1. Iljung Jin, Songyeon Lee, Martin Schmuhalek, Hojung Nam*,

"DD-PRiSM: A Deep Learning Framework for Decomposition and Prediction of Synergistic Drug Combinations", 

Briefings in Bioinformatics, 2024 Nov 22;26(1):bbae717.

• Selected as RECOMB 2025 Highlights Track (acceptance rate of 18.9%).

• Media covered: 동아일보 and +20 daily newspapers, KBS, YTN Science news.

2. Hyunho Kim, Bongsung Bae, Minsu Park, Yewon Shin, Trey Ideker*, Hojung Nam*,

"A genotype-to-drug diffusion model for generation of tailored anti-cancer small molecules", 

Nature Communications, 2025 Jul 1;16(1):5628.

• 한빛사

• Media covered: 조선비즈 and +17 daily newspapers.

3. Daehun Bae†, Minsang Kim†, Jiwon Seo*, Hojung Nam*,
"AI-Guided Discovery and Optimization of Antimicrobial Peptides Through Species-Aware Language Model",
Briefings in Bioinformatics, 2025 Jul 2;26(4):bbaf343.

4. Juntae Park, Daehun Bae, Hojung Nam*,
"Reinforcement learning with LoRA for targeted antimicrobial peptide design",
Briefings in Bioinformatics, Under Revision.

5. Haelee Bae, Hojung Nam*,

"DeepRNA-DTI: A Deep Learning Approach for RNA-Compound Interaction Prediction with Binding Site Interpretability", 

Submitted.

6. Songyeon Lee, Hojung Nam*,
"KG-SLomics: Cancer Type-Specific Synthetic Lethality Prediction Using Knowledge Graph and Multiomics Integrated Graph Neural Network",

Under Revision.

7. Minsu Park, Yewon Shin, Hyunho Kim*, Hojung Nam*,
"Enhancing multi-task in vivo toxicity prediction via integrated knowledge transfer of chemical knowledge and in vitro toxicity information ",

Under Revision.