Johan A. Westerhuis

Multi-omics data analysis reveals a novel beneficial role for strigolactones in tomato

This study identifies strigolactones as nitrogen-responsive rhizosphere signals in tomato that recruit beneficial bacteria under nitrogen limitation.

Supervised restricted data fusion with common, local & distinct components

PESCAR improves detection of subtle response-related patterns in multi-omics data by integrating response information into multiblock decomposition.

ACMTF-R: supervised multi-omics data integration uncovering shared and distinct outcome-associated variation

ACMTF-R integrates multi-omics data to identify shared and distinct outcome-associated variation, outperforming existing methods in simulated and real-world datasets.

parafac4microbiome: Exploratory analysis of longitudinal microbiome data using Parallel Factor Analysis

This paper introduces PARAFAC for analyzing longitudinal microbiome data, demonstrating its effectiveness in identifying temporal patterns across three studies.

MASCARA: coexpression analysis in data from designed experiments

MASCARA improves coexpression analysis in designed experiments by removing experimental variance to detect pathway-related coexpression patterns.

Multi-way modelling of oral microbial dynamics and host-microbiome interactions during induced gingivitis

This study uses PARAFAC to analyze oral microbiome and metabolome dynamics during experimental gingivitis, identifying microbial subcommunities and metabolic pathways linked to inflammation.

A Strategy for Differential Abundance Analysis of Sparse Microbiome Data with Group-wise Structured Zeros

The paper proposes a combined differential abundance analysis method for sparse microbiome data with group-wise zeros, validated through simulations and applied to plant microbiome datasets.

STATegra: a comprehensive multi-omics dataset of B-cell differentiation in mouse

The paper presents STATegra, a multi-omics dataset of mouse B-cell differentiation combining 10 omics technologies to study dynamic cellular processes.

iTOP: Inferring the Topology of Omics Data

iTOP infers relationships between omics datasets using partial matrix correlations and identifies gene expression as a mediator between other datasets and drug response.