9 citations · 9 across the 3 of their papers we have counts for
3 papers
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…
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…
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…