Suzhen Chen

49 papers receiving 1.5k citations

Peers

Suzhen Chen
Comparison fields: 5 of 122
  • Developmental Neuroscience 279
  • Cellular and Molecular Neuroscience 488
  • Neurology 163
  • Cell Biology 211
  • Molecular Biology 760
Replace L T Zhong with:
L T Zhong United States
Harald Frankowski United States
Jaya Padmanabhan United States
Margrit Hollborn Germany
Arantxa Tabernero Spain
Dominic C.H. Ng Australia
Kambiz N. Alavian United States
Jilin Sun United States
Zhifang Li China
Baolin Li China
Suzhen Chen relative to L T Zhong United States L T Zhong's profile →
Citations per field
00.5×10×20×30×44.7×
L T Zhong · 1×
Citations per year

Countries citing papers authored by Suzhen Chen

Since Specialization
Citations

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

Fields of papers citing papers by Suzhen Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 50 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1999195
2 2003156
3 2021154
4 1999153
5 2003132
6 200592
7 200392
8 202171
9 200057
10 200751
11 201635
12 201530
13 200323
14
Protective role of JNK inhibitor SP600125 in sepsis-induced acute lung injury.
201920
15 201019
16 201919
17 201319
18 200217
19 202416
20 200316

About Suzhen Chen

Suzhen Chen is a scholar working on Library and Information Sciences, Developmental Neuroscience, Biochemistry, Physiology and Cellular and Molecular Neuroscience, having authored 50 papers that have together received 1.5k indexed citations. Recurring topics across this work include Adipose Tissue and Metabolism (6 papers), Metabolism, Diabetes, and Cancer (5 papers), Liver Disease Diagnosis and Treatment (5 papers), Endoplasmic Reticulum Stress and Disease (4 papers), Glycosylation and Glycoproteins Research (4 papers), Nerve injury and regeneration (3 papers), Lipid metabolism and biosynthesis (3 papers) and Peroxisome Proliferator-Activated Receptors (3 papers). The work is most often cited by research in Developmental Neuroscience (279 citations), Cellular and Molecular Neuroscience (488 citations), Neurology (163 citations), Cell Biology (211 citations) and Molecular Biology (760 citations). Suzhen Chen has collaborated with scholars based in China, United States and Germany. Frequent co-authors include Melitta Schachner, Ling Dong, Martin Grumet, Ling Dong, Ned Mantei, Sylvain Lehmann, Alain Mangé, Ronald D. Graff, John J. Hemperly and Patricia F. Maness. Their work appears in journals such as Obesity, Cell Metabolism, Nutrition & Metabolism, Journal of Molecular Cell Biology and Molecular and Cellular Neuroscience.

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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