Da Sol Kim

2.0k total citations
55 papers, 1.6k citations indexed

About

Da Sol Kim is a scholar working on Physiology, Endocrinology, Diabetes and Metabolism and Molecular Biology. According to data from OpenAlex, Da Sol Kim has authored 55 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Physiology, 15 papers in Endocrinology, Diabetes and Metabolism and 12 papers in Molecular Biology. Recurrent topics in Da Sol Kim's work include Regulation of Appetite and Obesity (9 papers), Phytoestrogen effects and research (8 papers) and Adipose Tissue and Metabolism (8 papers). Da Sol Kim is often cited by papers focused on Regulation of Appetite and Obesity (9 papers), Phytoestrogen effects and research (8 papers) and Adipose Tissue and Metabolism (8 papers). Da Sol Kim collaborates with scholars based in South Korea, United States and Canada. Da Sol Kim's co-authors include Sunmin Park, Suna Kang, James W. Daily, Dae Young Kwon, Hye Jeong Yang, Na Rang Moon, Ji Man Hong, Hyun‐Jin Kim, Il Sung Ahn and Byoung‐Seob Ko and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Brain Research and International Journal of Molecular Sciences.

In The Last Decade

Da Sol Kim

55 papers receiving 1.5k citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Da Sol Kim 500 427 297 205 171 55 1.6k
Antonella Amato 507 1.0× 519 1.2× 389 1.3× 159 0.8× 71 0.4× 65 1.8k
Kiran S. Panickar 807 1.6× 428 1.0× 273 0.9× 267 1.3× 131 0.8× 72 2.6k
Neda Roshanravan 827 1.7× 485 1.1× 258 0.9× 217 1.1× 84 0.5× 87 1.9k
Kai‐Chun Cheng 685 1.4× 464 1.1× 370 1.2× 227 1.1× 69 0.4× 82 1.9k
Hui Fan 613 1.2× 368 0.9× 266 0.9× 215 1.0× 115 0.7× 64 1.6k
Hala F. Zaki 552 1.1× 313 0.7× 221 0.7× 123 0.6× 145 0.8× 101 1.9k
Xia Zhu 509 1.0× 339 0.8× 162 0.5× 175 0.9× 92 0.5× 72 1.8k
Eun Kyeong Lee 1.1k 2.3× 519 1.2× 181 0.6× 366 1.8× 118 0.7× 78 2.8k
Wiramon Rungratanawanich 420 0.8× 301 0.7× 133 0.4× 186 0.9× 142 0.8× 25 1.2k
Thiago Duarte 417 0.8× 281 0.7× 148 0.5× 146 0.7× 61 0.4× 80 1.9k

Countries citing papers authored by Da Sol Kim

Since Specialization
Citations

This map shows the geographic impact of Da Sol 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 Da Sol Kim with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Da Sol Kim more than expected).

Fields of papers citing papers by Da Sol Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Da Sol 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 Da Sol Kim. The network helps show where Da Sol Kim may publish in the future.

Co-authorship network of co-authors of Da Sol Kim

This figure shows the co-authorship network connecting the top 25 collaborators of Da Sol Kim. A scholar is included among the top collaborators of Da Sol 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 Da Sol Kim. Da Sol Kim is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Park, Soo Young, et al.. (2025). Genome-scale knockout simulation and clustering analysis of drug-resistant breast cancer cells reveal drug sensitization targets. Proceedings of the National Academy of Sciences. 122(26). e2425384122–e2425384122. 2 indexed citations
2.
Park, Sunmin, Da Sol Kim, & Suna Kang. (2024). Gene-diet interactions in carbonated sugar-sweetened beverage consumption and metabolic syndrome risk: A machine learning analysis in a large hospital-based cohort. Clinical Nutrition ESPEN. 64. 358–369. 3 indexed citations
3.
Kim, Da Sol, et al.. (2022). Convergence Modeling and Reproduction of a Bigyeokjincheolloe (Bomb Shell) Based on Three-dimensional Scanning and <i>γ</i>-ray Radiography. Journal of Conservation Science. 38(1). 55–63. 4 indexed citations
4.
Hong, Ji Man, et al.. (2021). Hemorrhagic Transformation After Ischemic Stroke: Mechanisms and Management. Frontiers in Neurology. 12. 703258–703258. 91 indexed citations
5.
Park, Sunmin, et al.. (2019). Folate and vitamin B-12 deficiencies additively impaire memory function and disturb the gut microbiota in amyloid-β infused rats. International Journal for Vitamin and Nutrition Research. 92(3-4). 169–181. 23 indexed citations
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Park, Sunmin, Da Sol Kim, & Suna Kang. (2018). Carrying minor allele of FADS1 and haplotype of FADS1 and FADS2 increased the risk of metabolic syndrome and moderate but not low fat diets lowered the risk in two Korean cohorts. European Journal of Nutrition. 58(2). 831–842. 29 indexed citations
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Kang, Suna, Na Rang Moon, Da Sol Kim, Sung Hoon Kim, & Sunmin Park. (2015). Central acylated ghrelin improves memory function and hippocampal AMPK activation and partly reverses the impairment of energy and glucose metabolism in rats infused with β-amyloid. Peptides. 71. 84–93. 33 indexed citations
10.
Daily, James W., Xin Zhang, Da Sol Kim, & Sunmin Park. (2015). Efficacy of Ginger for Alleviating the Symptoms of Primary Dysmenorrhea: A Systematic Review and Meta-analysis of Randomized Clinical Trials. Pain Medicine. 16(12). 2243–2255. 74 indexed citations
11.
Park, Sunmin, Da Sol Kim, & Suna Kang. (2015). Vitamin D deficiency impairs glucose-stimulated insulin secretion and increases insulin resistance by reducing PPAR-γ expression in nonobese Type 2 diabetic rats. The Journal of Nutritional Biochemistry. 27. 257–265. 71 indexed citations
12.
Yang, Hye Jeong, Dae Young Kwon, Hye Won Lee, et al.. (2015). Asian Elm tree inner bark prevents articular cartilage deterioration in ovariectomized obese rats with monoiodoacetate-induced osteoarthritis. Menopause The Journal of The North American Menopause Society. 23(2). 197–208. 11 indexed citations
13.
Kim, Da Sol, et al.. (2015). A Case Report of Mass-Forming Aspergillus Tracheobronchitis Successfully Treated with Voriconazole. Medicine. 94(34). e1434–e1434. 5 indexed citations
14.
Yang, Hye Jeong, Dae Young Kwon, Hyun‐Jin Kim, et al.. (2014). Fermenting soybeans with Bacillus licheniformis potentiates their capacity to improve cognitive function and glucose homeostaisis in diabetic rats with experimental Alzheimer’s type dementia. European Journal of Nutrition. 54(1). 77–88. 42 indexed citations
15.
Park, Sunmin, Da Sol Kim, Suna Kang, & Na Rang Moon. (2013). β-Amyloid-induced cognitive dysfunction impairs glucose homeostasis by increasing insulin resistance and decreasing β-cell mass in non-diabetic and diabetic rats. Metabolism. 62(12). 1749–1760. 36 indexed citations
16.
Park, Sunmin, et al.. (2013). Exercise training attenuates cerebral ischemic hyperglycemia by improving hepatic insulin signaling and β-cell survival. Life Sciences. 93(4). 153–160. 16 indexed citations
17.
Yang, Hye Jeong, Dae Young Kwon, Min Jung Kim, et al.. (2012). Jerusalem artichoke and chungkookjang additively improve insulin secretion and sensitivity in diabetic rats. Nutrition & Metabolism. 9(1). 112–112. 20 indexed citations
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Park, Sunmin, et al.. (2011). Glyceollin-containing fermented soybeans improve glucose homeostasis in diabetic mice. Nutrition. 28(2). 204–211. 29 indexed citations

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.

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