Young Do Koo

848 citations
21 papers · 583 · h-index 14

Impact in

Papers in

    • Peroxisome Proliferator-Activated Receptors 4
    • Ubiquitin and proteasome pathways 3
    • Retinoids in leukemia and cellular processes 2
    • Metabolism, Diabetes, and Cancer 2
    • Adipose Tissue and Metabolism 4

Young Do Koo

21 papers receiving 572 citations

Peers

Young Do Koo
Comparison fields: 5 of 104
  • Health, Toxicology and Mutagenesis 149
  • Cancer Research 72
  • Statistics, Probability and Uncertainty 33
  • Signal Processing 43
  • Small Animals 23
Replace Jun Seok Kim with:
Jun Seok Kim South Korea
Dan Krewski Canada
Manoj Aggarwal United States
Zixuan Li China
Huiting Yang China
Jieting Wang China
Yanzhi Chen China
Jin Park South Korea
Bei Pei China
Timothy M. Chan United States
Young Do Koo relative to Jun Seok Kim South Korea Jun Seok Kim's profile →
Citations per field
00.5×6.8×
Jun Seok Kim · 1×
Citations per year

Countries citing papers authored by Young Do Koo

Since Specialization
Citations

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

Fields of papers citing papers by Young Do Koo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Young Do Koo. 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 Young Do Koo. The network helps show where Young Do Koo may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2012183
2 201854
3 201553
4 201836
5 201833
6 201927
7 201626
8 201626
9 201623
10 201719
11 202216
12 201716
13 201715
14 202115
15 202011
16 201810
17 20156
18 20095
19 20214
20 20173

About Young Do Koo

Young Do Koo is a scholar working on Molecular Biology, Physiology, Aerospace Engineering, Cancer Research and Statistics, Probability and Uncertainty, having authored 21 papers that have together received 583 indexed citations. Recurring topics across this work include Nuclear Engineering Thermal-Hydraulics (4 papers), Adipose Tissue and Metabolism (4 papers), Peroxisome Proliferator-Activated Receptors (4 papers), Ubiquitin and proteasome pathways (3 papers), Risk and Safety Analysis (3 papers), Cancer, Hypoxia, and Metabolism (3 papers), Retinoids in leukemia and cellular processes (2 papers) and Metabolism, Diabetes, and Cancer (2 papers). The work is most often cited by research in Health, Toxicology and Mutagenesis (149 citations), Cancer Research (72 citations), Statistics, Probability and Uncertainty (33 citations), Signal Processing (43 citations) and Small Animals (23 citations). Young Do Koo has collaborated with scholars based in South Korea, Puerto Rico and United States. Frequent co-authors include Kyong Soo Park, Young Joo Park, Man Gyun Na, Hak Chul Jang, Min Joo Kim, Sung Soo Chung, Min Kyong Moon, Soon Hee Kim, Yeo Cho Yoon and Young-Chul Yoon. Their work appears in journals such as Nuclear Engineering and Technology, Experimental & Molecular Medicine, Metabolism, Diabetes & Metabolism Journal and Cell 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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