Dae‐Kyu Song
Impact in
- Equine top 2%
- Biological Psychiatry top 5%
Papers in
-
- Metabolism, Diabetes, and Cancer 12
- Surgery 25
- Pancreatic function and diabetes 20
- Co-authors
- Jae‐Hoon Bae (39 shared papers)Seung‐Soon Im (33 shared papers)Jae‐Hyung Park (21 shared papers)Seong‐Il Suh (18 shared papers)Byeong‐Churl Jang (20 shared papers)Won‐Ki Baek (16 shared papers)Frances M. Ashcroft (3 shared papers)Sang-Pyo Kim (9 shared papers)
- Journals
- Biochemical and Biophysical Research Communications (11 papers)Biochemical Pharmacology (6 papers)Pflügers Archiv - European Journal of Physiology (5 papers)Diabetes (4 papers)BMB Reports (4 papers)
- Partner nations
- South KoreaUnited StatesUnited Kingdom
In The Last Decade
Dae‐Kyu Song
111 papers receiving 2.7k citations
Peers
Comparison fields: 5 of 127
- Equine 49
- Biological Psychiatry 74
- Biochemistry 130
- Endocrinology, Diabetes and Metabolism 356
- Pathology and Forensic Medicine 377
Countries citing papers authored by Dae‐Kyu Song
This map shows the geographic impact of Dae‐Kyu Song'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 Dae‐Kyu Song with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dae‐Kyu Song more than expected).
Fields of papers citing papers by Dae‐Kyu Song
This network shows the impact of papers produced by Dae‐Kyu Song. 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 Dae‐Kyu Song. The network helps show where Dae‐Kyu Song may publish in the future.
Co-authors
The 25 scholars most cited alongside Dae‐Kyu Song, 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 113 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2005 | 126 | |
| 2 | 2014 | 97 | |
| 3 | 2008 | 74 | |
| 4 | 1998 | 69 | |
| 5 | 2009 | 69 | |
| 6 | 2021 | 65 | |
| 7 | 2001 | 63 | |
| 8 | 2018 | 59 | |
| 9 | 2019 | 58 | |
| 10 | 2004 | 57 | |
| 11 | 2020 | 54 | |
| 12 | 2000 | 53 | |
| 13 | 2004 | 52 | |
| 14 | 2015 | 52 | |
| 15 | 2002 | 52 | |
| 16 | 2014 | 52 | |
| 17 | 2016 | 46 | |
| 18 | 2007 | 44 | |
| 19 | 2002 | 43 | |
| 20 | 1998 | 42 |
About Dae‐Kyu Song
Dae‐Kyu Song is a scholar working on Molecular Biology, Surgery, Pathology and Forensic Medicine, Endocrinology, Diabetes and Metabolism and Cancer Research, having authored 113 papers that have together received 2.8k indexed citations. Recurring topics across this work include Pancreatic function and diabetes (20 papers), Metabolism, Diabetes, and Cancer (12 papers), Tea Polyphenols and Effects (12 papers), Cardiac Ischemia and Reperfusion (10 papers), Adipose Tissue and Metabolism (10 papers), Diabetes Treatment and Management (9 papers), Adipokines, Inflammation, and Metabolic Diseases (7 papers) and Cancer, Hypoxia, and Metabolism (7 papers). The work is most often cited by research in Equine (49 citations), Biological Psychiatry (74 citations), Biochemistry (130 citations), Endocrinology, Diabetes and Metabolism (356 citations) and Pathology and Forensic Medicine (377 citations). Dae‐Kyu Song has collaborated with scholars based in South Korea, United States and United Kingdom. Frequent co-authors include Jae‐Hoon Bae, Seung‐Soon Im, Jae‐Hyung Park, Seong‐Il Suh, Byeong‐Churl Jang, Won‐Ki Baek, Frances M. Ashcroft, Sang-Pyo Kim, Seung-Eun Song and Taeg Kyu Kwon. Their work appears in journals such as Biochemical and Biophysical Research Communications, Biochemical Pharmacology, Pflügers Archiv - European Journal of Physiology, Diabetes and BMB 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.