Ten quick tips for biomarker discovery and validation analyses using machine learning. - Ramón Díaz-Uriarte; Elisa Gómez de Lope; Rosalba Giugno; Holger Fröhlich; Petr V. Nazarov; Isabel A. Nepomuceno-Chamorro; Armin Rauschenberger; Enrico Glaab (PLoS Comput. Biol., 2022)

Graph Representation Learning Strategies for Omics Data: A Case Study on Parkinson's Disease. - Elisa Gómez de Lope; Saurabh Deshpande; Ramón Viñas Torné 001; Pietro Liò; Enrico Glaab; Stéphane P. A. Bordas (CoRR, 2024)

Integrating digital gait data with metabolomics and clinical data to predict outcomes in Parkinson's disease. - Cyril Brzenczek; Quentin Klopfenstein; Tom Hähnel; Holger Fröhlich; Enrico Glaab; Geeta Acharya; Gloria Aguayo; Myriam Alexandre; Muhammad Ali; Wim Ammerlann; Giuseppe Arena; Michele Bassis; et al. (npj Digit. Medicine, 2024)

Interpreting Omics Data in Parkinson's Disease: A Statistical, Machine Learning, and Graph Representation Learning Approach. - Elisa Gómez de Lope (2024)

Multi-cohort machine learning identifies predictors of cognitive impairment in Parkinson's disease. - Rebecca Ting Jiin Loo; Lukas Pavelka; Graziella Mangone; Fouad Khoury; Marie Vidailhet; Jean-Christophe Corvol; Enrico Glaab; Geeta Acharya; Gloria Aguayo; Myriam Alexandre; Muhammad Ali; Wim Ammerlann; et al. (npj Digit. Medicine, 2025)