3 papers
cs.LG2026
Two-Stage Fine-Tuning for Protein Sequence Generation with Targeted Amino-Acid Composition
Violeta Basten-Romero, Rubén Muñoz-Tafalla, Anna MarÃa DÃaz-Rovira +3
Protein language models are standard priors for biological sequence generation, but steering them toward explicit distributional design targets remains largely unexplored. We study…
cs.LG2026
Tensor-DTI: Enhancing Biomolecular Interaction Prediction with Contrastive Embedding Learning
Manel Gil-Sorribes, Júlia Vilalta-Mor, Isaac Filella-Mercè +4
Accurate drug-target interaction (DTI) prediction is essential for computational drug discovery, yet existing models often rely on single-modality predefined molecular descriptors…
cs.LG2025
Active Learning-Guided Seq2Seq Variational Autoencoder for Multi-target Inhibitor Generation
Júlia Vilalta-Mor, Alexis Molina, Laura Ortega Varga +2
Simultaneously optimizing molecules against multiple therapeutic targets remains a profound challenge in drug discovery, particularly due to sparse rewards and conflicting design c…