Yong-Jung Kim

1.3k total citations
56 papers, 927 citations indexed

About

Yong-Jung Kim is a scholar working on Modeling and Simulation, Public Health, Environmental and Occupational Health and Molecular Biology. According to data from OpenAlex, Yong-Jung Kim has authored 56 papers receiving a total of 927 indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Modeling and Simulation, 20 papers in Public Health, Environmental and Occupational Health and 14 papers in Molecular Biology. Recurrent topics in Yong-Jung Kim's work include Mathematical Biology Tumor Growth (23 papers), Mathematical and Theoretical Epidemiology and Ecology Models (20 papers) and Evolution and Genetic Dynamics (12 papers). Yong-Jung Kim is often cited by papers focused on Mathematical Biology Tumor Growth (23 papers), Mathematical and Theoretical Epidemiology and Ecology Models (20 papers) and Evolution and Genetic Dynamics (12 papers). Yong-Jung Kim collaborates with scholars based in South Korea, France and Japan. Yong-Jung Kim's co-authors include Changwook Yoon, Hai‐Yang Jin, Zhi‐An Wang, Chang‐Joong Lee, Eunjoo Cho, Uhn Lee, Oh‐Sang Kwon, Young M. Yoo, Laurent Desvillettes and Morinobu Endo and has published in prestigious journals such as Journal of The Electrochemical Society, Carbon and Brain Research.

In The Last Decade

Yong-Jung Kim

51 papers receiving 873 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yong-Jung Kim South Korea 16 472 297 277 225 187 56 927
David G. Míguez Spain 17 11 0.0× 52 0.2× 379 1.4× 77 0.3× 123 0.7× 41 775
Carlos Kwan‐Long Chau Hong Kong 6 89 0.2× 33 0.1× 272 1.0× 142 0.6× 42 0.2× 7 509
Neda Bagheri United States 22 15 0.0× 30 0.1× 697 2.5× 66 0.3× 24 0.1× 59 1.4k
Frank Morgan United States 11 27 0.1× 21 0.1× 862 3.1× 62 0.3× 189 1.0× 13 1.1k
Stefan Reinker Germany 8 27 0.1× 24 0.1× 377 1.4× 63 0.3× 148 0.8× 10 635
Marcin Leda United Kingdom 18 11 0.0× 18 0.1× 500 1.8× 35 0.2× 451 2.4× 35 976
Kate L. White United States 19 15 0.0× 23 0.1× 1.0k 3.6× 47 0.2× 121 0.6× 46 1.5k
Ernesto Andrianantoandro United States 3 6 0.0× 21 0.1× 905 3.3× 171 0.8× 456 2.4× 7 1.4k
Adriana T. Dawes United States 10 45 0.1× 12 0.0× 211 0.8× 14 0.1× 318 1.7× 31 514
Nan Hao United States 19 13 0.0× 8 0.0× 1.3k 4.7× 134 0.6× 155 0.8× 51 1.6k

Countries citing papers authored by Yong-Jung Kim

Since Specialization
Citations

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

Fields of papers citing papers by Yong-Jung Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yong-Jung 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 Yong-Jung Kim. The network helps show where Yong-Jung Kim may publish in the future.

Co-authorship network of co-authors of Yong-Jung Kim

This figure shows the co-authorship network connecting the top 25 collaborators of Yong-Jung Kim. A scholar is included among the top collaborators of Yong-Jung 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 Yong-Jung Kim. Yong-Jung 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.
Kim, Yong-Jung, et al.. (2024). Chemotactic cell aggregation viewed as instability and phase separation. Nonlinear Analysis Real World Applications. 80. 104147–104147. 1 indexed citations
2.
Hilhorst, Danielle, et al.. (2024). Fick’s law selects the Neumann boundary condition. Nonlinear Analysis. 245. 113561–113561. 4 indexed citations
3.
Kim, Yong-Jung, et al.. (2023). Modeling bacterial traveling wave patterns with exact cross-diffusion and population growth. Discrete and Continuous Dynamical Systems - B. 28(12). 6289–6305. 3 indexed citations
4.
Hilhorst, Dorothea, et al.. (2023). Hyperbolic limit for a biological invasion. Discrete and Continuous Dynamical Systems - B. 28(12). 6142–6158. 1 indexed citations
5.
Kim, Yong-Jung, Masayasu Mimura, & Changwook Yoon. (2023). Nonlinear Diffusion for Bacterial Traveling Wave Phenomenon. Bulletin of Mathematical Biology. 85(5). 35–35.
6.
Alfaro, Matthieu, et al.. (2022). On the modelling of spatially heterogeneous nonlocal diffusion: deciding factors and preferential position of individuals. Journal of Mathematical Biology. 84(5). 38–38. 8 indexed citations
7.
Wang, Hao, Kai Wang, & Yong-Jung Kim. (2022). Spatial Segregation in Reaction-Diffusion Epidemic Models. SIAM Journal on Applied Mathematics. 82(5). 1680–1709. 26 indexed citations
8.
Kim, Yong-Jung, et al.. (2018). Predator–prey equations with constant harvesting and planting. Journal of Theoretical Biology. 458. 47–57. 6 indexed citations
9.
Hilhorst, Danielle & Yong-Jung Kim. (2016). Diffusive and inviscid traveling waves of the Fisher equation and nonuniqueness of wave speed. Applied Mathematics Letters. 60. 28–35. 6 indexed citations
10.
Kim, Yong-Jung & Oh‐Sang Kwon. (2016). Evolution of Dispersal with Starvation Measure and Coexistence. Bulletin of Mathematical Biology. 78(2). 254–279. 17 indexed citations
11.
Yoon, Changwook & Yong-Jung Kim. (2016). Global Existence and Aggregation in a Keller–Segel Model with Fokker–Planck Diffusion. Acta Applicandae Mathematicae. 149(1). 101–123. 107 indexed citations
12.
Yoon, Changwook & Yong-Jung Kim. (2014). Bacterial chemotaxis without gradient-sensing. Journal of Mathematical Biology. 70(6). 1359–1380. 14 indexed citations
13.
Chung, Jaywan, Yong-Jung Kim, & Marshall Slemrod. (2014). An explicit solution of Burgers equation with stationary point source. Journal of Differential Equations. 257(7). 2520–2542. 5 indexed citations
14.
Kim, Yong-Jung, et al.. (2013). Global asymptotic stability and the ideal free distribution in a starvation driven diffusion. Journal of Mathematical Biology. 68(6). 1341–1370. 26 indexed citations
15.
Kim, Yong-Jung, Oh‐Sang Kwon, & Fang Li. (2013). Evolution of Dispersal Toward Fitness. Bulletin of Mathematical Biology. 75(12). 2474–2498. 23 indexed citations
16.
Cho, Eunjoo & Yong-Jung Kim. (2013). Starvation Driven Diffusion as a Survival Strategy of Biological Organisms. Bulletin of Mathematical Biology. 75(5). 845–870. 70 indexed citations
17.
Kim, Yong-Jung, Inyoung Jang, & Morinobu Endo. (2009). Carbon materials for supercapacitors. TANSO. 2009(236). 26–33. 4 indexed citations
18.
Lee, Chang‐Joong, et al.. (2006). Neuroprotection of adenoviral-vector-mediated GDNF expression against kainic-acid-induced excitotoxicity in the rat hippocampus. Experimental Neurology. 200(2). 407–417. 32 indexed citations
19.
Kim, Yong-Jung, et al.. (2005). Tamoxifen-induced cell death and expression of neurotrophic factors in cultured C6 glioma cells. Journal of Neuro-Oncology. 71(2). 121–125. 17 indexed citations
20.
Kim, Yong-Jung, et al.. (2003). Identification and functional evidence of GABAergic neurons in parts of the brain of adult zebrafish (Danio rerio). Neuroscience Letters. 355(1-2). 29–32. 64 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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