Sangseon Lee

Contact

sangseon486@snu.ac.kr

International Papers

  • Lu Y, Piao Y, Lee S, Kim S. Context-Aware Hierarchical Fusion for Drug Relational Learning. IEEE Transactions on Computational Biology and Bioinformatics. 2025 Mar 14
  • Bang D, Sung I, Piao Y, Lee S, Kim S. Predicting Drug-likeness via Biomedical Knowledge Alignment and EM-like One-Class Boundary Optimization, ICML2025 (Accepted)
  • Kim H, Humanyun S, Kim Tae, Park S, Lee S, Lee S, Kim S, Kang CG, Kim SW, Kim D. Enhancement of bioactive compounds, antioxidant capacity, and inhibitory effects on mushroom tyrosinase, α-glucosidase, and nitric oxide production in sorghum (Sorghum bicolor L.) via solid-state fermentation with Monascus purpureus. Food Science and Biotechnology. 2025 Jan.
  • Kim Y, Piao Y, Lee S, Kim S. Aligning Molecules and Fragments in a Shared Embedding Space for RL-Based Molecule Generation, ICLR2025 MLGenX workshop (Accepted)
  • Sung I, Bang D, Kim S, Lee S. Transferring Preclinical Drug Response to Patient via Tumor Heterogeneity-Aware Alignment and Perturbation Modeling, ICLR2025 MLGenX workshop (Accepted)
  • Lim H, Kim S, Lee S. CheapNet: Cross-attention on Hierarchical representations for Efficient protein-ligand binding Affinity Prediction. ICLR2025 (Accepted).
  • Sung I, Lee SS, Bang D, Yi J, Kim S, Lee SH. MDTR: A Knowledge-Guided Interpretable Representation for Quantifying Liver Toxicity at Transcriptomic Level. Frontiers in Pharmacology. Frontiers in Pharmacology. 2025 Jan 24.
  • Cho C, Lee S, Bang D, Piao Y, Kim S. ChemAP: predicting drug approval with chemical structures before clinical trial phase by leveraging multi-modal embedding space and knowledge distillation. Scientific Reports. 2024 Oct 3.
  • Lu Y, Piao Y, Lee S, Kim S. Context-Aware Hierarchical Fusion for Drug Relational Learning. 23rd International Workshop on Data Mining in Bioinformatics (BIOKDD). 2024 Aug 26
  • Lu Y, Lee S, Kang S, Kim S. Mixture-of-Experts Approach for Enhanced Drug-Target Interaction Prediction and Confidence Assessment. 23rd International Workshop on Data Mining in Bioinformatics (BIOKDD). 2024 Aug 26
  • Lee S, Park J, Piao Y, Lee D, Lee D, Kim S. Multi-layered Knowledge Graph Neural Network Reveals Pathway-level Agreement of Three Breast Cancer Multi-gene Assays. Computational and Structural Biotechnology Journal. 2024 Apr 22.
  • Piao Y, Lee S, Lu Y, Kim S. Improving Out-of-Distribution Generalization in Graphs via Hierarchical Semantic Environments. CVPR 2024. 2024 Mar
  • Park S, Lee S, Pak M, Kim S. Dual Representation Learning for Predicting Drug-side Effect Frequency using Protein Target Information. IEEE Journal of Biomedical and Health Informatics. 2024 Jan 5.
  • Yi J, Lee S, Lim S, Cho C, Piao Y, Yeo M, Kim D, Kim S, Lee S. Exploring chemical space for lead identification by propagating on chemical similarity network. Computational and Structural Biotechnology Journal. 2023 Aug 25.
  • Gu J, Bang D, Yi J, Lee S, Kim DK, Kim S. A model-agnostic framework to enhance knowledge graph-based drug combination prediction with drug–drug interaction data and supervised contrastive learning. Briefings in Bioinformatics. 2023 Aug 7.
  • Bang D, Lim S, Lee S, Kim S. Biomedical knowledge graph learning for drug repurposing by extending guilt-by-association to multiple layers. Nature Communications. 2023 June 15.
  • Pak M, Lee S, Sung I, Koo B, Kim S. Improved drug response prediction by drug target data integration via network-based profiling. Briefings in Bioinformatics. 2023 Feb 8.
  • Lee S, Lee D, Piao Y, Kim S. SPGP: Structure Prototype Guided Graph Pooling. NeurIPS 2022 New Frontiers in Graph Learning Workshop (NeurIPS GLFrontiers 2022), 2022 Dec 2.
  • Koo B, Lee D, Lee S, Sung I, Kim S, Lee S. Risk Stratification for Breast Cancer Patient by Simultaneous Learning of Molecular Subtype and Survival Outcome Using Genetic Algorithm-Based Gene Set Selection. Cancers. [From The 10th International Conference on Intelligent Biology and Medicine (ICIBM 2022)]. 2022 Aug 25.
  • Lim S, Lee S, Piao Y, Choi MG, Bang D, Gu J, Kim S. On Modeling and Utilizing Chemical Compound Information with Deep Learning Technologies: A Task-oriented Approach. Computational and Structural Biotechnology Journal (CSBJ). 2022 Aug 4.
  • Sung I, Lee S, Pak M, Shin Y, Kim S. AutoCoV: tracking the early spread of COVID-19 in terms of the spatial and temporal patterns from embedding space by K-mer based deep learning. BMC Bioinformatics. 2022 Apr 25.
  • Pak M, Lee S, Sung I, Shin Y, Jung I, Kim S. COVID-19 Virus Whole-genome Embedding Strategy through Density-based Clustering and Deep Learning Model. JOK. 2022 Apr.
  • Piao Y, Lee S, Lee D, Kim S. Sparse Structure Learning via Graph Neural Networks for Inductive Document Classification. AAAI 2022. 2022 Feb 22.
  • Kim J, Lim S, Lee S, Cho C, Kim S. Embedding of FDA Approved Drugs in Chemical Space Using Cascade Autoencoder with Metric Learning. IEEE BigComp 2022. AI-BioHealth 2022 workshop. 2022 Jan 17.
  • Kim M, Lee S, Lim S, Lee DY, Kim S. Subnetwork Representation Learning for Discovering Network Biomarkers in Predicting Lymph Node Metastasis in Early Oral Cancer. Scientific Reports 11 (23992), 1-12. 2021 Dec 14.
  • Lee T, Lee S, Kang M, Kim S. Deep hierarchical embedding for simultaneous modeling of GPCR proteins in a unified metric space. Scientific Reports 11 (1) 1-11. 2021 May 05.
  • Jeong D, Lim S, Lee S, Oh M, Cho C, Seong H, Jung W, Kim S. Construction of Condition-Specific Gene Regulatory Network using Kernel Canonical Correlation Analysis. Frontiers in Genetics. 2021 Mar 26.
  • Moon JH, Lee S, Pak M, Hur B, Kim S. MLDEG: A Machine Learning Approach to Identify Differentially Expressed Genes Using Network Property and Network Propagation. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 2021 Mar 22.
  • Park YJ, Lee S, Lim S, Hahn N, Ji Y, Huh JY, Alfadda AA, Kim S, Kim JB. DNMT1 maintains metabolic fitness of adipocytes through acting as an epigenetic safeguard of mitochondrial dynamics. Proceedings of the National Academy of Sciences (PNAS). 2021 Mar 16.
  • Kim I, Lee S, Kim Y, Namkoong H, Kim S. A Probabilistic Model for Pathway-guided Gene Set Selection. IEEE BIBM 2021. 12th International Workshop on Biomedical and Health Informatics (BHI 2021). Accepted.
  • Pak M, Jeong D, Moon JH, Ann H, Hur B, Lee S, Kim S. Network Propagation for the Analysis of Multi-Omics Data. Recent Advances in Biological Network Analysis (pp. 185-217). 2021
  • Oh M, Park S, Lee S, Lee D, Lim S, Jeong D, Jo K, Jung I, Kim S. DRIM: A web-based system for investigating drug response at the molecular level by condition-specific multi-omics data integration. Frontiers in Genetics. 2020 Nov 12.
  • Kang M, Lee S, Lee D, Kim S. Learning Cell-Type-Specific Gene Regulation Mechanisms by Multi-Attention Based Deep Learning with Regulatory Latent Space. Frontiers in Genetics, 2020 Sep 30.
  • Lee S, Lim S, Lee T, Sung I, Kim S. Cancer subtype classification and modeling by pathway attention and propagation. Bioinformatics, 2020 Mar 24.
  • Hur B, Kang D, Lee S, Moon JH, Lee G, Kim S. Venn-diaNet: Venn diagram based network propagation analysis framework for computing multiple biological experiments. BMC Bioinformatics, 2019 Dec 27. [From The 30th International Conference on Genome Informatics (GIW)]
  • Kang D, Ahn H, Lee S, Lee CJ, Hur J, Jung W, Kim S. StressGenePred: a twin prediction model architecture for classifying the stress types of samples and discovering stress-related genes in Arabidopsis. BMC Genomics, 2019 Dec 20.
  • Kim M, Lee S, Lim S, Kim S. SpliceHetero: An information theoretic approach for measuring spliceomic intratumor heterogeneity from bulk tumor RNA-seq. PloS ONE. 2019 Oct 23.
  • Lee S, Lee T, Noh YK, Kim S. Ranked k-spectrum kernel for comparative and evolutionary comparison of exons, introns, and CpG islands. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2019 Sep 3.
  • Lee D, Lee S, Kim S. PRISM: Methylation Pattern-based, Reference-free Inference of Subclonal Makeup. Bioinformatics, 2019 Jul 5. [From The 27th Intelligent Systems for Molecular Biology (ISMB)]
  • Moon JH, Lim S, Jo K, Lee S, Seo S, Kim S, PINTnet: construction of condition-specic pathway interaction network by computing shortest paths on weighted PPI. BMC Systems Biology. 2017 Mar 14.

Conference Papers

  • Kang D, Ahn H, Lee S, Lee CJ, Hur J, Jung W, Kim S. Identifying stress-related genes and predicting stress types in Arabidopsis using logical correlation layer and CMCL loss through time-series data. The 2018 International Conference on Bioinformatics and Biomedicine (BIBM). 2018 Dec 4. [Invited to BMC Genomics]
  • Lee S, Moon JH, Park Y, Kim S, Flow maximization analysis of cell cycle pathway activation status in breast cancer subtypes, 2017 IEEE International Conference on Big Data and Smart Computing (BigComp 2017)