Dai‐Lun Shin

442 citations
12 papers · 202 · h-index 7

Impact in

    • Viral gastroenteritis research and epidemiology
    • Viral Infections and Vectors
    • Influenza Virus Research Studies
    • Respiratory viral infections research

Papers in

    • Respiratory viral infections research 8
    • Influenza Virus Research Studies 6
    • Virology and Viral Diseases 3
    • SARS-CoV-2 and COVID-19 Research 2

Dai‐Lun Shin

12 papers receiving 185 citations

Peers

Dai‐Lun Shin
Comparison fields: 5 of 45
  • Infectious Diseases 82
  • Epidemiology 138
  • Agronomy and Crop Science 43
  • Animal Science and Zoology 25
  • Immunology 46
Replace Ericka Kirkpatrick Roubidoux with:
Ericka Kirkpatrick Roubidoux United States
Meng Hu United States
Jojanneke Dekkers Netherlands
Christopher R. E. Ward Canada
Elizabeth M. Drapeau United States
Udayan Joseph Singapore
Muneeswaran Selvaraj United Kingdom
Longfa Xu China
Veronica Martini United Kingdom
Dai‐Lun Shin relative to Ericka Kirkpatrick Roubidoux United States Ericka Kirkpatrick Roubidoux's profile →
Citations per field
00.5×1.5×2.1×
Ericka Kirkpatrick Roubidoux · 1×
Citations per year

Countries citing papers authored by Dai‐Lun Shin

Since Specialization
Citations

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

Fields of papers citing papers by Dai‐Lun Shin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Dai‐Lun Shin. 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 Dai‐Lun Shin. The network helps show where Dai‐Lun Shin may publish in the future.

Co-authors

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

All Works

12 of 12 papers shown
#Work
1 201957
2 201541
3 201424
4 202119
5 202018
6 202213
7 202013
8 20225
9 20234
10 20144
11 20223
12 20251

About Dai‐Lun Shin

Dai‐Lun Shin is a scholar working on Epidemiology, Infectious Diseases, Immunology, Molecular Biology and Animal Science and Zoology, having authored 12 papers that have together received 202 indexed citations. Recurring topics across this work include Respiratory viral infections research (8 papers), Influenza Virus Research Studies (6 papers), Virology and Viral Diseases (3 papers), Animal Disease Management and Epidemiology (2 papers), SARS-CoV-2 and COVID-19 Research (2 papers), Immune Response and Inflammation (2 papers), Animal Virus Infections Studies (2 papers) and Virus-based gene therapy research (2 papers). The work is most often cited by research in Infectious Diseases (82 citations), Epidemiology (138 citations), Agronomy and Crop Science (43 citations), Animal Science and Zoology (25 citations) and Immunology (46 citations). Dai‐Lun Shin has collaborated with scholars based in Germany, Taiwan and China. Frequent co-authors include Georg Herrler, Nai‐Huei Wu, Klaus Schughart, Bastian Hatesuer, Tatiana Nedelko, Silke Bergmann, Ludwig Haas, Ursula Siebert, Peter Valentin‐Weigand and Jan Lakemeyer. Their work appears in journals such as Viruses, Poultry Science, Journal of Virology, G3 Genes Genomes Genetics 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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