Dong-Jun Koo
Impact in
- Developmental Neuroscience top 10%
- Neurogenesis and neuroplasticity mechanisms
- Biomedical Engineering top 10%
- 3D Printing in Biomedical Research
- Innovative Microfluidic and Catalytic Techniques Innovation
- Microfluidic and Bio-sensing Technologies
Papers in
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- 3D Printing in Biomedical Research 4
- Nanoplatforms for cancer theranostics 2
-
- Nanoparticle-Based Drug Delivery 2
- Co-authors
- Sung‐Yon Kim (7 shared papers)Dal‐Hee Min (3 shared papers)Seongchan Kim (3 shared papers)Noo Li Jeon (2 shared papers)Somin Lee (1 shared paper)Hyojin Lee (2 shared papers)James Yu (1 shared paper)Joon Myong Song (1 shared paper)
- Journals
- Science Advances (2 papers)Neuron (1 paper)ACS Nano (1 paper)Nature Communications (1 paper)Acta Biomaterialia (1 paper)
- Partner nations
- South KoreaUnited StatesArmenia
In The Last Decade
Dong-Jun Koo
9 papers receiving 488 citations
Dong-Jun Koo's Hit Papers
Peers
Comparison fields: 5 of 68
- Developmental Neuroscience 36
- Biomedical Engineering 291
- Health Informatics 8
- Cellular and Molecular Neuroscience 75
- Oncology 85
Countries citing papers authored by Dong-Jun Koo
This map shows the geographic impact of Dong-Jun 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 Dong-Jun Koo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dong-Jun Koo more than expected).
Fields of papers citing papers by Dong-Jun Koo
This network shows the impact of papers produced by Dong-Jun 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 Dong-Jun Koo. The network helps show where Dong-Jun Koo may publish in the future.
Co-authors
The 25 scholars most cited alongside Dong-Jun Koo, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Microfluidic device with brain extracellular matrix promotes structural and functional maturation of human brain organoids Hit paper breakdown → | 2021 | 319 |
| 2 | 2020 | 58 | |
| 3 | 2022 | 44 | |
| 4 | 2021 | 29 | |
| 5 | 2020 | 14 | |
| 6 | Deep learning-based diagnosis of lung cancer using a nationwide respiratory cytology image set: improving accuracy and inter-observer variability. | 2023 | 12 |
| 7 | 2023 | 10 | |
| 8 | 2022 | 7 | |
| 9 | 2018 | 2 | |
| 10 | 2025 | 0 |
About Dong-Jun Koo
Dong-Jun Koo is a scholar working on Biomedical Engineering, Biomaterials, Molecular Biology, Biophysics and Endocrine and Autonomic Systems, having authored 10 papers that have together received 495 indexed citations. Recurring topics across this work include 3D Printing in Biomedical Research (4 papers), Nanoplatforms for cancer theranostics (2 papers), Nanoparticle-Based Drug Delivery (2 papers), Angiogenesis and VEGF in Cancer (2 papers), Advanced biosensing and bioanalysis techniques (1 paper), Cancer Research and Treatments (1 paper), Pluripotent Stem Cells Research (1 paper) and Cancer Cells and Metastasis (1 paper). The work is most often cited by research in Developmental Neuroscience (36 citations), Biomedical Engineering (291 citations), Health Informatics (8 citations), Cellular and Molecular Neuroscience (75 citations) and Oncology (85 citations). Dong-Jun Koo has collaborated with scholars based in South Korea, United States and Armenia. Frequent co-authors include Sung‐Yon Kim, Dal‐Hee Min, Seongchan Kim, Noo Li Jeon, Somin Lee, Hyojin Lee, James Yu, Joon Myong Song, Jihoon Ko and Tae‐Eun Park. Their work appears in journals such as Science Advances, Neuron, ACS Nano, Nature Communications and Acta Biomaterialia.
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.