Tai‐Ling Chao

1.2k citations
41 papers · 652 · h-index 14

Impact in

Papers in

    • SARS-CoV-2 and COVID-19 Research 26
    • COVID-19 Clinical Research Studies 9
    • SARS-CoV-2 detection and testing 5
    • Viral gastroenteritis research and epidemiology 3
    • interferon and immune responses 6

Tai‐Ling Chao

40 papers receiving 645 citations

Peers

Tai‐Ling Chao
Comparison fields: 5 of 86
  • Infectious Diseases 384
  • Computational Theory and Mathematics 91
  • Animal Science and Zoology 43
  • Immunology 74
  • Epidemiology 104
Replace Monique Laidlaw with:
Monique Laidlaw United States
Thi-Tuyet-Nhung Le France
Paula Monteiro Perin Germany
Junwen Luan China
Miya K. Bidon United States
Cornelius Rohde Germany
Kirstin Mösbauer Germany
Oliver Pilgram Germany
Danielle E. Dorosky United States
Meehyun Ko South Korea
Tai‐Ling Chao relative to Monique Laidlaw United States Monique Laidlaw's profile →
Citations per field
00.5×10×13.9×
Monique Laidlaw · 1×
Citations per year

Countries citing papers authored by Tai‐Ling Chao

Since Specialization
Citations

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

Fields of papers citing papers by Tai‐Ling Chao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tai‐Ling Chao. 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 Tai‐Ling Chao. The network helps show where Tai‐Ling Chao may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 41 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020195
2 200643
3 201341
4 202038
5 202136
6 202134
7 202126
8 202222
9 202120
10 202219
11 202017
12 202216
13 202215
14 202014
15 202313
16 202311
17 200510
18 20229
19 20227
20 20246

About Tai‐Ling Chao

Tai‐Ling Chao is a scholar working on Infectious Diseases, Immunology, Animal Science and Zoology, Molecular Biology and Epidemiology, having authored 41 papers that have together received 652 indexed citations. Recurring topics across this work include SARS-CoV-2 and COVID-19 Research (26 papers), COVID-19 Clinical Research Studies (9 papers), Animal Virus Infections Studies (7 papers), interferon and immune responses (6 papers), Computational Drug Discovery Methods (6 papers), SARS-CoV-2 detection and testing (5 papers), Viral gastroenteritis research and epidemiology (3 papers) and Influenza Virus Research Studies (3 papers). The work is most often cited by research in Infectious Diseases (384 citations), Computational Theory and Mathematics (91 citations), Animal Science and Zoology (43 citations), Immunology (74 citations) and Epidemiology (104 citations). Tai‐Ling Chao has collaborated with scholars based in Taiwan, United States and China. Frequent co-authors include Sui‐Yuan Chang, Ya‐Min Tsai, Pei‐Jer Chen, Ya‐Wen Cheng, Shiou-Hwei Yeh, Mi‐Hua Tao, Pan‐Chyr Yang, Kuo‐Yen Huang, Lily Wang and Pi‐Han Lin. Their work appears in journals such as Applied Microbiology and Biotechnology, Pharmaceutics, ACS Omega, International Journal of Molecular Sciences and Antiviral Research.

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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