Hsin‐Yi Chen

29 papers receiving 635 citations

Peers

Hsin‐Yi Chen
Comparison fields: 5 of 119
  • Complementary and alternative medicine 70
  • Computational Theory and Mathematics 110
  • Information Systems and Management 38
  • Pharmacology 41
  • Plant Science 175
Replace Ajantha Sinniah with:
Ajantha Sinniah Malaysia
Kun‐Yi Hsin Japan
Zhuolun Li China
Serge Eifes Luxembourg
P. Sasikala India
Rong Chen China
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Sally R. Ellingson United States
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Citations per field
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Citations per year

Countries citing papers authored by Hsin‐Yi Chen

Since Specialization
Citations

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

Fields of papers citing papers by Hsin‐Yi Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 30 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2015182
2 201139
3 201937
4 201935
5 202334
6 201934
7 201432
8
Effect of Personalization on the Perceived Usefulness of Online Customer Services: A Dual-Core Theory
201230
9 200925
10 201321
11 201420
12 201417
13 201816
14 202016
15 202015
16 201915
17 202012
18 201412
19 201412
20 20149

About Hsin‐Yi Chen

Hsin‐Yi Chen is a scholar working on Molecular Biology, Computational Theory and Mathematics, Immunology, Pharmacology and Oncology, having authored 30 papers that have together received 644 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (9 papers), Cholinesterase and Neurodegenerative Diseases (3 papers), Plant biochemistry and biosynthesis (3 papers), interferon and immune responses (2 papers), Metabolomics and Mass Spectrometry Studies (2 papers), Receptor Mechanisms and Signaling (2 papers), Toxin Mechanisms and Immunotoxins (2 papers) and Customer Service Quality and Loyalty (2 papers). The work is most often cited by research in Complementary and alternative medicine (70 citations), Computational Theory and Mathematics (110 citations), Information Systems and Management (38 citations), Pharmacology (41 citations) and Plant Science (175 citations). Hsin‐Yi Chen has collaborated with scholars based in Taiwan, China and United States. Frequent co-authors include Calvin Yu‐Chian Chen, Kuan‐Chung Chen, Calvin Yu‐Chian Chen, Ya‐Chi Yu, Dorothea Tholl, Li‐Qing Chen, Woei‐Jiun Guo, Wolf B. Frommer, Jung‐Hyun Huh and Qiujie Lv. Their work appears in journals such as BioMed Research International, RSC Advances, The Journal of Physical Chemistry Letters, Evidence-based Complementary and Alternative Medicine and Briefings in Bioinformatics.

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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