André Lamúrias

scRepresenter provides a workflow to compute, integrate, and benchmark cellular representations from scRNA-seq data using different methods for complex disease analysis.

DGH-GO is an application that uses Gene Ontology to cluster disease-causing genes and identify genetic heterogeneity in complex diseases like ASD and NDDs.

This paper introduces GraphMB, a deep learning method for metagenomic binning that integrates assembly graph structures with contig features, improving the number of high-quality genome bins obtained.

This paper develops a machine learning classifier to automate biomarker curation in the Exposome-Explorer database, reducing manual screening by 90% with 70.1% F2-score.

BO-LSTM uses biomedical ontologies with LSTM networks to improve drug-drug interaction classification in text, achieving better performance with limited annotations.