Shuda Chen

35 papers receiving 734 citations

Peers

Shuda Chen
Comparison fields: 5 of 102
  • Fluid Flow and Transfer Processes 60
  • Filtration and Separation 20
  • Cellular and Molecular Neuroscience 123
  • Pharmacology 100
  • Pediatrics, Perinatology and Child Health 94
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Nuno Pires Portugal
Said H. Audi United States
Atsushi Tsuchiya Japan
Chengyuan Wang China
Renata Zajączkowska Poland
Daisuke Takahashi Japan
Т. Д. Власов Russia
Tim Ibbotson United Kingdom
Hideo Shio Japan
Haihong Zhou China
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Citations per field
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Citations per year

Countries citing papers authored by Shuda Chen

Since Specialization
Citations

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

Fields of papers citing papers by Shuda Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 36 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Quantitative MR evaluation of intracranial epidermoid tumors by fast fluid-attenuated inversion recovery imaging and echo-planar diffusion-weighted imaging.
2001130
2 2011100
3 200878
4 201549
5 201649
6 200547
7 201643
8 201131
9 201829
10 201620
11 200216
12 200715
13 201314
14 201613
15 202211
16 201411
17 20099
18 20019
19 20228
20 20197

About Shuda Chen

Shuda Chen is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience, Organic Chemistry, Psychiatry and Mental health and Cognitive Neuroscience, having authored 36 papers that have together received 746 indexed citations. Recurring topics across this work include Neuroscience and Neuropharmacology Research (6 papers), Epilepsy research and treatment (5 papers), Ion channel regulation and function (5 papers), Ion Transport and Channel Regulation (3 papers), Phase Equilibria and Thermodynamics (3 papers), Computational Drug Discovery Methods (3 papers), Thermodynamic properties of mixtures (3 papers) and Analytical Chemistry and Chromatography (3 papers). The work is most often cited by research in Fluid Flow and Transfer Processes (60 citations), Filtration and Separation (20 citations), Cellular and Molecular Neuroscience (123 citations), Pharmacology (100 citations) and Pediatrics, Perinatology and Child Health (94 citations). Shuda Chen has collaborated with scholars based in China, United States and Türkiye. Frequent co-authors include Liemin Zhou, Jueqian Zhou, Ziyi Chen, Wenjun Fang, Fusao Ikawa, Yukari Kanou, Junko Takaba, Kaoru Kurisu, Qunfang Lei and Yinghong Hu. Their work appears in journals such as Neurological Sciences, Seizure, Brain Research, Journal of Chemical & Engineering Data and Epilepsy & Behavior.

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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