Sangseon Lee

576 total citations
40 papers, 363 citations indexed

About

Sangseon Lee is a scholar working on Molecular Biology, Computational Theory and Mathematics and Cancer Research. According to data from OpenAlex, Sangseon Lee has authored 40 papers receiving a total of 363 indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Molecular Biology, 12 papers in Computational Theory and Mathematics and 5 papers in Cancer Research. Recurrent topics in Sangseon Lee's work include Bioinformatics and Genomic Networks (16 papers), Gene expression and cancer classification (13 papers) and Computational Drug Discovery Methods (12 papers). Sangseon Lee is often cited by papers focused on Bioinformatics and Genomic Networks (16 papers), Gene expression and cancer classification (13 papers) and Computational Drug Discovery Methods (12 papers). Sangseon Lee collaborates with scholars based in South Korea, United States and Puerto Rico. Sangseon Lee's co-authors include Sun Kim, Sangsoo Lim, Taeheon Lee, Inuk Jung, Dong Won Kang, Heejoon Chae, Youngjun Park, Benjamin Hur, Jae Bum Kim and Sung-Min Rhee and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and Bioinformatics.

In The Last Decade

Sangseon Lee

35 papers receiving 358 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sangseon Lee South Korea 12 235 93 60 54 24 40 363
Ziqi Pan China 13 263 1.1× 111 1.2× 47 0.8× 48 0.9× 11 0.5× 28 502
Sangsoo Lim South Korea 13 334 1.4× 151 1.6× 38 0.6× 69 1.3× 20 0.8× 26 481
Zihan Guo China 12 283 1.2× 114 1.2× 132 2.2× 59 1.1× 10 0.4× 39 549
Chunyan Ao China 11 402 1.7× 50 0.5× 29 0.5× 72 1.3× 9 0.4× 24 519
Huaicheng Sun China 7 233 1.0× 82 0.9× 31 0.5× 93 1.7× 5 0.2× 10 366
Hasan Zulfiqar China 15 677 2.9× 98 1.1× 53 0.9× 93 1.7× 19 0.8× 27 815
Katharine Bisordi United States 6 387 1.6× 60 0.6× 85 1.4× 70 1.3× 76 3.2× 9 532
J. J. Patten United States 7 246 1.0× 175 1.9× 30 0.5× 20 0.4× 15 0.6× 15 509
Takeshi Hase Japan 10 289 1.2× 94 1.0× 25 0.4× 16 0.3× 19 0.8× 23 452
Antoine Bodein Canada 6 310 1.3× 26 0.3× 37 0.6× 64 1.2× 45 1.9× 14 481

Countries citing papers authored by Sangseon Lee

Since Specialization
Citations

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

Fields of papers citing papers by Sangseon Lee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sangseon Lee

This figure shows the co-authorship network connecting the top 25 collaborators of Sangseon Lee. A scholar is included among the top collaborators of Sangseon Lee 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 Sangseon Lee. Sangseon Lee 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
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Lee, Sangseon, et al.. (2025). MDTR: a knowledge-guided interpretable representation for quantifying liver toxicity at transcriptomic level. Frontiers in Pharmacology. 15. 1398370–1398370. 1 indexed citations
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Lee, Sangseon, et al.. (2024). Improving Out-of-Distribution Generalization in Graphs via Hierarchical Semantic Environments. 27621–27630. 3 indexed citations
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Lee, Sangseon, et al.. (2023). Exploring chemical space for lead identification by propagating on chemical similarity network. Computational and Structural Biotechnology Journal. 21. 4187–4195. 4 indexed citations
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Lee, Sangseon, et al.. (2023). Improved drug response prediction by drug target data integration via network-based profiling. Briefings in Bioinformatics. 24(2). 11 indexed citations
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Lee, Sangseon, et al.. (2022). Sparse Structure Learning via Graph Neural Networks for Inductive Document Classification. Proceedings of the AAAI Conference on Artificial Intelligence. 36(10). 11165–11173. 25 indexed citations
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Lee, Sangseon, et al.. (2021). Developed an In-Line System of Measuring MTF for Automating the Assembly Process of Lens-Module in a Smartphone Camera. Journal of the Korean Society for Precision Engineering. 38(5). 359–363. 1 indexed citations
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Lee, Sangseon, et al.. (2021). Subnetwork representation learning for discovering network biomarkers in predicting lymph node metastasis in early oral cancer. Scientific Reports. 11(1). 23992–23992. 2 indexed citations
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Lee, Taeheon, Sangseon Lee, Minji Kang, & Sun Kim. (2021). Deep hierarchical embedding for simultaneous modeling of GPCR proteins in a unified metric space. Scientific Reports. 11(1). 9543–9543. 2 indexed citations
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Kang, Minji, et al.. (2020). Learning Cell-Type-Specific Gene Regulation Mechanisms by Multi-Attention Based Deep Learning With Regulatory Latent Space. Frontiers in Genetics. 11. 869–869. 10 indexed citations
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Lee, Sangseon, Sangsoo Lim, Dabin Jeong, et al.. (2020). DRIM: A Web-Based System for Investigating Drug Response at the Molecular Level by Condition-Specific Multi-Omics Data Integration. Frontiers in Genetics. 11. 564792–564792. 13 indexed citations
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Lee, Sangseon, et al.. (2019). SpliceHetero: An information theoretic approach for measuring spliceomic intratumor heterogeneity from bulk tumor RNA-seq. PLoS ONE. 14(10). e0223520–e0223520. 7 indexed citations
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Hur, Benjamin, et al.. (2019). Venn-diaNet : venn diagram based network propagation analysis framework for comparing multiple biological experiments. BMC Bioinformatics. 20(S23). 667–667. 26 indexed citations
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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

Breakdown of academic impact, for papers by Ziqi Pan Breakdown of academic impact, for papers by Sangsoo Lim Breakdown of academic impact, for papers by Zihan Guo Breakdown of academic impact, for papers by Chunyan Ao Breakdown of academic impact, for papers by Huaicheng Sun Breakdown of academic impact, for papers by Hasan Zulfiqar Breakdown of academic impact, for papers by Katharine Bisordi Breakdown of academic impact, for papers by J. J. Patten Breakdown of academic impact, for papers by Takeshi Hase Breakdown of academic impact, for papers by Antoine Bodein
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