Sheldon Tai

1.4k citations
22 papers · 580 · h-index 14

Impact in

Papers in

Sheldon Tai

21 papers receiving 571 citations

Peers

Sheldon Tai
Comparison fields: 5 of 100
  • Virology 124
  • Infectious Diseases 116
  • General Dentistry 10
  • Modeling and Simulation 21
  • Epidemiology 128
Replace Rishikesh Kumar with:
Rishikesh Kumar India
Sergeev Aa Russia
Jennifer German United States
Chang Lu France
Marie O. Pohl Switzerland
Anna Ilinskaya United States
Leon C. W. Lin Australia
Chenguang Shen China
Vincent Moulés France
Thakshila Amarasena Australia
Sheldon Tai relative to Rishikesh Kumar India Rishikesh Kumar's profile →
Citations per field
00.5×5.3×
Rishikesh Kumar · 1×
Citations per year

Countries citing papers authored by Sheldon Tai

Since Specialization
Citations

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

Fields of papers citing papers by Sheldon Tai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2022145
2 201371
3 201567
4 202045
5 202136
6 201032
7 202230
8 202224
9 201322
10 201617
11 201616
12 201715
13 202114
14 201613
15 201911
16 20207
17 20156
18 20213
19 20223
20 20202

About Sheldon Tai

Sheldon Tai is a scholar working on Epidemiology, Infectious Diseases, Molecular Biology, Virology and Pulmonary and Respiratory Medicine, having authored 22 papers that have together received 580 indexed citations. Recurring topics across this work include Herpesvirus Infections and Treatments (7 papers), HIV Research and Treatment (5 papers), Cytomegalovirus and herpesvirus research (5 papers), Infection Control and Ventilation (4 papers), Virus-based gene therapy research (3 papers), Influenza Virus Research Studies (3 papers), RNA and protein synthesis mechanisms (3 papers) and Biosensors and Analytical Detection (3 papers). The work is most often cited by research in Virology (124 citations), Infectious Diseases (116 citations), General Dentistry (10 citations), Modeling and Simulation (21 citations) and Epidemiology (128 citations). Sheldon Tai has collaborated with scholars based in United States, Canada and Switzerland. Frequent co-authors include Donald K. Milton, Jennifer German, Olga A. Nikolaitchik, Wei-Shau Hu, Vinay K. Pathak, Roger K. Maes, Masahiro Niikura, Hans H. Cheng, Annabel G. Wise and Tian Li. Their work appears in journals such as Virus Research, Virology, Clinical Infectious Diseases, European Journal of Medicinal Chemistry and Sensors and Actuators B Chemical.

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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