A Comparison of two Methods for Finding Groups using Heat Maps and Model Based Clustering. - Fabrice Colas; Ingrid Meulenbelt; Jeanine J. Houwing-Duistermaat; P. Eline Slagboom; Joost N. Kok (SGAI Conf. (Applications), 2007)

A Scenario Implementation in Rfor SubtypeDiscoveryExamplified on Chemoinformatics Data. - Fabrice Colas; Ingrid Meulenbelt; Jeanine J. Houwing-Duistermaat; Margreet Kloppenburg; Iain Watt; Stephanie M. van Rooden; Martine Visser; Johan Marinus; Edward O. Cannon; Andreas Bender 002; Jacobus J. van Hilten; P. Eline Slagboom; et al. (ISoLA, 2008)

Integrating Protein-Protein Interaction Networks with Gene-Gene Co-Expression Networks improves Gene Signatures for Classifying Breast Cancer Metastasis. - Erik van den Akker 001; Bas Verbruggen; Bas T. Heijmans; Marian Beekman; Joost N. Kok; Pieternella E. Slagboom; Marcel J. T. Reinders (J. Integr. Bioinform., 2011)

PASSion: a pattern growth algorithm-based pipeline for splice junction detection in paired-end RNA-Seq data. - Yanju Zhang; Eric-Wubbo Lameijer; Peter A. C. 't Hoen; Zemin Ning; P. Eline Slagboom; Kai Ye 001 (Bioinform., 2012)

MethylAid: visual and interactive quality control of large Illumina 450k datasets. - Maarten van Iterson; Elmar W. Tobi; Roderick C. Slieker; Wouter den Hollander; René Luijk; P. Eline Slagboom; Bastiaan T. Heijmans (Bioinform., 2014)

An alternative approach to multiple testing for methylation QTL mapping reduces the proportion of falsely identified CpGs. - René Luijk; Jelle J. Goeman; P. Eline Slagboom; Bastiaan T. Heijmans; Erik W. van Zwet (Bioinform., 2015)

Detecting dispersed duplications in high-throughput sequencing data using a database-free approach. - M. Kroon; Eric-Wubbo Lameijer; N. Lakenberg; Jayne Y. Hehir-Kwa; D. T. Thung; P. Eline Slagboom; Joost N. Kok; Kai Ye 001 (Bioinform., 2016)

RNNs on Monitoring Physical Activity Energy Expenditure in Older People. - Stylianos Paraschiakos; Cláudio Rebelo de Sá; Jeremiah Okai; P. Eline Slagboom; Marian Beekman; Arno J. Knobbe (CoRR, 2020)

Activity recognition using wearable sensors for tracking the elderly. - Stylianos Paraschiakos; Ricardo Cachucho; Matthijs Moed; Diana van Heemst; Simon Mooijaart; P. Eline Slagboom; Arno J. Knobbe; Marian Beekman (User Model. User Adapt. Interact., 2020)

GOTOV Human Physical Activity and Energy Expenditure Dataset on Older Individuals. - Stylianos Paraschiakos; Marian Beekman; Arno J. Knobbe; Ricardo Cachucho; P. Eline Slagboom (4TU.Federation, 2021)

MiMIR: R-shiny application to infer risk factors and endpoints from Nightingale Health's 1H-NMR metabolomics data. - Daniele Bizzarri; Marcel J. T. Reinders; Marian Beekman; P. Eline Slagboom; Erik van den Akker 001 (Bioinform., 2022)

A recurrent neural network architecture to model physical activity energy expenditure in older people. - Stylianos Paraschiakos; Cláudio Rebelo de Sá; Jeremiah Okai; P. Eline Slagboom; Marian Beekman; Arno J. Knobbe (Data Min. Knowl. Discov., 2022)

MRI-based and metabolomics-based age scores act synergetically for mortality prediction shown by multi-cohort federated learning. - Pedro Mateus; Swier Garst; Jing Yu; Davy Cats; Alexander G. J. Harms; Mahlet A. Birhanu; Marian Beekman; P. Eline Slagboom; Marcel J. T. Reinders; Jeroen van der Grond; Andre Dekker; Jacobus F. A. Jansen; et al. (CoRR, 2024)