Hye-Won Kang

590 total citations
23 papers, 377 citations indexed

About

Hye-Won Kang is a scholar working on Molecular Biology, Condensed Matter Physics and Electronic, Optical and Magnetic Materials. According to data from OpenAlex, Hye-Won Kang has authored 23 papers receiving a total of 377 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Molecular Biology, 4 papers in Condensed Matter Physics and 3 papers in Electronic, Optical and Magnetic Materials. Recurrent topics in Hye-Won Kang's work include Gene Regulatory Network Analysis (8 papers), Bioinformatics and Genomic Networks (4 papers) and Microbial Metabolic Engineering and Bioproduction (4 papers). Hye-Won Kang is often cited by papers focused on Gene Regulatory Network Analysis (8 papers), Bioinformatics and Genomic Networks (4 papers) and Microbial Metabolic Engineering and Bioproduction (4 papers). Hye-Won Kang collaborates with scholars based in United States, South Korea and United Kingdom. Hye-Won Kang's co-authors include Thomas G. Kurtz, Alexei Bogdanov, Grzegorz A. Rempała, Melissa Crawford, Gerard J. Nuovo, Avner Friedman, Michela Garofalo, Muller Fabbri, S. Patrick Nana‐Sinkam and Ian T. Ferguson and has published in prestigious journals such as PLoS ONE, Scientific Reports and The FASEB Journal.

In The Last Decade

Hye-Won Kang

22 papers receiving 362 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Hye-Won Kang United States 13 205 55 40 38 38 23 377
Meiling Wu Taiwan 11 169 0.8× 99 1.8× 18 0.5× 112 2.9× 12 0.3× 25 424
Tamir Epstein United States 12 337 1.6× 107 1.9× 249 6.2× 11 0.3× 23 0.6× 21 704
Zhanghan Wu United States 11 180 0.9× 51 0.9× 7 0.2× 21 0.6× 10 0.3× 16 375
Yu‐Ru Liu China 12 306 1.5× 45 0.8× 24 0.6× 10 0.3× 18 0.5× 32 488
Ilan Tsafrir Israel 7 533 2.6× 67 1.2× 141 3.5× 21 0.6× 49 1.3× 7 776
Xin Lou China 16 532 2.6× 112 2.0× 139 3.5× 112 2.9× 7 0.2× 60 925
Christian Münkel Germany 13 505 2.5× 44 0.8× 51 1.3× 66 1.7× 13 0.3× 25 774
Arnaud Chauvière United States 13 151 0.7× 66 1.2× 46 1.1× 16 0.4× 11 0.3× 20 450
Kyle M. Douglass Switzerland 10 223 1.1× 121 2.2× 23 0.6× 10 0.3× 3 0.1× 17 504
Pooja Reddy United States 9 218 1.1× 52 0.9× 38 0.9× 35 0.9× 10 0.3× 19 622

Countries citing papers authored by Hye-Won Kang

Since Specialization
Citations

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

Fields of papers citing papers by Hye-Won Kang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hye-Won 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 Hye-Won Kang. The network helps show where Hye-Won Kang may publish in the future.

Co-authorship network of co-authors of Hye-Won Kang

This figure shows the co-authorship network connecting the top 25 collaborators of Hye-Won Kang. A scholar is included among the top collaborators of Hye-Won 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 Hye-Won Kang. Hye-Won 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.
2.
Kang, Hye-Won, et al.. (2024). Mechanistic insights into condensate formation of human liver-type phosphofructokinase by stochastic modeling approaches. Scientific Reports. 14(1). 19011–19011. 1 indexed citations
3.
Erban, Radek & Hye-Won Kang. (2023). Chemical Systems with Limit Cycles. Bulletin of Mathematical Biology. 85(8). 76–76. 5 indexed citations
4.
Lee, Ki Baek, et al.. (2020). Antioxidants reduce the heterogeneity of the intracellular glutathione level in senescent cell population of human dermal fibroblasts. Journal of Dermatological Science. 98(3). 195–198. 1 indexed citations
5.
Xu, Bin, Hye-Won Kang, & Alexandra Jilkine. (2019). Comparison of Deterministic and Stochastic Regime in a Model for Cdc42 Oscillations in Fission Yeast. Bulletin of Mathematical Biology. 81(5). 1268–1302. 6 indexed citations
6.
Kang, Hye-Won, Wasiur R. KhudaBukhsh, Heinz Koeppl, & Grzegorz A. Rempała. (2019). Quasi-Steady-State Approximations Derived from the Stochastic Model of Enzyme Kinetics. Bulletin of Mathematical Biology. 81(5). 1303–1336. 21 indexed citations
7.
Kang, Hye-Won & Radek Erban. (2019). Multiscale Stochastic Reaction–Diffusion Algorithms Combining Markov Chain Models with Stochastic Partial Differential Equations. Bulletin of Mathematical Biology. 81(8). 3185–3213. 5 indexed citations
8.
Jeong, Eui Man, Ji‐Woong Shin, Jisun Lim, et al.. (2019). Monitoring Glutathione Dynamics and Heterogeneity in Living Stem Cells. International Journal of Stem Cells. 12(2). 367–379. 14 indexed citations
9.
Kang, Hye-Won, et al.. (2018). A Mathematical Model for Enzyme Clustering in Glucose Metabolism. Scientific Reports. 8(1). 2696–2696. 15 indexed citations
10.
Kim, Jae Kyoung, Grzegorz A. Rempała, & Hye-Won Kang. (2017). Reduction for Stochastic Biochemical Reaction Networks with Multiscale Conservations. Multiscale Modeling and Simulation. 15(4). 1376–1403. 14 indexed citations
11.
Kang, Hye-Won, et al.. (2015). Robustness and period sensitivity analysis of minimal models for biochemical oscillators. Scientific Reports. 5(1). 13161–13161. 15 indexed citations
12.
Kang, Hye-Won, Melissa Crawford, Muller Fabbri, et al.. (2013). A Mathematical Model for MicroRNA in Lung Cancer. PLoS ONE. 8(1). e53663–e53663. 42 indexed citations
13.
Jung, Joohee, Sung Jin Park, Hye-Won Kang, et al.. (2012). Polymeric Nanoparticles Containing Taxanes Enhance Chemoradiotherapeutic Efficacy in Non-small Cell Lung Cancer. International Journal of Radiation Oncology*Biology*Physics. 84(1). e77–e83. 48 indexed citations
14.
Kang, Hye-Won. (2012). A multiscale approximation in a heat shock response model of E. coli. BMC Systems Biology. 6(1). 143–143. 11 indexed citations
15.
Bogdanov, Alexei, Charles P. Lin, & Hye-Won Kang. (2007). Optical Imaging of the Adoptive Transfer of Human Endothelial Cells in Mice Using Anti-Human CD31 Monoclonal Antibody. Pharmaceutical Research. 24(6). 1186–1192. 14 indexed citations
16.
Bogdanov, Alexei, et al.. (2007). Synthesis and Testing of a Binary Catalytic System for Imaging of Signal Amplification in Vivo. Bioconjugate Chemistry. 18(4). 1123–1130. 16 indexed citations
17.
Kang, Hye-Won, et al.. (2005). Effects of indium incorporation in AlGaN on threading dislocation density. Physica status solidi. C, Conferences and critical reviews/Physica status solidi. C, Current topics in solid state physics. 2(7). 2145–2148. 12 indexed citations
18.
Dietz, N., Mustafa Alevli, Vincent Woods, et al.. (2005). The characterization of InN growth under high‐pressure CVD conditions. physica status solidi (b). 242(15). 2985–2994. 21 indexed citations
19.
Kim, Hee Joo, Hyun-Ho Kwak, Kyung‐Seok Hu, et al.. (2003). Topographic anatomy of the mandibular nerve branches distributed on the two heads of the lateral pterygoid. International Journal of Oral and Maxillofacial Surgery. 32(4). 408–413. 23 indexed citations
20.
Kang, Hye-Won, Z. C. Feng, Ian T. Ferguson, Shiping Guo, & M. Pophristić. (2003). Reduction of Threading Dislocation Density in AlGaN by Indium Incorporation. MRS Proceedings. 798. 1 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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