Kaijin Wu

1.1k citations
30 papers · 955 · h-index 19

Impact in

  • Cell Biology top 10%
    • Endoplasmic Reticulum Stress and Disease
    • Cellular transport and secretion
  • Physiology top 10%
    • Salivary Gland Disorders and Functions

Papers in

Kaijin Wu

30 papers receiving 937 citations

Peers

Kaijin Wu
Comparison fields: 5 of 86
  • Cell Biology 199
  • Physiology 188
  • Public Health, Environmental and Occupational Health 169
  • Oncology 150
  • Immunology and Allergy 32
Replace Lisa Dillard‐Telm with:
Lisa Dillard‐Telm United States
WeiYu Lin United States
David G. Ryan United States
Maria Teresa Perra Italy
Mario Mairhofer Austria
S Roy Himes Australia
Phil Hass United States
Masaharu Ohbayashi Japan
Laura Ann Adang United States
Kyu‐Seon Oh United States
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Citations per field
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Lisa Dillard‐Telm · 1×
Citations per year

Countries citing papers authored by Kaijin Wu

Since Specialization
Citations

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

Fields of papers citing papers by Kaijin Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 30 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2018114
2 200576
3 201067
4 201764
5 200763
6 201054
7 201846
8 201942
9 200642
10 199539
11 200539
12 199538
13
The Rb gene suppresses the growth of normal cells.
199338
14 200632
15 200929
16 201228
17 200925
18 200621
19 201819
20 201615

About Kaijin Wu

Kaijin Wu is a scholar working on Physiology, Public Health, Environmental and Occupational Health, Genetics, Cell Biology and Hematology, having authored 30 papers that have together received 955 indexed citations. Recurring topics across this work include Ocular Surface and Contact Lens (7 papers), Salivary Gland Disorders and Functions (5 papers), Virus-based gene therapy research (4 papers), Glycosylation and Glycoproteins Research (3 papers), Cellular transport and secretion (3 papers), Cancer Genomics and Diagnostics (2 papers), Cholesterol and Lipid Metabolism (2 papers) and Growth Hormone and Insulin-like Growth Factors (2 papers). The work is most often cited by research in Cell Biology (199 citations), Physiology (188 citations), Public Health, Environmental and Occupational Health (169 citations), Oncology (150 citations) and Immunology and Allergy (32 citations). Kaijin Wu has collaborated with scholars based in United States, China and Italy. Frequent co-authors include Sarah F. Hamm‐Alvarez, Joel Schechter, Kevin R. Kelly, Chuanqing Ding, Katja Schenke‐Layland, Jiansong Xie, Amy Shiu Lee, Frank J. Talamantes, Christopher J. Rhodes and Xiaodong Li. Their work appears in journals such as Experimental Eye Research, Investigative Ophthalmology & Visual Science, PLoS ONE, Endocrinology and Life Science Alliance.

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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