DeepWAS: Multivariate genotype-phenotype associations by directly integrating regulatory information using deep learning. - Janine Arloth; Gökcen Eraslan; Till F. M. Andlauer; Jade Martins; Stella Iurato; Brigitte Kühnel; Melanie Waldenberger; Josef Frank; Ralf Gold; Bernhard Hemmer; Felix Luessi; Sandra Nischwitz; et al. (PLoS Comput. Biol., 2020)

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)

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)