Seung Woo Cho

14.3k total citations · 5 hit papers
25 papers, 7.0k citations indexed

About

Seung Woo Cho is a scholar working on Molecular Biology, Surgery and Cancer Research. According to data from OpenAlex, Seung Woo Cho has authored 25 papers receiving a total of 7.0k indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Molecular Biology, 3 papers in Surgery and 3 papers in Cancer Research. Recurrent topics in Seung Woo Cho's work include CRISPR and Genetic Engineering (13 papers), Advanced biosensing and bioanalysis techniques (4 papers) and Single-cell and spatial transcriptomics (3 papers). Seung Woo Cho is often cited by papers focused on CRISPR and Genetic Engineering (13 papers), Advanced biosensing and bioanalysis techniques (4 papers) and Single-cell and spatial transcriptomics (3 papers). Seung Woo Cho collaborates with scholars based in South Korea, United States and United Kingdom. Seung Woo Cho's co-authors include Jin‐Soo Kim, Sojung Kim, Jung‐Eun Kim, Jong Min Kim, Daesik Kim, Jiyeon Kweon, Yongsub Kim, Heon Seok Kim, Sangsu Bae and Howard Y. Chang and has published in prestigious journals such as Science, Cell and Nucleic Acids Research.

In The Last Decade

Seung Woo Cho

24 papers receiving 6.8k citations

Hit Papers

Targeted genome engineering in human cells with the Cas9 ... 2013 2026 2017 2021 2013 2014 2013 2015 2016 400 800 1.2k
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Targeted genome engineering in human cells with the Cas9 RNA-guided endonuclease
    2013 1.4k citations Seung Woo Cho, Sojung Kim et al. Nature Biotechnology profile →
  2. Highly efficient RNA-guided genome editing in human cells via delivery of purified Cas9 ribonucleoproteins
    2014 1.4k citations Sojung Kim, Daesik Kim et al. Genome Research profile →
  3. Analysis of off-target effects of CRISPR/Cas-derived RNA-guided endonucleases and nickases
    2013 1.1k citations Seung Woo Cho, Sojung Kim et al. Genome Research profile →
  4. DNA-free genome editing in plants with preassembled CRISPR-Cas9 ribonucleoproteins
    2015 852 citations Je Wook Woo, Jung‐Eun Kim et al. Nature Biotechnology profile →
  5. CRISPRi-based genome-scale identification of functional long noncoding RNA loci in human cells
    2016 530 citations Siyuan Liu, Max A. Horlbeck et al. Science profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Seung Woo Cho South Korea 16 6.5k 1.3k 1.2k 691 642 25 7.0k
Matthew H. Larson United States 14 8.2k 1.3× 2.0k 1.6× 658 0.5× 445 0.6× 525 0.8× 19 8.9k
Yanfang Fu United States 16 7.3k 1.1× 1.7k 1.4× 736 0.6× 338 0.5× 708 1.1× 19 8.1k
Alexandro E. Trevino United States 13 5.4k 0.8× 1.1k 0.9× 609 0.5× 338 0.5× 431 0.7× 30 6.0k
Scot A. Wolfe United States 48 7.2k 1.1× 1.5k 1.2× 768 0.6× 736 1.1× 306 0.5× 97 8.3k
Luhan Yang United States 6 7.3k 1.1× 1.7k 1.4× 804 0.7× 206 0.3× 556 0.9× 8 8.0k
Sangsu Bae South Korea 34 6.5k 1.0× 1.4k 1.1× 1.2k 1.0× 150 0.2× 664 1.0× 112 7.1k
Ophir Shalem United States 21 11.6k 1.8× 2.3k 1.8× 935 0.8× 745 1.1× 822 1.3× 42 13.1k
Gloria A. Brar United States 23 6.1k 0.9× 770 0.6× 634 0.5× 587 0.8× 207 0.3× 40 6.6k
Benjamin P. Kleinstiver United States 28 8.4k 1.3× 1.9k 1.5× 1.0k 0.8× 146 0.2× 1.0k 1.6× 66 8.7k
Aditya Raguram United States 19 6.6k 1.0× 1.9k 1.5× 1.2k 1.0× 120 0.2× 531 0.8× 23 7.2k

Countries citing papers authored by Seung Woo Cho

Since Specialization
Citations

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

Fields of papers citing papers by Seung Woo Cho

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Seung Woo Cho. 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 Seung Woo Cho. The network helps show where Seung Woo Cho may publish in the future.

Co-authorship network of co-authors of Seung Woo Cho

This figure shows the co-authorship network connecting the top 25 collaborators of Seung Woo Cho. A scholar is included among the top collaborators of Seung Woo Cho 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 Seung Woo Cho. Seung Woo Cho 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.
Jeong, Euihwan, et al.. (2025). Applications of multiplexed CRISPR–Cas for genome engineering. Experimental & Molecular Medicine. 57(7). 1373–1380. 2 indexed citations
2.
Yoon, Heejeong, Joo H. Kang, Seung Woo Cho, et al.. (2024). Brain‐Decellularized ECM‐Based 3D Myeloid Sarcoma Platform: Mimicking Adaptive Phenotypic Alterations in the Brain. Advanced Healthcare Materials. 13(13). e2304371–e2304371. 3 indexed citations
3.
Cho, Seung Woo, et al.. (2023). Intestinal Peyer’s Patches: Structure, Function, and In Vitro Modeling. Tissue Engineering and Regenerative Medicine. 20(3). 341–353. 30 indexed citations
4.
Oh, Jung‐Min, Yujin Kang, Jumi Park, et al.. (2023). MSH2-MSH3 promotes DNA end resection during homologous recombination and blocks polymerase theta-mediated end-joining through interaction with SMARCAD1 and EXO1. Nucleic Acids Research. 51(11). 5584–5602. 11 indexed citations
5.
Park, Inwon, Suhyun Kim, Seung Woo Cho, et al.. (2023). Extracorporeal Blood Treatment Using Functional Magnetic Nanoclusters Mitigates Organ Dysfunction of Sepsis in Swine. Small Methods. 8(5). e2301428–e2301428. 1 indexed citations
6.
Shin, Hyun Mu, Gwanghun Kim, Ji Hyun Sim, et al.. (2021). Chromatin accessibility of circulating CD8+ T cells predicts treatment response to PD-1 blockade in patients with gastric cancer. Nature Communications. 12(1). 975–975. 22 indexed citations
7.
Lee, HoJoon, Howard Y. Chang, Seung Woo Cho, & Hanlee P. Ji. (2020). CRISPRpic: fast and precise analysis for CRISPR-induced mutations via p refixed i ndex c ounting. NAR Genomics and Bioinformatics. 2(2). lqaa012–lqaa012. 12 indexed citations
8.
Kebschull, Justus M., Ethan B. Richman, Drew Friedmann, et al.. (2020). Cerebellar nuclei evolved by repeatedly duplicating a conserved cell-type set. Science. 370(6523). 129 indexed citations
9.
Cho, Seung Woo, et al.. (2018). The Effect of Prostaglandin E1 on the Resolution of Ecchymosis. 14(1). 44–48. 1 indexed citations
10.
Cho, Seung Woo, Jin Xu, Ruping Sun, et al.. (2018). Promoter of lncRNA Gene PVT1 Is a Tumor-Suppressor DNA Boundary Element. Cell. 173(6). 1398–1412.e22. 313 indexed citations
11.
Liu, Siyuan, Max A. Horlbeck, Seung Woo Cho, et al.. (2016). CRISPRi-based genome-scale identification of functional long noncoding RNA loci in human cells. Science. 355(6320). 530 indexed citations breakdown →
12.
Chen, Xingqi, Ying Shen, Jason D. Buenrostro, et al.. (2016). ATAC-see reveals the accessible genome by transposase-mediated imaging and sequencing. Nature Methods. 13(12). 1013–1020. 164 indexed citations
13.
Woo, Je Wook, Jung‐Eun Kim, Soon Il Kwon, et al.. (2015). DNA-free genome editing in plants with preassembled CRISPR-Cas9 ribonucleoproteins. Nature Biotechnology. 33(11). 1162–1164. 852 indexed citations breakdown →
14.
Hyun, Y., Jung‐Eun Kim, Seung Woo Cho, et al.. (2014). Site-directed mutagenesis in Arabidopsis thaliana using dividing tissue-targeted RGEN of the CRISPR/Cas system to generate heritable null alleles. Planta. 241(1). 271–284. 123 indexed citations
15.
Kim, Sojung, Daesik Kim, Seung Woo Cho, Jung‐Eun Kim, & Jin‐Soo Kim. (2014). Highly efficient RNA-guided genome editing in human cells via delivery of purified Cas9 ribonucleoproteins. Genome Research. 24(6). 1012–1019. 1357 indexed citations breakdown →
16.
Ramakrishna, Suresh, Seung Woo Cho, Sojung Kim, et al.. (2014). Surrogate reporter-based enrichment of cells containing RNA-guided Cas9 nuclease-induced mutations. Nature Communications. 5(1). 3378–3378. 100 indexed citations
17.
Cho, Seung Woo, Ji‐Hyun Lee, Ji‐Hyun Lee, et al.. (2013). Heritable Gene Knockout in Caenorhabditis elegans by Direct Injection of Cas9–sgRNA Ribonucleoproteins. Genetics. 195(3). 1177–1180. 204 indexed citations
18.
Cho, Seung Woo, Sojung Kim, Jong Min Kim, & Jin‐Soo Kim. (2013). Targeted genome engineering in human cells with the Cas9 RNA-guided endonuclease. Nature Biotechnology. 31(3). 230–232. 1445 indexed citations breakdown →
19.
Cho, Seung Woo, Sojung Kim, Yongsub Kim, et al.. (2013). Analysis of off-target effects of CRISPR/Cas-derived RNA-guided endonucleases and nickases. Genome Research. 24(1). 132–141. 1079 indexed citations breakdown →
20.
Kim, Seokjoong, Hyung Joo Lee, Hyojin Kim, Seung Woo Cho, & Jin‐Soo Kim. (2009). Targeted genome editing in human cells with zinc finger nucleases constructed via modular assembly. Genome Research. 19(7). 1279–1288. 348 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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