Junyeop Kim

1.5k total citations · 1 hit paper
38 papers, 957 citations indexed

About

Junyeop Kim is a scholar working on Molecular Biology, Information Systems and Education. According to data from OpenAlex, Junyeop Kim has authored 38 papers receiving a total of 957 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Molecular Biology, 6 papers in Information Systems and 6 papers in Education. Recurrent topics in Junyeop Kim's work include Education and Learning Interventions (5 papers), CRISPR and Genetic Engineering (5 papers) and Pluripotent Stem Cells Research (5 papers). Junyeop Kim is often cited by papers focused on Education and Learning Interventions (5 papers), CRISPR and Genetic Engineering (5 papers) and Pluripotent Stem Cells Research (5 papers). Junyeop Kim collaborates with scholars based in South Korea, United States and Denmark. Junyeop Kim's co-authors include Yu‐Jung Chang, Jongpil Kim, Hanseul Park, Hwan Geun Choi, Hongwon Kim, Christopher J. Lengner, Trista Bingham, Gregorio A. Millett, Darrell P. Wheeler and George Ayala and has published in prestigious journals such as ACS Nano, Nature Neuroscience and Biomaterials.

In The Last Decade

Junyeop Kim

34 papers receiving 933 citations

Hit Papers

Modeling G2019S-LRRK2 Sporadic Parkinson's Disease in 3D ... 2019 2026 2021 2023 2019 50 100 150 200 250

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Junyeop Kim South Korea 12 499 158 142 138 113 38 957
Denis Barry Ireland 16 219 0.4× 40 0.3× 155 1.1× 204 1.5× 66 0.6× 39 1.0k
Jennifer L. Collins United States 16 588 1.2× 44 0.3× 268 1.9× 21 0.2× 62 0.5× 40 1.4k
Aaron M. Miller United States 21 378 0.8× 77 0.5× 190 1.3× 58 0.4× 230 2.0× 45 1.4k
Mark L. Nelson United States 18 646 1.3× 28 0.2× 286 2.0× 63 0.5× 55 0.5× 32 1.7k
Eva Nordström Sweden 20 256 0.5× 88 0.6× 191 1.3× 28 0.2× 79 0.7× 30 1.3k
Stephen Soltys United States 14 1.6k 3.2× 116 0.7× 197 1.4× 50 0.4× 125 1.1× 28 2.3k
Carme Solé Spain 21 741 1.5× 15 0.1× 87 0.6× 21 0.2× 87 0.8× 52 1.2k
Esther Rincón Spain 13 417 0.8× 11 0.1× 61 0.4× 137 1.0× 29 0.3× 33 951
Samuel J. Beck United States 23 862 1.7× 20 0.1× 37 0.3× 49 0.4× 106 0.9× 101 1.8k
Susan Murray United States 21 236 0.5× 38 0.2× 78 0.5× 11 0.1× 171 1.5× 52 1.8k

Countries citing papers authored by Junyeop Kim

Since Specialization
Citations

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

Fields of papers citing papers by Junyeop Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Junyeop Kim

This figure shows the co-authorship network connecting the top 25 collaborators of Junyeop Kim. A scholar is included among the top collaborators of Junyeop 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 Junyeop Kim. Junyeop 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, Junyeop, et al.. (2025). Electromagnetized MXenes Enhance the Efficient Direct Reprogramming of Dopamine Neurons for Parkinson’s Disease Therapy. ACS Nano. 19(17). 16744–16759. 2 indexed citations
2.
Kim, Junyeop, Sumin Kim, Yu‐Jung Chang, et al.. (2023). Transcriptional activation of endogenous Oct4 via the CRISPR/dCas9 activator ameliorates Hutchinson‐Gilford progeria syndrome in mice. Aging Cell. 22(6). e13825–e13825. 11 indexed citations
3.
Kim, Hyunjin, YoonJung Cho, Junyeop Kim, & Minseong Kim. (2023). Exploring school life adaptation according to the type of latent group of social and emotional skills of Korean child and adolescents. Asian Journal of Education. 24(3). 557–585.
4.
Kim, Hongwon, Byounggook Cho, Hanseul Park, et al.. (2022). Dormant state of quiescent neural stem cells links Shank3 mutation to autism development. Molecular Psychiatry. 27(6). 2751–2765. 19 indexed citations
5.
Chang, Yu‐Jung, et al.. (2021). Electromagnetized Graphene Facilitates Direct Lineage Reprogramming into Dopaminergic Neurons. Advanced Functional Materials. 31(46). 13 indexed citations
6.
Chang, Yu‐Jung, Byounggook Cho, Euiyeon Lee, et al.. (2021). Electromagnetized gold nanoparticles improve neurogenesis and cognition in the aged brain. Biomaterials. 278. 121157–121157. 31 indexed citations
7.
Chang, Yu‐Jung, Junyeop Kim, Hanseul Park, Hwan Geun Choi, & Jongpil Kim. (2020). Modelling neurodegenerative diseases with 3D brain organoids. Biological reviews/Biological reviews of the Cambridge Philosophical Society. 95(5). 1497–1509. 46 indexed citations
8.
Choi, Hwan Geun, Soonbong Baek, Byounggook Cho, et al.. (2020). Epitranscriptomic N6-Methyladenosine Modification Is Required for Direct Lineage Reprogramming into Neurons. ACS Chemical Biology. 15(8). 2087–2097. 7 indexed citations
9.
Choi, Hwan Geun, et al.. (2019). Nac1 facilitates pluripotency gene activation for establishing somatic cell reprogramming. Biochemical and Biophysical Research Communications. 518(2). 253–258. 3 indexed citations
10.
Park, Hanseul, Jungju Oh, Gayong Shim, et al.. (2019). In vivo neuronal gene editing via CRISPR–Cas9 amphiphilic nanocomplexes alleviates deficits in mouse models of Alzheimer’s disease. Nature Neuroscience. 22(4). 524–528. 204 indexed citations
11.
Kim, Hongwon, Hwan Geun Choi, Yu‐Jung Chang, et al.. (2019). Modeling G2019S-LRRK2 Sporadic Parkinson's Disease in 3D Midbrain Organoids. Stem Cell Reports. 12(3). 518–531. 260 indexed citations breakdown →
12.
Chang, Yu‐Jung, Euiyeon Lee, Junyeop Kim, et al.. (2018). Efficient in vivo direct conversion of fibroblasts into cardiomyocytes using a nanoparticle-based gene carrier. Biomaterials. 192. 500–509. 68 indexed citations
13.
Kim, Junyeop, et al.. (2013). Exploring the trend in within-school achievement gap and its school-level covariates. 26(5). 959–980.
14.
Kim, Junyeop, et al.. (2013). Differential Patterns of Achievement Gap and Its Correlates among Different Types of High School. 26(3). 555–577. 1 indexed citations
15.
Song, Mi‐Young, et al.. (2011). Investigation on Contextual Variables Affecting Academic Achievement. 24(2). 261–290. 3 indexed citations
16.
Song, Mi‐Young, et al.. (2011). A Further Analysis of Achievement Gap among Districts based on 2009 NAEA (National Assessment of Educational Achievement) Results. 24(1). 51–72. 2 indexed citations
17.
Harawa, Nina T., Mei Leng, Junyeop Kim, & William E. Cunningham. (2011). Racial/Ethnic and Gender Differences Among Older Adults in Nonmonogamous Partnerships, Time Spent Single, and Human Immunodeficiency Virus Testing. Sexually Transmitted Diseases. 38(12). 1110–1117. 26 indexed citations
18.
Kim, Junyeop, et al.. (2009). A Longitudinal Analysis of Relationships among Parental Expectation, Involvement, and Children's Psychological Stress mediated by Learning Outcomes and Academic Self-Concept. The Korean Journal of Educational Psychology. 23(2). 389–412. 11 indexed citations
19.
Kim, Junyeop & Michael Seltzer. (2007). Causal Inference in Multilevel Settings in Which Selection Processes Vary across Schools. CSE Technical Report 708.. 9 indexed citations
20.
Choi, Kilchan & Junyeop Kim. (2006). Closing the Gap: Modeling Within-School Variance Heterogeneity in School Effect Studies. CSE Report 689.. 2 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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026