ling, Lei Yang, Shiyi Chen, et al.. (2024). Effects of fermentation conditions on molecular weight, production, and physicochemical properties of gellan gum. International Journal of Biological Macromolecules. 279(Pt 3). 135304–135304. 3 indexed citations
4.
Zhou, Qiuzhong, Wen Li, Melvin Khee‐Shing Leow, et al.. (2023). Multidimensional conservation analysis decodes the expression of conserved long noncoding RNAs. Life Science Alliance. 6(6). e202302002–e202302002. 3 indexed citations
5.
Zhou, Qiuzhong, Lexiang Yu, Joshua R. Cook, Li Qiang, & Lei Sun. (2023). Deciphering the decline of metabolic elasticity in aging and obesity. Cell Metabolism. 35(9). 1661–1671.e6. 32 indexed citations
6.
Sun, Lei, et al.. (2023). The Role of Splicing Factors in Adipogenesis and Thermogenesis. Molecules and Cells. 46(5). 268–277. 14 indexed citations
7.
Leow, Melvin Khee‐Shing, Kothandaraman Narasimhan, Sanjay Kumar Verma, et al.. (2022). Activated brown adipose tissue releases exosomes containing mitochondrial methylene tetrahydrofolate dehydrogenase (NADP dependent) 1-like protein (MTHFD1L). Bioscience Reports. 42(5). 7 indexed citations
8.
Xu, Dan & Lei Sun. (2022). HOTAIR underlies the region-specific development of adipose tissue. Nature Reviews Endocrinology. 18(11). 663–664. 2 indexed citations
9.
Yang, Yi, Xingjie Shi, Wei Liu, et al.. (2021). SC-MEB: spatial clustering with hidden Markov random field using empirical Bayes. Briefings in Bioinformatics. 23(1). 50 indexed citations
10.
Kraakman, Michael J., Qiuzhong Zhou, Qiongming Liu, et al.. (2021). Adipsin promotes bone marrow adiposity by priming mesenchymal stem cells. eLife. 10. 50 indexed citations
11.
Chen, Zhenzhen, Junpei Wang, Yuhong Meng, et al.. (2020). Repurposing Doxepin to Ameliorate Steatosis and Hyperglycemia by Activating FAM3A Signaling Pathway. Diabetes. 69(6). 1126–1139. 24 indexed citations
12.
Lim, Yen Ching, Ufuk Degirmenci, Xiang Hu, et al.. (2020). The RNA-binding protein HuR is a negative regulator in adipogenesis. Nature Communications. 11(1). 213–213. 77 indexed citations
13.
Zhou, Qiuzhong, Zhenzhen Fu, Yingyun Gong, et al.. (2020). Metabolic Health Status Contributes to Transcriptome Alternation in Human Visceral Adipose Tissue During Obesity. Obesity. 28(11). 2153–2162. 9 indexed citations
14.
Cao, Ji, Lei Sun, Pornpun Aramsangtienchai, et al.. (2019). HDAC11 regulates type I interferon signaling through defatty-acylation of SHMT2. Proceedings of the National Academy of Sciences. 116(12). 5487–5492. 132 indexed citations
15.
Arcinas, Camille, Wilson Lek Wen Tan, Wen‐Ning Fang, et al.. (2019). Adipose circular RNAs exhibit dynamic regulation in obesity and functional role in adipogenesis. Nature Metabolism. 1(7). 688–703. 80 indexed citations
16.
Cibi, Dasan Mary, Masum M. Mia, Shamini G. Shekeran, et al.. (2019). Neural crest-specific deletion of Rbfox2 in mice leads to craniofacial abnormalities including cleft palate. eLife. 8. 24 indexed citations
17.
Sun, Lei & Jiandie D. Lin. (2019). Function and Mechanism of Long Noncoding RNAs in Adipocyte Biology. Diabetes. 68(5). 887–896. 46 indexed citations
18.
Lo, Kinyui Alice, Camille Arcinas, Zhichun Zhang, et al.. (2018). Adipocyte Long-Noncoding RNA Transcriptome Analysis of Obese Mice Identified Lnc-Leptin, Which Regulates Leptin. Diabetes. 67(6). 1045–1056. 48 indexed citations
19.
Bai, Zhiqiang, Xiaoran Chai, Myeong Jin Yoon, et al.. (2017). Dynamic transcriptome changes during adipose tissue energy expenditure reveal critical roles for long noncoding RNA regulators. PLoS Biology. 15(8). e2002176–e2002176. 72 indexed citations
20.
Xu, Dan, Shaohai Xu, Yen Ching Lim, et al.. (2017). RNA Binding Protein Ybx2 Regulates RNA Stability During Cold-Induced Brown Fat Activation. Diabetes. 66(12). 2987–3000. 28 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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