Kun Lyu

696 citations
17 papers · 516 · h-index 9

Impact in

Papers in

    • Liver Disease Diagnosis and Treatment 4
    • Adipokines, Inflammation, and Metabolic Diseases 2
    • Metabolism, Diabetes, and Cancer 2

Kun Lyu

17 papers receiving 515 citations

Peers

Kun Lyu
Comparison fields: 5 of 61
  • Endocrinology, Diabetes and Metabolism 222
  • Physiology 255
  • Epidemiology 251
  • Endocrine and Autonomic Systems 26
  • Cardiology and Cardiovascular Medicine 85
Replace Pia Fahlbusch with:
Pia Fahlbusch Germany
Tyler Field United States
Maria Cristina Procopio Italy
Brandy Weller Canada
Babak Dehestani Ireland
Anannya Banga United States
Clinton M. Hasenour United States
Marine Coué France
Mark Sommerfeld Germany
Jinglei Yu United Kingdom
Kun Lyu relative to Pia Fahlbusch Germany Pia Fahlbusch's profile →
Citations per field
00.5×2.5×
Pia Fahlbusch · 1×
Citations per year

Countries citing papers authored by Kun Lyu

Since Specialization
Citations

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

Fields of papers citing papers by Kun Lyu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Kun Lyu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Kun Lyu Line = papers co-authored together Kun Lyu links everyone, so they are left out of the graph.

All Works

17 of 17 papers shown
#Work
1 2020178
2 2020104
3 201862
4 201957
5 202029
6 202127
7 202416
8 202014
9 202214
10 20223
11 20242
12 20192
13 20202
14
[Viral myocarditis serum exosome-derived miR-320 promotes the apoptosis of mouse cardiomyocytes by inhibiting AKT/mTOR pathway and targeting phosphatidylinositol 3-kinase regulatory subunit 1 (Pik3r1)].
20232
15 20182
16 20191
17
[Spleen-derived CD4+ T cells of asthmatic mice promote M2 polarization of macrophages in vitro].
20191

About Kun Lyu

Kun Lyu is a scholar working on Epidemiology, Molecular Biology, Physiology, Surgery and Biochemistry, having authored 17 papers that have together received 516 indexed citations. Recurring topics across this work include Adipose Tissue and Metabolism (4 papers), Liver Disease Diagnosis and Treatment (4 papers), Pancreatic function and diabetes (3 papers), Lipid metabolism and biosynthesis (3 papers), Metabolism, Diabetes, and Cancer (2 papers), Tree Root and Stability Studies (2 papers), Regulation of Appetite and Obesity (2 papers) and Adipokines, Inflammation, and Metabolic Diseases (2 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (222 citations), Physiology (255 citations), Epidemiology (251 citations), Endocrine and Autonomic Systems (26 citations) and Cardiology and Cardiovascular Medicine (85 citations). Kun Lyu has collaborated with scholars based in China, United States and Brazil. Frequent co-authors include Gerald I. Shulman, Gary W. Cline, Kitt Falk Petersen, Panu K. Luukkonen, Dongyan Zhang, Hannele Yki‐Järvinen, Tiina E. Lehtimäki, Sylvie Dufour, Antti Hakkarainen and Varman T. Samuel. Their work appears in journals such as Diabetologia, Journal of Lipid Research, Cell Metabolism, The Journal of Physiology and Diabetes.

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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