Jonathan Chan

1.4k citations
22 papers · 680 · h-index 11

Impact in

  • Virology top 5%
    • HIV Research and Treatment
    • Biomedical Text Mining and Ontologies
    • Histone Deacetylase Inhibitors Research
    • Muscle Physiology and Disorders
    • Ubiquitin and proteasome pathways

Papers in

Jonathan Chan

21 papers receiving 668 citations

Peers

Jonathan Chan
Comparison fields: 5 of 136
  • Virology 120
  • Molecular Biology 403
  • Immunology 106
  • Health Informatics 6
  • Cancer Research 64
Replace Peter Yang with:
Peter Yang United States
Xosé M. Fernández United Kingdom
Ziqing Liu United States
Öznur Taştan Türkiye
Minji Seo South Korea
Deepak Sharma United States
Pierre Dönnes Germany
Anna Maria Masci United States
Cliburn Chan United States
J. Lynn Fink Australia
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Citations per field
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Citations per year

Countries citing papers authored by Jonathan Chan

Since Specialization
Citations

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

Fields of papers citing papers by Jonathan Chan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Jonathan Chan, 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 Jonathan Chan Line = papers co-authored together Jonathan Chan 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 2012155
2 2005132
3 201275
4 201564
5 200363
6 201352
7 201728
8 201720
9 202318
10 201913
11 197312
12 202410
13 20118
14 20208
15 20217
16 20214
17 20123
18 20123
19 20033
20
The Ubiquitin-Proteasome Pathway Generates Keratin 6A-Derived Antimicrobial Peptides to Mediate Antimicrobial Activities in Human Corneal Epithelial Cells
20161

About Jonathan Chan

Jonathan Chan is a scholar working on Molecular Biology, Artificial Intelligence, Microbiology, Immunology and Infectious Diseases, having authored 22 papers that have together received 680 indexed citations. Recurring topics across this work include Genetics, Bioinformatics, and Biomedical Research (3 papers), Antimicrobial Peptides and Activities (3 papers), HIV Research and Treatment (2 papers), COVID-19 diagnosis using AI (2 papers), Ocular Surface and Contact Lens (2 papers), Histone Deacetylase Inhibitors Research (2 papers), HIV/AIDS drug development and treatment (2 papers) and Machine Learning in Bioinformatics (1 paper). The work is most often cited by research in Virology (120 citations), Molecular Biology (403 citations), Immunology (106 citations), Health Informatics (6 citations) and Cancer Research (64 citations). Jonathan Chan has collaborated with scholars based in United States, Thailand and Canada. Frequent co-authors include Warner C. Greene, Zhenguo Wu, Kewei Ma, Guang Zhu, Yang Yang, Fei Zhu, Cheng Zhang, Preecha Patumcharoenpol, Asawin Meechai and Bairong Shen. Their work appears in journals such as Journal of Biological Chemistry, The Journal of Cell Biology, BMC Bioinformatics, Physical Review Letters and Immunological Reviews.

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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