Taeyoung Koo
- Molecular Biology top 5%
- Genetics top 2%
- Business and International Management top 1%
- Oncology
- Cardiology and Cardiovascular Medicine top 10%
- Co-authors
- Jin‐Soo KimDaesik KimKyoungmi KimJeong Hun KimJin Hyoung KimSung Wook ParkMatthew J. A. WoodEunji Kim
- Topics
- CRISPR and Genetic Engineering (21 papers)Virus-based gene therapy research (15 papers)Muscle Physiology and Disorders (10 papers)
- Partner nations
- South KoreaUnited KingdomFrance
In The Last Decade
Taeyoung Koo
33 papers receiving 2.5k citations
Hit Papers
Peers
Comparison fields: 5 of 80
- Molecular Biology 2.3k
- Genetics 785
- Business and International Management 199
- Oncology 161
- Cardiology and Cardiovascular Medicine 149
Countries citing papers authored by Taeyoung Koo
This map shows the geographic impact of Taeyoung 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 Taeyoung Koo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Taeyoung Koo more than expected).
Fields of papers citing papers by Taeyoung Koo
This network shows the impact of papers produced by Taeyoung 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 Taeyoung Koo. The network helps show where Taeyoung Koo may publish in the future.
Co-authorship network of co-authors of Taeyoung Koo
This figure shows the co-authorship network connecting the top 25 collaborators of Taeyoung Koo. A scholar is included among the top collaborators of Taeyoung Koo based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Taeyoung Koo. Taeyoung Koo is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 10 | |
| 3 | 10 | |
| 4 | 13 | |
| 5 | 9 | |
| 6 | 35 | |
| 7 | 180 | |
| 8 | 66 | |
| 9 | 45 | |
| 10 | Adenine base editing in mouse embryos and an adult mouse model of Duchenne muscular dystrophybreakdown → | 340 |
| 11 | 138 | |
| 12 | 96 | |
| 13 | In vivo genome editing with a small Cas9 orthologue derived from Campylobacter jejunibreakdown → | 531 |
| 14 | 164 | |
| 15 | 79 | |
| 16 | 50 | |
| 17 | 46 | |
| 18 | Expression, Purification and Osteogenic Bioactivity of Recombinant Human BMP-2 Derived by Escherichia Coli | 22 |
| 19 | 10 | |
| 20 | 48 |
About Taeyoung Koo
Taeyoung Koo is a scholar working on Business and International Management, Genetics and Aging, having authored 34 papers that have together received 2.5k indexed citations. Recurring topics across this work include CRISPR and Genetic Engineering (21 papers), Virus-based gene therapy research (15 papers) and Muscle Physiology and Disorders (10 papers). The work is most often cited by research in Business and International Management (199 citations), Aging (135 citations) and Molecular Biology (2.3k citations). Taeyoung Koo has collaborated with scholars based in South Korea, United Kingdom and France. Frequent co-authors include Jin‐Soo Kim, Daesik Kim, Kyoungmi Kim, Jeong Hun Kim, Jin Hyoung Kim, Sung Wook Park, Matthew J. A. Wood, Eunji Kim, Hee‐Yeon Cho and George Dickson. Their work appears in journals such as Nucleic Acids Research, Nature Communications and Nano Letters.
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.