Tae Wan Kim
- Molecular Biology top 5%
- Cellular and Molecular Neuroscience top 5%
- Biomaterials top 2%
- Biomedical Engineering top 10%
- Plant Science top 10%
- Co-authors
- Sang Don KohKenton M. SandersEun‐Jung ChoHong‐Duk YounSi Jae ParkHyonchol JangSang Yup LeeNeil Aronin
- Topics
- CRISPR and Genetic Engineering (14 papers)Pluripotent Stem Cells Research (13 papers)Meat and Animal Product Quality (8 papers)
- Partner nations
- South KoreaUnited StatesAustria
In The Last Decade
Tae Wan Kim
118 papers receiving 3.3k citations
Peers
Comparison fields: 5 of 134
- Molecular Biology 2.2k
- Cellular and Molecular Neuroscience 623
- Biomaterials 496
- Biomedical Engineering 297
- Plant Science 278
Countries citing papers authored by Tae Wan Kim
This map shows the geographic impact of Tae Wan Kim'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 Tae Wan Kim with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tae Wan Kim more than expected).
Fields of papers citing papers by Tae Wan Kim
This network shows the impact of papers produced by Tae Wan Kim. 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 Tae Wan Kim. The network helps show where Tae Wan Kim may publish in the future.
Co-authorship network of co-authors of Tae Wan Kim
This figure shows the co-authorship network connecting the top 25 collaborators of Tae Wan Kim. A scholar is included among the top collaborators of Tae Wan Kim 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 Tae Wan Kim. Tae Wan Kim is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 1 | |
| 3 | 9 | |
| 4 | 0 | |
| 5 | 2 | |
| 6 | 1 | |
| 7 | 8 | |
| 8 | 3 | |
| 9 | 23 | |
| 10 | 1 | |
| 11 | 9 | |
| 12 | 37 | |
| 13 | 2 | |
| 14 | Proteomic evaluation of the response of soybean (Glycine max var Seoritae) leaves to UV-B | 2 |
| 15 | 79 | |
| 16 | Nondestructive and Rapid Estimation of Chlorophyll Content in Rye Leaf Using Digital Camera | 8 |
| 17 | Enhancement of protein solubility in a cell-free protein synthesis system by adding detergents | 0 |
| 18 | Surface Imaging of Barley Aleurone Cell by Atomic Force Microscopy | 1 |
| 19 | Organic photovoltaic effects depending on CuPc layer thickness | 3 |
| 20 | Tissue Engineering of Smooth Muscle under a Mechanically Dynamic Condition | 18 |
About Tae Wan Kim
Tae Wan Kim is a scholar working on Process Chemistry and Technology, Molecular Biology and Food Science, having authored 132 papers that have together received 3.4k indexed citations. Recurring topics across this work include CRISPR and Genetic Engineering (14 papers), Pluripotent Stem Cells Research (13 papers) and Meat and Animal Product Quality (8 papers). The work is most often cited by research in Gastroenterology (239 citations), Sensory Systems (194 citations) and Biomaterials (496 citations). Tae Wan Kim has collaborated with scholars based in South Korea, United States and Austria. Frequent co-authors include Sang Don Koh, Kenton M. Sanders, Eun‐Jung Cho, Hong‐Duk Youn, Si Jae Park, Hyonchol Jang, Sang Yup Lee, Neil Aronin, Manho Kim and Marian DiFiglia. Their work appears in journals such as Cell, Nucleic Acids Research and Nature Communications.
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.