Shu Lin

11.3k total citations · 2 hit papers
180 papers, 7.6k citations indexed

About

Shu Lin is a scholar working on Molecular Biology, Endocrine and Autonomic Systems and Cellular and Molecular Neuroscience. According to data from OpenAlex, Shu Lin has authored 180 papers receiving a total of 7.6k indexed citations (citations by other indexed papers that have themselves been cited), including 64 papers in Molecular Biology, 49 papers in Endocrine and Autonomic Systems and 39 papers in Cellular and Molecular Neuroscience. Recurrent topics in Shu Lin's work include Regulation of Appetite and Obesity (42 papers), Neuropeptides and Animal Physiology (35 papers) and Extracellular vesicles in disease (15 papers). Shu Lin is often cited by papers focused on Regulation of Appetite and Obesity (42 papers), Neuropeptides and Animal Physiology (35 papers) and Extracellular vesicles in disease (15 papers). Shu Lin collaborates with scholars based in Australia, China and United States. Shu Lin's co-authors include Xu‐Feng Huang, Herbert Herzog, Benjamin A. García, Amanda Sainsbury, Yan‐Chuan Shi, Dana Boey, C. David Allis, Laura A. Banaszynski, Manuel M. Müller and Oren J. Becher and has published in prestigious journals such as Science, Chemical Reviews and Proceedings of the National Academy of Sciences.

In The Last Decade

Shu Lin

176 papers receiving 7.5k citations

Hit Papers

Inhibition of PRC2 Activity by a Gain-of-Function H3 Muta... 2013 2026 2017 2021 2013 2022 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shu Lin Australia 46 3.3k 1.8k 1.7k 1.3k 715 180 7.6k
Eiichi Hinoi Japan 37 3.5k 1.0× 681 0.4× 1.4k 0.8× 861 0.7× 543 0.8× 159 7.4k
Yutaka Oiso Japan 47 3.6k 1.1× 1.1k 0.6× 1.3k 0.8× 1.2k 0.9× 480 0.7× 321 8.3k
Hong Yu United States 50 4.0k 1.2× 2.7k 1.6× 2.0k 1.2× 1.2k 1.0× 1.4k 1.9× 154 9.8k
Daniel L. Marks United States 54 2.8k 0.8× 2.8k 1.6× 3.3k 2.0× 1.1k 0.9× 1.8k 2.5× 176 10.0k
Catherine Godson Ireland 58 5.1k 1.5× 1.6k 0.9× 1.1k 0.6× 738 0.6× 1.6k 2.3× 155 11.2k
Koji Maemura Japan 47 3.9k 1.2× 1.0k 0.6× 1.9k 1.1× 477 0.4× 193 0.3× 229 8.4k
Darrell W. Brann United States 63 3.2k 1.0× 1.3k 0.7× 1.6k 0.9× 2.0k 1.6× 399 0.6× 189 11.5k
Eng‐Ang Ling Singapore 55 3.3k 1.0× 816 0.5× 1.4k 0.8× 2.5k 2.0× 281 0.4× 263 11.0k
Holger M. Reichardt Germany 52 2.5k 0.7× 1.6k 0.9× 1.5k 0.9× 783 0.6× 170 0.2× 135 10.1k
Keith L. Parker United States 51 5.3k 1.6× 1.0k 0.6× 1.1k 0.6× 835 0.7× 349 0.5× 100 10.5k

Countries citing papers authored by Shu Lin

Since Specialization
Citations

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

Fields of papers citing papers by Shu Lin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shu Lin

This figure shows the co-authorship network connecting the top 25 collaborators of Shu Lin. A scholar is included among the top collaborators of Shu Lin 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 Shu Lin. Shu Lin 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.
Liu, Yi‐Jing, et al.. (2025). Exosomes derived let-7f-5p is a potential biomarker of SLE with anti-inflammatory function. Non-coding RNA Research. 12. 116–131. 1 indexed citations
2.
Fang, Yuming, Wei-can Chen, Yan Zhang, et al.. (2025). Spinal cord injury–derived exosomes exacerbate damage: miR-155-5p mediates inflammatory responses. Neural Regeneration Research. 21(6). 2514–2522. 1 indexed citations
3.
Wang, Hongyang, et al.. (2025). Advancements in Clinical Diagnosis and the Application of Auxiliary Imaging in Sarcopenic Obesity. Obesity Facts. 1–13. 1 indexed citations
4.
Xu, Liming, et al.. (2024). Latest advances and clinical application prospects of resveratrol therapy for neurocognitive disorders. Brain Research. 1830. 148821–148821. 2 indexed citations
5.
Xie, Yaping, Huifen Zhao, Shu Lin, et al.. (2024). Suppression of certain intestinal microbiota metabolites may lead to gestational diabetes in mice fed a high-fat diet. Frontiers in Microbiology. 15. 1473441–1473441.
6.
Wu, Qi, et al.. (2024). Dopamine Receptor 1 Treatment Promotes Epithelial Repair of Corneal Injury by Inhibiting NOD-Like Receptor Protein 3–Associated Inflammation. Investigative Ophthalmology & Visual Science. 65(1). 49–49. 1 indexed citations
8.
Chen, Jinguo, et al.. (2023). Prediction of Receptor Status in Radiomics: Recent Advances in Breast Cancer Research. Academic Radiology. 31(7). 3004–3014. 5 indexed citations
9.
Huang, Bingbing, Ruiyun Wu, Lingling Qiu, et al.. (2023). Evaluation of non-invasive gene detection in preimplantation embryos: a systematic review and meta-analysis. Journal of Assisted Reproduction and Genetics. 40(6). 1243–1253. 8 indexed citations
10.
Xiong, Bin, et al.. (2023). Recent advances microRNAs and metabolic reprogramming in colorectal cancer research. Frontiers in Oncology. 13. 1165862–1165862. 3 indexed citations
11.
Chen, Qianqian, et al.. (2023). Diagnostic value of mammography density of breast masses by using deep learning. Frontiers in Oncology. 13. 1110657–1110657. 2 indexed citations
12.
Chen, Shao-rong, et al.. (2023). Latest advances in the study of non-coding RNA-mediated circadian rhythm disorders causing endometrial cancer. Frontiers in Oncology. 13. 1277543–1277543. 3 indexed citations
13.
Chen, Shao-rong, et al.. (2022). Therapeutic options for premature ovarian insufficiency: an updated review. Reproductive Biology and Endocrinology. 20(1). 28–28. 58 indexed citations
14.
Lin, Shu, et al.. (2022). Update of application of olfactory ensheathing cells and stem cells/exosomes in the treatment of retinal disorders. Stem Cell Research & Therapy. 13(1). 11–11. 8 indexed citations
15.
Lin, Shuting, et al.. (2021). Update on the Role of Neuropeptide Y and Other Related Factors in Breast Cancer and Osteoporosis. Frontiers in Endocrinology. 12. 705499–705499. 15 indexed citations
16.
Wu, Jinxiang, Shu Lin, & Shuangbo Kong. (2021). Psychological Stress and Functional Endometrial Disorders: Update of Mechanism Insights. Frontiers in Endocrinology. 12. 690255–690255. 10 indexed citations
17.
Lewis, Peter W., Manuel M. Müller, Francisco J. Cordero, et al.. (2013). Inhibition of PRC2 Activity by a Gain-of-Function H3 Mutation Found in Pediatric Glioblastoma. Science. 340(6134). 857–861. 898 indexed citations breakdown →
18.
Rothbart, Scott B., et al.. (2012). Poly-acetylated chromatin signatures are preferred epitopes for site-specific histone H4 acetyl antibodies. Scientific Reports. 2(1). 489–489. 34 indexed citations
19.
Shi, Yan‐Chuan, Shu Lin, Iris P.L. Wong, et al.. (2010). NPY Neuron-Specific Y2 Receptors Regulate Adipose Tissue and Trabecular Bone but Not Cortical Bone Homeostasis in Mice. PLoS ONE. 5(6). e11361–e11361. 81 indexed citations
20.
Zhang, Lei, Laurence Macia, Nigel Turner, et al.. (2009). Peripheral neuropeptide Y Y1 receptors regulate lipid oxidation and fat accretion. International Journal of Obesity. 34(2). 357–373. 60 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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