3 papers
quant-ph2026
A quantum generative model for in silico clinical trials using scarce training datasets
Olatz Sanz Larrarte, Reza Dastbasteh, Roberto Sanchez-Navarro +7
In silico methods have emerged as a strategy to complement clinical trials. These are particularly relevant for rare or heterogeneous diseases for which traditional methods are cos…
cs.LG2023
Towards a more inductive world for drug repurposing approaches
Jesus de la Fuente, Guillermo Serrano, Uxía Veleiro +8
Drug-target interaction (DTI) prediction is a challenging, albeit essential task in drug repurposing. Learning on graph models have drawn special attention as they can significantl…
q-bio.GN2023
Sweetwater: An interpretable and adaptive autoencoder for efficient tissue deconvolution
Jesus de la Fuente, Naroa Legarra, Guillermo Serrano +8
Single-cell RNA-sequencing (scRNA-seq) stands as a powerful tool for deciphering cellular heterogeneity and exploring gene expression profiles at high resolution. However, its high…