Shao‐Chun Lu

50 papers receiving 1.6k citations

Peers

Shao‐Chun Lu
Comparison fields: 5 of 108
  • Biological Psychiatry 50
  • Immunology 334
  • Hepatology 104
  • Cancer Research 188
  • Periodontics 53
Replace Jing Luo with:
Jing Luo China
Chiara Bolego Italy
Makiko Hayashi Japan
Alessia Perino Italy
Midori Fujishiro Japan
Robert F. Stachlewitz United States
Niels Kloosterhuis Netherlands
Rajaa El Bekay Spain
Justine M. Abais United States
Shao‐Chun Lu relative to Jing Luo China Jing Luo's profile →
Citations per field
00.5×2.8×
Jing Luo · 1×
Citations per year

Countries citing papers authored by Shao‐Chun Lu

Since Specialization
Citations

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

Fields of papers citing papers by Shao‐Chun Lu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Shao‐Chun Lu. 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 Shao‐Chun Lu. The network helps show where Shao‐Chun Lu may publish in the future.

Co-authors

The 25 scholars most cited alongside Shao‐Chun Lu, 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 Shao‐Chun Lu Line = papers co-authored together Shao‐Chun Lu links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 54 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2014168
2 2002134
3 201086
4 200478
5 201373
6 201066
7 201966
8 200866
9 201655
10 201354
11
The association of single nucleotide polymorphisms in the 5'-regulatory region of the lumican gene with susceptibility to high myopia in Taiwan.
200651
12 201550
13 200150
14 201349
15 201644
16 200643
17 201439
18 200035
19 201033
20 200929

About Shao‐Chun Lu

Shao‐Chun Lu is a scholar working on Molecular Biology, Immunology, Cancer Research, Epidemiology and Surgery, having authored 54 papers that have together received 1.7k indexed citations. Recurring topics across this work include Atherosclerosis and Cardiovascular Diseases (7 papers), Cancer, Lipids, and Metabolism (6 papers), Adipokines, Inflammation, and Metabolic Diseases (6 papers), Immune Response and Inflammation (5 papers), RNA Interference and Gene Delivery (5 papers), Liver Disease Diagnosis and Treatment (5 papers), Cholesterol and Lipid Metabolism (5 papers) and Fatty Acid Research and Health (4 papers). The work is most often cited by research in Biological Psychiatry (50 citations), Immunology (334 citations), Hepatology (104 citations), Cancer Research (188 citations) and Periodontics (53 citations). Shao‐Chun Lu has collaborated with scholars based in Taiwan, United States and China. Frequent co-authors include Po‐Yuan Chang, Shwu‐Fen Chang, Hui‐Ling Chen, Chu‐Huang Chen, Shu‐Ching Hsu, Chia-Ying Chen, Po‐Chao Huang, Jung‐Yaw Lin, Chia‐Huei Lee and Jimmy Yu‐Wai Chan. Their work appears in journals such as Pharmacogenomics, Journal of Biomedical Science, The Journal of Nutritional Biochemistry, FEBS Journal and Annals of Nutrition and Metabolism.

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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