Eun‐Bum Kang

1.1k total citations
24 papers, 935 citations indexed

About

Eun‐Bum Kang is a scholar working on Physiology, Epidemiology and Cellular and Molecular Neuroscience. According to data from OpenAlex, Eun‐Bum Kang has authored 24 papers receiving a total of 935 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Physiology, 8 papers in Epidemiology and 6 papers in Cellular and Molecular Neuroscience. Recurrent topics in Eun‐Bum Kang's work include Alzheimer's disease research and treatments (6 papers), Autophagy in Disease and Therapy (4 papers) and Tryptophan and brain disorders (4 papers). Eun‐Bum Kang is often cited by papers focused on Alzheimer's disease research and treatments (6 papers), Autophagy in Disease and Therapy (4 papers) and Tryptophan and brain disorders (4 papers). Eun‐Bum Kang collaborates with scholars based in South Korea, United States and Japan. Eun‐Bum Kang's co-authors include Jung‐Hoon Koo, Joon‐Yong Cho, Joon Yong Cho, Insu Kwon, Hyun-Tae Kim, Ludmila Cosío-Lima, Youngil Lee, Youngseok Lee, Joo‐Youn Cho and Chao Yang and has published in prestigious journals such as Brain Research, The FASEB Journal and Medicine & Science in Sports & Exercise.

In The Last Decade

Eun‐Bum Kang

23 papers receiving 921 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Eun‐Bum Kang South Korea 17 483 199 198 142 139 24 935
Jung‐Hoon Koo South Korea 15 424 0.9× 193 1.0× 211 1.1× 135 1.0× 121 0.9× 30 925
Joon‐Yong Cho South Korea 17 491 1.0× 241 1.2× 216 1.1× 178 1.3× 122 0.9× 64 1.1k
Talita Tuon Brazil 20 313 0.6× 187 0.9× 138 0.7× 78 0.5× 121 0.9× 38 1.1k
Susana Revilla Spain 7 439 0.9× 145 0.7× 182 0.9× 74 0.5× 144 1.0× 8 756
Mak Adam Daulatzai Australia 18 598 1.2× 281 1.4× 313 1.6× 67 0.5× 135 1.0× 22 1.2k
Edwina Abou Haidar United States 6 482 1.0× 272 1.4× 117 0.6× 70 0.5× 123 0.9× 8 1.0k
İlkay Aksu Türkiye 21 309 0.6× 165 0.8× 99 0.5× 95 0.7× 86 0.6× 44 1.1k
Lauretta El Hayek United States 6 530 1.1× 327 1.6× 127 0.6× 69 0.5× 161 1.2× 8 1.1k
Lisa S. Robison United States 23 388 0.8× 149 0.7× 268 1.4× 75 0.5× 110 0.8× 39 1.2k
Bo-Kyun Kim South Korea 15 245 0.5× 167 0.8× 180 0.9× 68 0.5× 65 0.5× 55 1.0k

Countries citing papers authored by Eun‐Bum Kang

Since Specialization
Citations

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

Fields of papers citing papers by Eun‐Bum Kang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Eun‐Bum Kang. 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 Eun‐Bum Kang. The network helps show where Eun‐Bum Kang may publish in the future.

Co-authorship network of co-authors of Eun‐Bum Kang

This figure shows the co-authorship network connecting the top 25 collaborators of Eun‐Bum Kang. A scholar is included among the top collaborators of Eun‐Bum Kang 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 Eun‐Bum Kang. Eun‐Bum Kang 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.
Kim, Jongkyu, et al.. (2024). Efficacy of natural eggshell membrane for knee osteoarthritis: A randomized, double-blind, placebo-controlled clinical trial. Journal of Functional Foods. 121. 106449–106449. 1 indexed citations
3.
Lim, Eun‐Jin, Eun‐Bum Kang, Eun-Su Jang, & Chang‐Gue Son. (2020). The Prospects of the Two-Day Cardiopulmonary Exercise Test (CPET) in ME/CFS Patients: A Meta-Analysis. Journal of Clinical Medicine. 9(12). 4040–4040. 30 indexed citations
4.
Koo, Jung‐Hoon, Eun‐Bum Kang, & Joon‐Yong Cho. (2019). Resistance Exercise Improves Mitochondrial Quality Control in a Rat Model of Sporadic Inclusion Body Myositis. Gerontology. 65(3). 240–252. 18 indexed citations
5.
Koo, Jung‐Hoon & Eun‐Bum Kang. (2019). Effects of treadmill exercise on the regulatory mechanisms of mitochondrial dynamics and oxidative stress in the brains of high-fat diet fed rats. Physical Activity and Nutrition. 23(1). 28–35. 17 indexed citations
7.
Koo, Jung‐Hoon, et al.. (2017). Effect of Resistance Exercise on Muscle Metabolism and Autophagy in sIBM. Medicine & Science in Sports & Exercise. 49(8). 1562–1571. 14 indexed citations
8.
Kang, Eun‐Bum, et al.. (2016). The effects of senior brain health exercise program on basic physical fitness, cognitive function and BDNF of elderly women - a feasibility study. Physical Activity and Nutrition. 20(2). 8–18. 27 indexed citations
9.
Koo, Jung‐Hoon, et al.. (2016). Treadmill exercise decreases amyloid-β burden possibly via activation of SIRT-1 signaling in a mouse model of Alzheimer's disease. Experimental Neurology. 288. 142–152. 122 indexed citations
10.
Kang, Eun‐Bum, Jung‐Hoon Koo, Chao Yang, et al.. (2016). Neuroprotective Effects of Endurance Exercise Against High‐Fat Diet‐Induced Hippocampal Neuroinflammation. Journal of Neuroendocrinology. 28(5). 79 indexed citations
11.
Kang, Eun‐Bum, et al.. (2015). Effect of treadmill exercise on PI3K/AKT/mTOR, autophagy, and Tau hyperphosphorylation in the cerebral cortex of NSE/htau23 transgenic mice. Physical Activity and Nutrition. 19(3). 199–209. 60 indexed citations
12.
Lee, Youngil, Eun‐Bum Kang, Insu Kwon, et al.. (2015). Cardiac Kinetophagy Coincides with Activation of Anabolic Signaling. Medicine & Science in Sports & Exercise. 48(2). 219–226. 19 indexed citations
13.
Kang, Eun‐Bum, et al.. (2014). The effect of 8 weeks sling exercise program on upper limb muscle strength CUE and SCIM III in spinal cord injury patients. The Korean Journal of Sport. 12(4). 415–426. 1 indexed citations
14.
Kang, Eun‐Bum, et al.. (2014). The effect of treadmill exercise on inflammatory responses in rat model of streptozotocin-induced experimental dementia of Alzheimer’s type. Physical Activity and Nutrition. 18(2). 225–233. 26 indexed citations
15.
Kang, Eun‐Bum & Joon Yong Cho. (2014). Effects of treadmill exercise on brain insulin signaling and β-amyloid in intracerebroventricular streptozotocin induced-memory impairment in rats. Physical Activity and Nutrition. 18(1). 89–96. 32 indexed citations
16.
Kang, Eun‐Bum, et al.. (2013). Effect of Periodical Complex Training Program on the Body Composition and Erogometer Record of National Canoe Athletes. The Korean Journal of Sport. 11(3). 75–84. 2 indexed citations
17.
Kang, Eun‐Bum, et al.. (2013). Neuroprotective effects of treadmill exercise on BDNF and PI3-K/Akt signaling pathway in the cortex of transgenic mice model of Alzheimer’s disease. Physical Activity and Nutrition. 17(4). 151–160. 54 indexed citations
18.
Kang, Eun‐Bum, Insu Kwon, Jung‐Hoon Koo, et al.. (2013). Treadmill exercise represses neuronal cell death and inflammation during Aβ-induced ER stress by regulating unfolded protein response in aged presenilin 2 mutant mice. APOPTOSIS. 18(11). 1332–1347. 101 indexed citations
19.
Kang, Eun‐Bum, et al.. (2010). Treadmill exercise represses neuronal cell death in an aged transgenic mouse model of Alzheimer's disease. Neuroscience Research. 69(2). 161–173. 175 indexed citations
20.
Kang, Eun‐Bum, et al.. (2008). The Effect of Exercise Training on Aβ-42, BDNF, GLUT-1 and HSP-70 Proteins in a NSE/ APPsw-transgenic Model for Alzheimer's Disease.. Journal of Life Science. 18(6). 796–803. 3 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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