Wiro J. Niessen

Detecting Genetic Interactions with Visible Neural Networks

The paper develops methods to detect non-linear genetic interactions using visible neural networks and applies them to identify significant epistasis pairs in inflammatory bowel disease.

Phenotype prediction using biologically interpretable neural networks on multi-cohort multi-omics data

The paper develops interpretable neural networks for multi-omics data to predict smoking status, age, and LDL levels, showing improved performance and generalizability across cohorts.

Genetic variants for head size share genes and pathways with cancer

This study identifies 67 genetic loci associated with head size, finding strong overlaps with cancer pathways and genes, suggesting shared genetic mechanisms between head growth and cancer risk.

GenNet framework: interpretable neural networks for phenotype prediction

GenNet predicts phenotypes from genetic variants using interpretable deep learning, identifying genes and pathways associated with traits like hair color and schizophrenia.

Changes in the intracranial volume from early adulthood to the sixth decade of life: A longitudinal study

This study reports longitudinal changes in intracranial volume (ICV) from early adulthood to the sixth decade, finding increases until the fourth decade followed by decreases, with cross-sectional results showing larger changes.

High-dimensional mapping of cognition to the brain using voxel-based morphometry and subcortical shape analysis.

The paper maps cognitive performance to brain structure using voxel-based morphometry and subcortical shape analysis in a large population sample.

Genetic Determinants of Cortical Structure (Thickness, Surface Area and Volumes) among Disease Free Adults in the CHARGE Consortium

The paper identifies 161 genome-wide significant genetic associations for cortical structure traits across 34 brain regions, highlighting key biological pathways and gene functions.

Automated Quantification of Enlarged Perivascular Spaces in Clinical Brain MRI across Sites

This paper evaluates two automated methods for quantifying enlarged perivascular spaces in clinical MRI scans across multiple sites, finding one method achieves correlation with visual scoring comparable to inter-rater agreement in some regions.