Su Wang

1.4k citations
10 papers · 395 · h-index 8

Impact in

  • Immunology top 10%
    • Immunotherapy and Immune Responses
    • T-cell and B-cell Immunology
    • Immune Cell Function and Interaction
    • Immune Response and Inflammation

Papers in

    • Immunotherapy and Immune Responses 3
    • Aquaculture disease management and microbiota 3
    • interferon and immune responses 1
    • Invertebrate Immune Response Mechanisms 1
    • Zebrafish Biomedical Research Applications 2

Su Wang

8 papers receiving 373 citations

Peers

Su Wang
Comparison fields: 5 of 71
  • Immunology 259
  • Virology 24
  • Aging 6
  • Microbiology 18
  • Infectious Diseases 43
Replace A. V. Kubarenko with:
A. V. Kubarenko Germany
David Drexler Germany
Sumit Sen Santara India
Maria Tokuyama United States
Hua‐Chen Chang United States
Sudhirdas Prayaga United States
Detlef Stober Germany
Paushali Mukherjee India
Saliha Majdoul United States
Su Wang relative to A. V. Kubarenko Germany A. V. Kubarenko's profile →
Citations per field
00.5×
A. V. Kubarenko · 1×
Citations per year

Countries citing papers authored by Su Wang

Since Specialization
Citations

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

Fields of papers citing papers by Su Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

10 of 10 papers shown
#Work
1 1997239
2 200770
3 201919
4 201819
5 201818
6 201315
7 20198
8 20237
9 20240
10 20240

About Su Wang

Su Wang is a scholar working on Immunology, Cell Biology, Statistics and Probability, Surgery and Molecular Biology, having authored 10 papers that have together received 395 indexed citations. Recurring topics across this work include Immunotherapy and Immune Responses (3 papers), Aquaculture disease management and microbiota (3 papers), Zebrafish Biomedical Research Applications (2 papers), Statistical Methods in Clinical Trials (2 papers), interferon and immune responses (1 paper), Invertebrate Immune Response Mechanisms (1 paper), Hydrogen's biological and therapeutic effects (1 paper) and Apelin-related biomedical research (1 paper). The work is most often cited by research in Immunology (259 citations), Virology (24 citations), Aging (6 citations), Microbiology (18 citations) and Infectious Diseases (43 citations). Su Wang has collaborated with scholars based in China and United States. Frequent co-authors include Michael J. Caulfield, R. Randall Deck, Arthur Friedman, Xu Liu, Hans Wigzell, Tong‐Ming Fu, John Donnelly, Jeffrey B. Ulmer, Margaret A. Liu and Shicui Zhang. Their work appears in journals such as Fish & Shellfish Immunology, Oncotarget, Human Vaccines, Therapeutic Innovation & Regulatory Science and Clinical Therapeutics.

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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