Youngjun Park

423 citations
14 papers · 265 · h-index 8

Impact in

    • Cancer Genomics and Diagnostics
    • Machine Learning in Bioinformatics
    • Bioinformatics and Genomic Networks
    • Genomics and Phylogenetic Studies
    • RNA and protein synthesis mechanisms

Papers in

    • Bioinformatics and Genomic Networks 6
    • Gene expression and cancer classification 5
    • Single-cell and spatial transcriptomics 4
    • Cancer Genomics and Diagnostics 5

Youngjun Park

12 papers receiving 263 citations

Peers

Youngjun Park
Comparison fields: 5 of 56
  • Cancer Research 61
  • Molecular Biology 171
  • Computational Theory and Mathematics 34
  • Pulmonary and Respiratory Medicine 60
  • Biophysics 9
Replace Angelo Limeta with:
Angelo Limeta Sweden
Tommaso Palmieri United Kingdom
Kirill Zhudenkov United States
Aikaterini Tourna United Kingdom
Joel Nulsen United Kingdom
Lisa Dreßler United Kingdom
Santhilata Kuppili Venkata United Kingdom
Nitin Sharma United Kingdom
Lu Meng China
Glyn Bradley United Kingdom
Youngjun Park relative to Angelo Limeta Sweden Angelo Limeta's profile →
Citations per field
00.5×4.8×
Angelo Limeta · 1×
Citations per year

Countries citing papers authored by Youngjun Park

Since Specialization
Citations

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

Fields of papers citing papers by Youngjun Park

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

14 of 14 papers shown
#Work
1 201891
2 201639
3 199937
4 202027
5 202122
6 201617
7 201713
8 202110
9 20245
10 20242
11 20171
12 20201
13 20250
14 20240

About Youngjun Park

Youngjun Park is a scholar working on Molecular Biology, Cancer Research, Pulmonary and Respiratory Medicine, Genetics and Biophysics, having authored 14 papers that have together received 265 indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (6 papers), Cancer Genomics and Diagnostics (5 papers), Gene expression and cancer classification (5 papers), Single-cell and spatial transcriptomics (4 papers), Cell Image Analysis Techniques (2 papers), Inflammatory Bowel Disease (2 papers), Ferroptosis and cancer prognosis (2 papers) and Computational Drug Discovery Methods (1 paper). The work is most often cited by research in Cancer Research (61 citations), Molecular Biology (171 citations), Computational Theory and Mathematics (34 citations), Pulmonary and Respiratory Medicine (60 citations) and Biophysics (9 citations). Youngjun Park has collaborated with scholars based in South Korea, Germany and Ethiopia. Frequent co-authors include Sun Kim, Minsik Oh, Seokjun Seo, Sangsoo Lim, Anne-Christin Hauschild, Dominik Heider, Jin‐Wu Nam, Y. Y. Koh, Sangseon Lee and Benjamin Hur. Their work appears in journals such as Methods, Briefings in Bioinformatics, Journal of Crohn s and Colitis, Computers in Biology and Medicine and Scientific Reports.

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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