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NAR Genomics and Bioinformatics|January 6, 2022
Differential analysis of binarized single-cell RNA sequencing data captures biological variationGerard A Bouland, Ahmed Mahfouz, Marcel J T ReindersGenome Biology|April 21, 2023
Consequences and opportunities arising due to sparser single-cell RNA-seq datasetsGerard A Bouland, Ahmed Mahfouz, Marcel J T ReindersNeurology. Genetics|May 1, 2023
Identifying Aging and Alzheimer Disease-Associated Somatic Variations in Excitatory Neurons From the Human Frontal CortexMeng Zhang, Gerard A Bouland, Henne Holstege, et al.Biorxiv : the Preprint Server for Biology|September 30, 2024
gsQTL: Associating genetic risk variants with gene sets by exploiting their shared variabilityGerard A Bouland, Niccolò Tesi, Ahmed Mahfouz, et al.Bioinformatics (Oxford, England)|September 11, 2019
NACHO: an R package for quality control of NanoString nCounter dataMickaël Canouil, Gerard A Bouland, Amélie Bonnefond, et al.Medrxiv : the Preprint Server for Health Sciences|June 9, 2023
Single-cell RNA sequencing data reveals rewiring of transcriptional relationships in Alzheimer's Disease associated with risk variantsGerard A Bouland, Kevin I Marinus, Ronald E van Kesteren, et al.NAR Genomics and Bioinformatics|February 12, 2021
CONQUER: an interactive toolbox to understand functional consequences of GWAS hitsGerard A Bouland, Joline W J Beulens, Joey Nap, et al.BMC Genomics|May 15, 2022
Diabetes risk loci-associated pathways are shared across metabolic tissuesGerard A Bouland, Joline W J Beulens, Joey Nap, et al.Diabetologia|February 20, 2024
An omics-based machine learning approach to predict diabetes progression: a RHAPSODY studyRoderick C Slieker, Magnus Münch, Louise A Donnelly, et al.Diabetologia|June 10, 2021
Replication and cross-validation of type 2 diabetes subtypes based on clinical variables: an IMI-RHAPSODY studyRoderick C Slieker, Louise A Donnelly, Hugo Fitipaldi, et al.Pageof 2