Keng‐Chang Tsai

2.7k citations
103 papers · 2.2k indexed · h-index 27
Topics
Computational Drug Discovery Methods (18 papers)Monoclonal and Polyclonal Antibodies Research (14 papers)Influenza Virus Research Studies (10 papers)
Partner nations
TaiwanUnited StatesChina

In The Last Decade

Keng‐Chang Tsai

100 papers receiving 2.1k citations

Peers

Keng‐Chang Tsai
Comparison fields: 5 of 132
  • Molecular Biology 975
  • Organic Chemistry 555
  • Computational Theory and Mathematics 406
  • Epidemiology 263
  • Infectious Diseases 249
Replace Yu‐Sheng Chao with:
Yu‐Sheng Chao Taiwan
Remo Perozzo Switzerland
Sun Choi South Korea
Gulam Mustafa Hasan India
Jérôme Eberhardt United States
Dharmendra Kumar Yadav India
Pedro A. Valiente Cuba
Thomas Scior Mexico
Sebastian Salentin Germany
Mario E. Valdés‐Tresanco Cuba
Keng‐Chang Tsai relative to Yu‐Sheng Chao Taiwan Yu‐Sheng Chao's profile →
Citations per field
00.5×
Yu‐Sheng Chao · 1×
Citations per year

Countries citing papers authored by Keng‐Chang Tsai

Since Specialization
Citations

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

Fields of papers citing papers by Keng‐Chang Tsai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Keng‐Chang Tsai. 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 Keng‐Chang Tsai. The network helps show where Keng‐Chang Tsai may publish in the future.

Co-authorship network of co-authors of Keng‐Chang Tsai

This figure shows the co-authorship network connecting the top 25 collaborators of Keng‐Chang Tsai. A scholar is included among the top collaborators of Keng‐Chang Tsai based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Keng‐Chang Tsai. Keng‐Chang Tsai is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
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11 1
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13 18
14 5
15 11
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18 58
19 31
20 14

About Keng‐Chang Tsai

Keng‐Chang Tsai is a scholar working on Toxicology, Pharmacology and Computational Theory and Mathematics, having authored 103 papers that have together received 2.2k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (18 papers), Monoclonal and Polyclonal Antibodies Research (14 papers) and Influenza Virus Research Studies (10 papers). The work is most often cited by research in Computational Theory and Mathematics (406 citations), Organic Chemistry (555 citations) and Molecular Biology (975 citations). Keng‐Chang Tsai has collaborated with scholars based in Taiwan, United States and China. Frequent co-authors include An‐Suei Yang, Chi‐Huey Wong, Jim‐Min Fang, Yih‐Shyun E. Cheng, Shiyun Wang, Tien‐Sheng Tseng, Yu‐Ching Lee, Minyong Li, Nai‐Wan Hsiao and Thy‐Hou Lin. Their work appears in journals such as Journal of the American Chemical Society, Journal of Biological Chemistry and PLoS ONE.

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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