Testing for association between RNA-Seq and high-dimensional data. - Armin Rauschenberger; Marianne A. Jonker; Mark A. van de Wiel; Renée X. de Menezes (BMC Bioinform., 2016)

Sparse classification with paired covariates. - Armin Rauschenberger; Iuliana Ciocanea-Teodorescu; Marianne A. Jonker; Renée X. de Menezes; Mark A. van de Wiel (Adv. Data Anal. Classif., 2020)

Predictive and interpretable models via the stacked elastic net. - Armin Rauschenberger; Enrico Glaab; Mark A. van de Wiel (Bioinform., 2021)

Predicting correlated outcomes from molecular data. - Armin Rauschenberger; Enrico Glaab (Bioinform., 2021)

Fast Cross-validation for Multi-penalty High-dimensional Ridge Regression. - Mark A. van de Wiel; Mirrelijn M. van Nee; Armin Rauschenberger (J. Comput. Graph. Stat., 2021)

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)

Penalized regression with multiple sources of prior effects. - Armin Rauschenberger; Zied Landoulsi; Mark A. van de Wiel; Enrico Glaab (Bioinform., 2023)

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)