Sangsu Bae

10.8k total citations · 4 hit papers
112 papers, 7.1k citations indexed

About

Sangsu Bae is a scholar working on Molecular Biology, Plant Science and Genetics. According to data from OpenAlex, Sangsu Bae has authored 112 papers receiving a total of 7.1k indexed citations (citations by other indexed papers that have themselves been cited), including 104 papers in Molecular Biology, 18 papers in Plant Science and 17 papers in Genetics. Recurrent topics in Sangsu Bae's work include CRISPR and Genetic Engineering (82 papers), Advanced biosensing and bioanalysis techniques (22 papers) and RNA and protein synthesis mechanisms (18 papers). Sangsu Bae is often cited by papers focused on CRISPR and Genetic Engineering (82 papers), Advanced biosensing and bioanalysis techniques (22 papers) and RNA and protein synthesis mechanisms (18 papers). Sangsu Bae collaborates with scholars based in South Korea, United States and Ethiopia. Sangsu Bae's co-authors include Jin‐Soo Kim, Jeongbin Park, Heon Seok Kim, Seung Woo Cho, Jiyeon Kweon, Sojung Kim, Yongsub Kim, Jihyeon Yu, Gue‐Ho Hwang and Kayeong Lim and has published in prestigious journals such as Cell, Proceedings of the National Academy of Sciences and Journal of the American Chemical Society.

In The Last Decade

Sangsu Bae

106 papers receiving 7.0k citations

Hit Papers

Cas-OFFinder: a fast and versatile algorithm that searche... 2013 2026 2017 2021 2014 2013 2015 2015 500 1000 1.5k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sangsu Bae South Korea 34 6.5k 1.4k 1.2k 664 430 112 7.1k
Matthew H. Larson United States 14 8.2k 1.3× 2.0k 1.4× 658 0.5× 525 0.8× 515 1.2× 19 8.9k
Hiroshi Nishimasu Japan 42 9.4k 1.5× 1.4k 1.0× 1.3k 1.1× 882 1.3× 573 1.3× 89 10.4k
Alexis C. Komor United States 18 9.1k 1.4× 2.5k 1.8× 1.3k 1.1× 860 1.3× 535 1.2× 41 9.9k
Michael S. Packer United States 14 8.4k 1.3× 2.3k 1.7× 1.3k 1.0× 748 1.1× 453 1.1× 18 9.0k
Luke W. Koblan United States 15 7.5k 1.2× 2.3k 1.7× 1.1k 0.9× 626 0.9× 428 1.0× 19 8.0k
Andrew V. Anzalone United States 15 6.1k 0.9× 1.7k 1.2× 1.2k 1.0× 515 0.8× 352 0.8× 19 6.8k
Aditya Raguram United States 19 6.6k 1.0× 1.9k 1.4× 1.2k 1.0× 531 0.8× 332 0.8× 23 7.2k
Alexander A. Sousa United States 11 5.1k 0.8× 1.4k 1.0× 763 0.6× 568 0.9× 375 0.9× 13 5.4k
Benjamin P. Kleinstiver United States 28 8.4k 1.3× 1.9k 1.4× 1.0k 0.8× 1.0k 1.6× 663 1.5× 66 8.7k

Countries citing papers authored by Sangsu Bae

Since Specialization
Citations

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

Fields of papers citing papers by Sangsu Bae

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sangsu Bae

This figure shows the co-authorship network connecting the top 25 collaborators of Sangsu Bae. A scholar is included among the top collaborators of Sangsu Bae 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 Sangsu Bae. Sangsu Bae 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
3.
Bae, Sangsu, et al.. (2024). Current status of genome editing technologies: special issue of BMB Reports in 2024. BMB Reports. 57(1). 1–1. 3 indexed citations
4.
Hwang, Gue‐Ho, et al.. (2024). Genome-wide in-locus epitope tagging of Arabidopsis proteins using prime editors. BMB Reports. 57(1). 66–70. 3 indexed citations
5.
Lee, Hee Jung, Young Suk Yu, Chang Rok Kim, et al.. (2024). Prion-like domain mediated phase separation of ARID1A promotes oncogenic potential of Ewing’s sarcoma. Nature Communications. 15(1). 6569–6569. 13 indexed citations
6.
Kim, Yun-Jeong, et al.. (2024). Enhancing genome editing in hPSCs through dual inhibition of DNA damage response and repair pathways. Nature Communications. 15(1). 4002–4002. 5 indexed citations
7.
Uddin, Nizam, Seungmo Kim, Yi Zhao, et al.. (2024). Tumor-intrinsic role of ICAM-1 in driving metastatic progression of triple-negative breast cancer through direct interaction with EGFR. Molecular Cancer. 23(1). 230–230. 14 indexed citations
8.
Kim, Heon Seok, Susan M. Grimes, Tianqi Chen, et al.. (2023). Direct measurement of engineered cancer mutations and their transcriptional phenotypes in single cells. Nature Biotechnology. 42(8). 1254–1262. 15 indexed citations
9.
Kang, In Man, Hyo-Jin Kim, Young-Ho Lee, et al.. (2023). Engineering second-generation TCR-T cells by site-specific integration of TRAF-binding motifs into the CD247 locus. Journal for ImmunoTherapy of Cancer. 11(4). e005519–e005519. 7 indexed citations
10.
Kim, Nan-Sun, Jihyeon Yu, Sangsu Bae, et al.. (2022). Identification and Characterization of PSEUDO-RESPONSE REGULATOR (PRR) 1a and 1b Genes by CRISPR/Cas9-Targeted Mutagenesis in Chinese Cabbage (Brassica rapa L.). International Journal of Molecular Sciences. 23(13). 6963–6963. 5 indexed citations
11.
Habib, Omer, et al.. (2021). Comprehensive analysis of prime editing outcomes in human embryonic stem cells. Nucleic Acids Research. 50(2). 1187–1197. 63 indexed citations
12.
Lee, Kyounghee, Ok‐Sun Park, Jihyeon Yu, et al.. (2021). Arabidopsis ATXR2 represses de novo shoot organogenesis in the transition from callus to shoot formation. Cell Reports. 37(6). 109980–109980. 33 indexed citations
13.
Byeon, Eunjin, Min‐Sub Kim, Duck‐Hyun Kim, et al.. (2021). The freshwater water flea Daphnia magna NIES strain genome as a resource for CRISPR/Cas9 gene targeting: The glutathione S-transferase omega 2 gene. Aquatic Toxicology. 242. 106021–106021. 24 indexed citations
14.
Hwang, Gue‐Ho, You Kyeong Jeong, Omer Habib, et al.. (2021). PE-Designer and PE-Analyzer: web-based design and analysis tools for CRISPR prime editing. Nucleic Acids Research. 49(W1). W499–W504. 84 indexed citations
15.
Jeong, Chang-Bum, Hye-Min Kang, Sung-Ah Hong, et al.. (2020). Generation of albino via SLC45a2 gene targeting by CRISPR/Cas9 in the marine medaka Oryzias melastigma. Marine Pollution Bulletin. 154. 111038–111038. 12 indexed citations
16.
Hwang, Gue‐Ho & Sangsu Bae. (2020). Web-Based Base Editing Toolkits: BE-Designer and BE-Analyzer. Methods in molecular biology. 2189. 81–88. 13 indexed citations
17.
Jeong, You Kyeong, Beomjong Song, & Sangsu Bae. (2020). Current Status and Challenges of DNA Base Editing Tools. Molecular Therapy. 28(9). 1938–1952. 93 indexed citations
18.
Kim, Heon Seok, Kyungjin Lee, Sangsu Bae, et al.. (2017). CRISPR/Cas9-mediated gene knockout screens and target identification via whole-genome sequencing uncover host genes required for picornavirus infection. Journal of Biological Chemistry. 292(25). 10664–10671. 33 indexed citations
19.
Lee, Seung Hwan & Sangsu Bae. (2016). Structural and dynamic views of the CRISPR-Cas system at the single-molecule level. BMB Reports. 49(4). 201–207. 6 indexed citations
20.
Bae, Sangsu, et al.. (2013). Z-DNA stabilization is dominated by the Hofmeister effect. Physical Chemistry Chemical Physics. 15(38). 15829–15829. 14 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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