Wanil Kim
Impact in
- Aging top 2%
- Genetics, Aging, and Longevity in Model Organisms
-
- Circadian rhythm and melatonin
Papers in
-
- Ubiquitin and proteasome pathways 7
- Nuclear Structure and Function 6
- Cell Biology 14
- Microtubule and mitosis dynamics 5
- Co-authors
- Kyong‐Tai Kim (31 shared papers)Kyung‐Ha Lee (22 shared papers)Do‐Yeon Kim (15 shared papers)Jerry W. Shay (3 shared papers)Tae‐Hong Kang (2 shared papers)Il‐Hong Bae (2 shared papers)Eun‐Gyung Cho (4 shared papers)Kyung‐Chul Woo (2 shared papers)
- Journals
- Scientific Reports (6 papers)Biochemical and Biophysical Research Communications (5 papers)International Journal of Molecular Sciences (4 papers)Animal Cells and Systems (3 papers)Journal of Biological Chemistry (3 papers)
- Partner nations
- South KoreaSingaporeUnited States
In The Last Decade
Wanil Kim
79 papers receiving 1.5k citations
Peers
Comparison fields: 5 of 134
- Aging 94
- Endocrine and Autonomic Systems 127
- Microbiology 96
- Molecular Biology 871
- Dermatology 97
Countries citing papers authored by Wanil Kim
This map shows the geographic impact of Wanil 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 Wanil Kim with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Wanil Kim more than expected).
Fields of papers citing papers by Wanil Kim
This network shows the impact of papers produced by Wanil 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 Wanil Kim. The network helps show where Wanil Kim may publish in the future.
Co-authors
The 25 scholars most cited alongside Wanil Kim, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 96 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 152 | |
| 2 | 2016 | 133 | |
| 3 | 2008 | 95 | |
| 4 | 2008 | 79 | |
| 5 | 2008 | 61 | |
| 6 | 2018 | 60 | |
| 7 | 2017 | 45 | |
| 8 | 2018 | 37 | |
| 9 | 2011 | 37 | |
| 10 | 2008 | 37 | |
| 11 | 2021 | 36 | |
| 12 | 2014 | 34 | |
| 13 | 2011 | 33 | |
| 14 | 2020 | 31 | |
| 15 | 2016 | 31 | |
| 16 | 2013 | 31 | |
| 17 | 2010 | 27 | |
| 18 | 2012 | 26 | |
| 19 | 2010 | 25 | |
| 20 | 2016 | 25 |
About Wanil Kim
Wanil Kim is a scholar working on Molecular Biology, Cell Biology, Social Psychology, Leadership and Management and Dermatology, having authored 96 papers that have together received 1.5k indexed citations. Recurring topics across this work include Healthcare Education and Workforce Issues (10 papers), Circadian rhythm and melatonin (8 papers), Ubiquitin and proteasome pathways (7 papers), Nuclear Structure and Function (6 papers), Psychosocial Factors Impacting Youth (5 papers), Dermatology and Skin Diseases (5 papers), Microtubule and mitosis dynamics (5 papers) and Job Satisfaction and Organizational Behavior (5 papers). The work is most often cited by research in Aging (94 citations), Endocrine and Autonomic Systems (127 citations), Microbiology (96 citations), Molecular Biology (871 citations) and Dermatology (97 citations). Wanil Kim has collaborated with scholars based in South Korea, Singapore and United States. Frequent co-authors include Kyong‐Tai Kim, Kyung‐Ha Lee, Do‐Yeon Kim, Jerry W. Shay, Tae‐Hong Kang, Il‐Hong Bae, Eun‐Gyung Cho, Kyung‐Chul Woo, Jaeyoung Ko and Ho Sup Yoon. Their work appears in journals such as Scientific Reports, Biochemical and Biophysical Research Communications, International Journal of Molecular Sciences, Animal Cells and Systems and Journal of Biological Chemistry.
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.