Stephen V. Su

28 papers receiving 2.1k citations

Stephen V. Su's Hit Papers

mRNA structure regulates protein expression through changes in functional half-life 2019 · 399 citations
3990+2+4Years since publication100200300

Peers

Stephen V. Su
Comparison fields: 5 of 98
  • Virology 149
  • Immunology 482
  • Infectious Diseases 346
  • Molecular Biology 1.1k
  • Epidemiology 474
Replace Petra Neddermann with:
Petra Neddermann Italy
George E. Mark United States
Seng-Lai Tan United States
Philippe Emmanuel Mangeot France
Eugenio Santelli United States
Thierry Chardès France
Seng‐Lai Tan United States
Christine Thumann France
Patrick R. Romano United States
Karen E. Johnson United States
Stephen V. Su relative to Petra Neddermann Italy Petra Neddermann's profile →
Citations per field
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Petra Neddermann · 1×
Citations per year

Countries citing papers authored by Stephen V. Su

Since Specialization
Citations

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

Fields of papers citing papers by Stephen V. Su

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Stephen V. Su. 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 Stephen V. Su. The network helps show where Stephen V. Su may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 28 papers — load more, or switch the sort, to bring in the rest.

#Work
1
mRNA structure regulates protein expression through changes in functional half-life
Hit paper breakdown →
2019399
2 2006274
3 2020272
4 2019265
5 2006176
6 200878
7 200676
8 200870
9 200966
10 200456
11 200550
12 200739
13 199738
14 200933
15 200430
16 201929
17 201126
18 200323
19 200920
20 201919

About Stephen V. Su

Stephen V. Su is a scholar working on Virology, Immunology, Oncology, Molecular Biology and Pharmacology, having authored 28 papers that have together received 2.1k indexed citations. Recurring topics across this work include HIV Research and Treatment (4 papers), RNA and protein synthesis mechanisms (4 papers), Cytokine Signaling Pathways and Interactions (3 papers), RNA Research and Splicing (3 papers), Glycosylation and Glycoproteins Research (3 papers), Immunotherapy and Immune Responses (3 papers), Immune cells in cancer (2 papers) and RNA Interference and Gene Delivery (2 papers). The work is most often cited by research in Virology (149 citations), Immunology (482 citations), Infectious Diseases (346 citations), Molecular Biology (1.1k citations) and Epidemiology (474 citations). Stephen V. Su has collaborated with scholars based in United States, Australia and Sweden. Frequent co-authors include Benhur Lee, Nikhil Khatwani, Oscar A Negrete, Andrea Bertolotti‐Ciarlet, Hector Aguilar-Carreno, Mike C. Wolf, Kristian H. Link, Vladimir Presnyak, Melissa J. Moore and David W. Reid. Their work appears in journals such as Bioorganic & Medicinal Chemistry Letters, Journal of Virology, Proceedings of the National Academy of Sciences, Australian Journal of Chemistry and Current HIV 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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