Javier Gómez Ortega

The paper introduces a temporal AI model, MaxToki, trained on extensive gene data to predict cell state changes across human aging and identifies age-modulating targets.

The paper develops a multi-task learning approach to create context-specific gene network representations, applying it to colorectal tumors to predict therapeutic targets.

The study updates exome matching to account for protein size and expression, finding that differential gene expression between sexes does not improve fecundity, suggesting conserved amino acid proportions across taxa.

The paper curates a database of senescence-associated genes and performs systems biology analyses to identify novel regulators and pathways of cellular senescence.