André Patrício

On why and how to encode probability distributions on graph representations of omics data: enhancing predictive tasks and knowledge discovery

The paper introduces a graph-based framework that integrates statistical distributions into omics data to improve predictive performance and biological interpretability in cancer datasets.

Pattern-centric transformation of omics-data sources grounded on multi-wise gene associations aids predictive tasks in TCGA while ensuring interpretability.

The paper transforms omics data from gene-centric to pattern-centric to improve predictive performance and interpretability in TCGA data.