Dongmin Bang

Contact

eugenomics@snu.ac.kr

International Papers

  • Kim Y, Bang D, Koo B, Yi J, Cho C, Choi J, Kim S. MixingDTA: Improved Drug-Target Affinity Prediction by Extending Mixup with Guilt-By-Association, Bioinformatics [Transferred from ISMB/ECCB2025] (Accepted)
  • Bang D, Kim J, Song H, Kim S. ADME-Drug-Likeness: Enriching Molecular Foundation Models via Pharmacokinetics-Guided Multi-Task Learning for Drug-likeness Prediction, Bioinformatics [Transferred from ISMB/ECCB2025] (Accepted)
  • Bang D, Sung I, Piao Y, Lee S, Kim S. Predicting Drug-likeness via Biomedical Knowledge Alignment and EM-like One-Class Boundary Optimization, 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)
  • 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.
  • Lee J, Bang D, Kim S. Residue-Level Multi-View Deep Learning for Accurate ATP Binding Site Prediction and Its Applications in Kinase Drug Binding. Journal of Chemical Informatics and Modeling (JCIM). 2024 Dec 17.
  • 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.
  • Pak M, Bang D, Sung I, Kim S, Lee S. DGDRP: Drug-specific Gene selection for Drug Response Prediction via re-ranking through propagating and learning biological network. Frontiers in Genetics. 2024 Sep 20
  • Bang D, Koo B, Kim S. Transfer Learning of Condition-Specific Perturbation in Gene Interactions Improves Drug Response Prediction. Bioinformatics, 2024 Jul. [From The 32nd Intelligent Systems for Molecular Biology (ISMB)]
  • Lee D, Lee D, Bang D, Kim S. DiSCO: Diffusion Schrödinger Bridge for Molecular Conformer Optimization. AAAI 2024. 2024
  • 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.
  • Shin J, Piao Y, Bang D, Kim S, Jo K. DRPreter: Interpretable Anticancer Drug Response Prediction Using Knowledge-Guided Graph Neural Networks and Transformer. International Journal of Molecular Sciences (IJMS). 2022 Nov 11.
  • Bang D, Gu J, Park J, Jeong D, Koo B, Yi J, Shin J, Jung I, Kim S, Lee S. A Survey on Computational Methods for Investigation on ncRNA-Disease Association through the Mode of Action Perspective. International Journal of Molecular Sciences (IJMS). 2022 Sep 29.
  • 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.