Kena Wang

839 citations
18 papers · 642 · h-index 7

Impact in

  • Immunology top 10%
    • Immune Cell Function and Interaction
    • Immunotherapy and Immune Responses
    • T-cell and B-cell Immunology
  • Genetics top 10%
    • Virus-based gene therapy research

Papers in

Kena Wang

18 papers receiving 611 citations

Peers

Kena Wang
Comparison fields: 5 of 70
  • Immunology 256
  • Genetics 201
  • Virology 26
  • Molecular Biology 317
  • Cell Biology 73
Replace Yasir Mohamud with:
Yasir Mohamud Canada
Peter Walden United States
Patricio Meneses United States
Dina Anderson United States
Naoto Koyanagi Japan
Chen Seng Ng Canada
Emma Nilsson Sweden
Linda J. Visser Netherlands
Jonathan Diep United States
Hamish Allen United States
Kena Wang relative to Yasir Mohamud Canada Yasir Mohamud's profile →
Citations per field
00.5×1.5×2.1×
Yasir Mohamud · 1×
Citations per year

Countries citing papers authored by Kena Wang

Since Specialization
Citations

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

Fields of papers citing papers by Kena Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

18 of 18 papers shown
#Work
1 1994267
2 1998166
3 200068
4 199732
5 202331
6 199429
7 199721
8 20155
9 20214
10 20234
11 20174
12 20083
13 20222
14 20142
15 20221
16 19941
17 20211
18 20131

About Kena Wang

Kena Wang is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience, Computer Vision and Pattern Recognition, Genetics and Infectious Diseases, having authored 18 papers that have together received 642 indexed citations. Recurring topics across this work include Epigenetics and DNA Methylation (3 papers), Neurotransmitter Receptor Influence on Behavior (3 papers), Image and Object Detection Techniques (2 papers), Advanced Vision and Imaging (2 papers), Virus-based gene therapy research (2 papers), Metallurgy and Material Forming (1 paper), Autonomous Vehicle Technology and Safety (1 paper) and Metabolism and Genetic Disorders (1 paper). The work is most often cited by research in Immunology (256 citations), Genetics (201 citations), Virology (26 citations), Molecular Biology (317 citations) and Cell Biology (73 citations). Kena Wang has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Per A. Peterson, Glen R. Nemerow, Klaus Früh, David B. Williams, Woong‐Kyung Suh, Myrna F. Cohen-Doyle, Shuang Huang, David A. Cheresh, Tinglu Guan and Lars Karlsson. Their work appears in journals such as Journal of Virology, FEBS Letters, Frontiers in Pediatrics, Medicine and Brain 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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