papers
Publications (3)
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.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…
q-bio.BM2023
Optimizing Drug Design by Merging Generative AI With Active Learning Frameworks
Isaac Filella-Merce, Alexis Molina, Marek Orzechowski +7
Traditional drug discovery programs are being transformed by the advent of machine learning methods. Among these, Generative AI methods (GM) have gained attention due to their abil…