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ORCIDDongmin Bang
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2020 – today
- 2025
[j6]Youngoh Kim, Dongmin Bang, Bonil Koo
, Jungseob Yi, Changyun Cho, Jeonguk Choi, Sun Kim:
MixingDTA: improved drug-target affinity prediction by extending mixup with guilt-by-association. Bioinform. 41(Supplement_1): i105-i114 (2025)- [j5]Dongmin Bang, Juyeon Kim, Haerin Song, Sun Kim:
ADME-drug-likeness: enriching molecular foundation models via pharmacokinetics-guided multi-task learning for drug-likeness prediction. Bioinform. 41(Supplement_1): i352-i361 (2025) - [j4]Sumin Ha, Dongmin Bang, Sun Kim:
Fate-tox: fragment attention transformer for E(3)-equivariant multi-organ toxicity prediction. J. Cheminformatics 17(1): 74 (2025) - [j3]Jaechan Lee, Dongmin Bang, Sun Kim:
Residue-Level Multiview Deep Learning for ATP Binding Site Prediction and Applications in Kinase Inhibitors. J. Chem. Inf. Model. 65(1): 50-61 (2025) - [c2]Dongmin Bang, Inyoung Sung, Yinhua Piao, Sangseon Lee, Sun Kim:
BounDr.E: Predicting Drug-likeness via Biomedical Knowledge Alignment and EM-like One-Class Boundary Optimization. ICML 2025 - 2024
- [j2]Dongmin Bang, Bonil Koo, Sun Kim:
Transfer learning of condition-specific perturbation in gene interactions improves drug response prediction. Bioinform. 40(Supplement_1): i130-i139 (2024) - [c1]Danyeong Lee, Dohoon Lee, Dongmin Bang, Sun Kim:
DiSCO: Diffusion Schrödinger Bridge for Molecular Conformer Optimization. AAAI 2024: 13365-13373 - 2023
- [j1]Jeonghyeon Gu, Dongmin Bang, Jungseob Yi, Sangseon Lee, Dong Kyu Kim, Sun Kim:
A model-agnostic framework to enhance knowledge graph-based drug combination prediction with drug-drug interaction data and supervised contrastive learning. Briefings Bioinform. 24(5) (2023)
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