Li‐Hsing Chen

605 citations
12 papers · 541 · h-index 11

Impact in

Papers in

Li‐Hsing Chen

12 papers receiving 519 citations

Peers

Li‐Hsing Chen
Comparison fields: 5 of 57
  • Computational Theory and Mathematics 133
  • Organic Chemistry 133
  • Molecular Biology 254
  • Cancer Research 31
  • Oncology 29
Replace Takaaki A. Fukami with:
Takaaki A. Fukami Japan
Masako Kuno Japan
Mulugeta Mamo United States
Jonathan P. Hutchinson United Kingdom
Aras Emdadi United States
Sameh Eid Egypt
Patrick M. Eidam United States
Maria Tardugno Italy
Martin Schröder Germany
Markella Konstantinidou Netherlands
Li‐Hsing Chen relative to Takaaki A. Fukami Japan Takaaki A. Fukami's profile →
Citations per field
00.5×1.5×
Takaaki A. Fukami · 1×
Citations per year

Countries citing papers authored by Li‐Hsing Chen

Since Specialization
Citations

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

Fields of papers citing papers by Li‐Hsing Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

12 of 12 papers shown
#Work
1 2008168
2 200978
3 201069
4 200849
5 201133
6 200832
7 200726
8 200925
9 200921
10 200921
11 201113
12 20106

About Li‐Hsing Chen

Li‐Hsing Chen is a scholar working on Computational Theory and Mathematics, Cancer Research, Molecular Biology, Organic Chemistry and Oncology, having authored 12 papers that have together received 541 indexed citations. Recurring topics across this work include Bacillus and Francisella bacterial research (4 papers), Synthesis and biological activity (4 papers), Computational Drug Discovery Methods (4 papers), Protein Kinase Regulation and GTPase Signaling (3 papers), Protease and Inhibitor Mechanisms (3 papers), Structural and Chemical Analysis of Organic and Inorganic Compounds (2 papers), Chemical Synthesis and Analysis (2 papers) and Metal complexes synthesis and properties (2 papers). The work is most often cited by research in Computational Theory and Mathematics (133 citations), Organic Chemistry (133 citations), Molecular Biology (254 citations), Cancer Research (31 citations) and Oncology (29 citations). Li‐Hsing Chen has collaborated with scholars based in United States. Frequent co-authors include Maurizio Pellecchia, Surya Kanta De, John L. Stebbins, Aras Emdadi, Sherida L. Johnson, Megan M. Riel-Mehan, Thomas Machleidt, Jason F. Cellitti, Jesús Vázquez and Michael Karin. Their work appears in journals such as Journal of Medicinal Chemistry, Bioorganic & Medicinal Chemistry, Proceedings of the National Academy of Sciences, ChemMedChem and Bioorganic Chemistry.

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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