Phil Jun Kang

430 citations
15 papers · 329 · h-index 8

Impact in

Papers in

    • Pluripotent Stem Cells Research 8
    • CRISPR and Genetic Engineering 4
    • Peroxisome Proliferator-Activated Receptors 2
    • Tissue Engineering and Regenerative Medicine 2

Phil Jun Kang

14 papers receiving 326 citations

Peers

Phil Jun Kang
Comparison fields: 5 of 50
  • Genetics 108
  • Rehabilitation 54
  • Developmental Neuroscience 25
  • Molecular Biology 165
  • Cellular and Molecular Neuroscience 38
Replace Atsushi Fujiya with:
Atsushi Fujiya Japan
Chong-Un Cheong Taiwan
Eun Kyoung Jun South Korea
Cungang Fan China
Sheng-Ping Fu China
Joon-Seok Choi South Korea
Min-Young Lee South Korea
Po‐Cheng Lin Taiwan
Peisheng Jin China
Phil Jun Kang relative to Atsushi Fujiya Japan Atsushi Fujiya's profile →
Citations per field
00.5×1.5×1.9×
Atsushi Fujiya · 1×
Citations per year

Countries citing papers authored by Phil Jun Kang

Since Specialization
Citations

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

Fields of papers citing papers by Phil Jun Kang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Phil Jun Kang. 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 Phil Jun Kang. The network helps show where Phil Jun Kang may publish in the future.

Co-authors

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

All Works

15 of 15 papers shown
#Work
1 2014140
2 201643
3 201430
4 201923
5 201822
6 202321
7 201318
8 201912
9 20176
10 20174
11 20173
12 20203
13 20192
14 20172
15 20250

About Phil Jun Kang

Phil Jun Kang is a scholar working on Molecular Biology, Surgery, Cellular and Molecular Neuroscience, Clinical Biochemistry and Physiology, having authored 15 papers that have together received 329 indexed citations. Recurring topics across this work include Pluripotent Stem Cells Research (8 papers), CRISPR and Genetic Engineering (4 papers), Metabolism and Genetic Disorders (3 papers), Peroxisome Proliferator-Activated Receptors (2 papers), Neurogenesis and neuroplasticity mechanisms (2 papers), Tissue Engineering and Regenerative Medicine (2 papers), 3D Printing in Biomedical Research (2 papers) and Hereditary Neurological Disorders (2 papers). The work is most often cited by research in Genetics (108 citations), Rehabilitation (54 citations), Developmental Neuroscience (25 citations), Molecular Biology (165 citations) and Cellular and Molecular Neuroscience (38 citations). Phil Jun Kang has collaborated with scholars based in South Korea, Japan and Singapore. Frequent co-authors include Gyuman Park, Seungkwon You, Seungkwon You, Eun Sung Jun, Jung H. Lee, Qiankun Zhang, In Kim, Byung Sun Yoon, Jai-Hee Moon and Gwonhwa Song. Their work appears in journals such as Stem Cell Research, Biochemical and Biophysical Research Communications, Journal of Biomedical Science, Experimental & Molecular Medicine and Biomaterials.

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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