Di Sun

22 papers receiving 912 citations

Peers

Di Sun
Comparison fields: 5 of 80
  • Virology 273
  • Infectious Diseases 207
  • Health, Toxicology and Mutagenesis 123
  • Molecular Biology 546
  • Genetics 153
Replace Kuan-Teh Jeang with:
Kuan-Teh Jeang United States
Albert Leonard Ruff United States
Linda Yen United States
Jaime Sanchez-Dardon Canada
Simone C. Zimmerli Switzerland
Daniela Lener France
Perungavur N. Ranganathan United States
Gabriel N. Maine United States
Paz J. Luncsford United States
Isabelle Bouchaert France
Di Sun relative to Kuan-Teh Jeang United States Kuan-Teh Jeang's profile →
Citations per field
00.5×2×3×4×4.7×
Kuan-Teh Jeang · 1×
Citations per year

Countries citing papers authored by Di Sun

Since Specialization
Citations

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

Fields of papers citing papers by Di Sun

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 25 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1988216
2 1989188
3 1993110
4 199389
5 201669
6 201253
7 199338
8 201537
9 201635
10 201731
11 199431
12 199528
13 202225
14 201522
15 202318
16 199214
17 20244
18 20253
19 20252
20 20241

About Di Sun

Di Sun is a scholar working on Virology, Endocrinology, Diabetes and Metabolism, Health, Toxicology and Mutagenesis, Cellular and Molecular Neuroscience and Reproductive Medicine, having authored 25 papers that have together received 1.0k indexed citations. Recurring topics across this work include HIV Research and Treatment (8 papers), Effects and risks of endocrine disrupting chemicals (4 papers), HIV/AIDS drug development and treatment (3 papers), Thyroid Cancer Diagnosis and Treatment (3 papers), T-cell and Retrovirus Studies (3 papers), Neuropeptides and Animal Physiology (3 papers), CRISPR and Genetic Engineering (2 papers) and Hypothalamic control of reproductive hormones (2 papers). The work is most often cited by research in Virology (273 citations), Infectious Diseases (207 citations), Health, Toxicology and Mutagenesis (123 citations), Molecular Biology (546 citations) and Genetics (153 citations). Di Sun has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Sudhir Agrawal, Paul C. Zamecnik, Prem S. Sarin, Julianna Lisziewicz, John Goodchild, Maria Pilar Civeira, Jacob V. Maizel, Allan E. Konopka, T Ikeuchi and Jason A. Smythe. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of Virology, International Journal of Environmental Research and Public Health, Experimental and Clinical Endocrinology & Diabetes and Endocrine Practice.

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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