The split-up algorithm: a fast symbolic method for computing p-values of distribution-free statistics. - Mark A. van de Wiel (Comput. Stat., 2001)

CGHMultiArray: exact P-values for multi-array comparative genomic hybridization data. - Mark A. van de Wiel; Serge J. Smeets; Ruud H. Brakenhoff; Bauke Ylstra (Bioinform., 2005)

A Note on Sample Size Determination for a Nonparametric Test of Location. - Subhabrata Chakraborti; B. Hong; Mark A. van de Wiel (Technometrics, 2006)

CGHcall: calling aberrations for array CGH tumor profiles. - Mark A. van de Wiel; Kyung In Kim; Sjoerd J. Vosse; Wessel N. van Wieringen; Saskia M. Wilting; Bauke Ylstra (Bioinform., 2007)

Some Comments on False Discovery Rate. - Avner Bar-Hen; Kyung In Kim; Mark A. van de Wiel (J. Bioinform. Comput. Biol., 2007)

Effects of dependence in high-dimensional multiple testing problems. - Kyung In Kim; Mark A. van de Wiel (BMC Bioinform., 2008)

Smoothing waves in array CGH tumor profiles. - Mark A. van de Wiel; Rebecca Brosens; Paul H. C. Eilers; Candy Kumps; Gerrit Meijer; Björn Menten; Erik Sistermans; Frank Speleman; Marieke E. Timmerman; Bauke Ylstra (Bioinform., 2009)

CGHpower: exploring sample size calculations for chromosomal copy number experiments. - Ilari Scheinin; Jose A. Ferreira; Sakari Knuutila; Gerrit Meijer; Mark A. van de Wiel; Bauke Ylstra (BMC Bioinform., 2010)

Preprocessing and downstream analysis of microarray DNA copy number profiles. - Mark A. van de Wiel; Franck Picard; Wessel N. van Wieringen; Bauke Ylstra (Briefings Bioinform., 2011)

Stepwise classification of cancer samples using clinical and molecular Data. - Askar Obulkasim; Gerrit Meijer; Mark A. van de Wiel (BMC Bioinform., 2011)

Exploratory Factor Analysis of Pathway Copy Number Data with an Application Towards the Integration with Gene Expression Data. - Wessel N. van Wieringen; Mark A. van de Wiel (J. Comput. Biol., 2011)

Matching of array CGH and gene expression microarray features for the purpose of integrative genomic analyses. - Wessel N. van Wieringen; Kristian Unger; Gwenaël G. R. Leday; Oscar Krijgsman; Renée X. de Menezes; Bauke Ylstra; Mark A. van de Wiel (BMC Bioinform., 2012)

PLRS: a flexible tool for the joint analysis of DNA copy number and mRNA expression data. - Gwenaël G. R. Leday; Mark A. van de Wiel (Bioinform., 2013)

tigaR: integrative significance analysis of temporal differential gene expression induced by genomic abnormalities. - Viktorian Miok; Saskia M. Wilting; Mark A. van de Wiel; Annelieke Jaspers; Paula I. van Noort; Ruud H. Brakenhoff; Peter J. F. Snijders; Renske D. M. Steenbergen; Wessel N. van Wieringen (BMC Bioinform., 2014)

ShrinkBayes: a versatile R-package for analysis of count-based sequencing data in complex study designs. - Mark A. van de Wiel; Maarten Neerincx; Tineke E. Buffart; Daoud Sie; Henk M. W. Verheul (BMC Bioinform., 2014)

Semi-supervised adaptive-height snipping of the hierarchical clustering tree. - Askar Obulkasim; Gerrit A. Meijer; Mark A. van de Wiel (BMC Bioinform., 2015)

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)

GeneBreak: detection of recurrent DNA copy number aberration-associated chromosomal breakpoints within genes. - Evert van den Broek; Stef van Lieshout; Christian Rausch; Bauke Ylstra; Mark A. van de Wiel; Gerrit A. Meijer; Remond J. A. Fijneman; Sanne Abeln (F1000Research, 2016)

Better diagnostic signatures from RNAseq data through use of auxiliary co-data. - Putri W. Novianti; Barbara C. Snoek; Saskia M. Wilting; Mark A. van de Wiel (Bioinform., 2017)

Improved high-dimensional prediction with Random Forests by the use of co-data. - Dennis E. te Beest; Steven W. Mes; Saskia M. Wilting; Ruud H. Brakenhoff; Mark A. van de Wiel (BMC Bioinform., 2017)

PRECISE: a domain adaptation approach to transfer predictors of drug response from pre-clinical models to tumors. - Soufiane Mourragui; Marco Loog; Mark A. van de Wiel; Marcel J. T. Reinders; Lodewyk F. A. Wessels (Bioinform., 2019)

Stable prediction with radiomics data. - Carel F. W. Peeters; Caroline Übelhör; Steven W. Mes; Roland Martens; Thomas Koopman; Pim de Graaf; Floris H. P. van Velden; Ronald Boellaard; Jonas A. Castelijns; Dennis E. te Beest; Martijn W. Heymans; Mark A. van de Wiel (CoRR, 2019)

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)

The spectral condition number plot for regularization parameter evaluation. - Carel F. W. Peeters; Mark A. van de Wiel; Wessel N. van Wieringen (Comput. Stat., 2020)

Updating of the Gaussian graphical model through targeted penalized estimation. - Wessel N. van Wieringen; Koen A. Stam; Carel F. W. Peeters; Mark A. van de Wiel (J. Multivar. Anal., 2020)

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

Estimation of variance components, heritability and the ridge penalty in high-dimensional generalized linear models. - Jurre R. Veerman; Gwenaël G. R. Leday; Mark A. van de Wiel (Commun. Stat. Simul. Comput., 2022)

Percolate: An Exponential Family JIVE Model to Design DNA-Based Predictors of Drug Response. - Soufiane Mourragui; Marco Loog; Mirrelijn M. van Nee; Mark A. van de Wiel; Marcel J. T. Reinders; Lodewyk F. A. Wessels (RECOMB, 2023)

Co-data Learning for Bayesian Additive Regression Trees. - Jeroen M. Goedhart; Thomas Klausch; Jurriaan Janssen; Mark A. van de Wiel (CoRR, 2023)

Fast Marginal Likelihood Estimation of Penalties for Group-Adaptive Elastic Net. - Mirrelijn M. van Nee; Tim van de Brug; Mark A. van de Wiel (J. Comput. Graph. Stat., 2023)

Estimation of predictive performance in high-dimensional data settings using learning curves. - Jeroen M. Goedhart; Thomas Klausch; Mark A. van de Wiel (Comput. Stat. Data Anal., 2023)

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

ecpc: an R-package for generic co-data models for high-dimensional prediction. - Mirrelijn M. van Nee; Lodewyk F. A. Wessels; Mark A. van de Wiel (BMC Bioinform., 2023)

Refining CART Models for Covariate Shift with Importance Weight. - Mingyang Cai; Thomas Klausch; Mark A. van de Wiel (CoRR, 2024)

Hypothesis-free discovery from epidemiological data by automatic detection and local inference for tree-based nonlinearities and interactions. - Giorgio Spadaccini; Marjolein Fokkema; Mark A. van de Wiel (CoRR, 2025)