Sébastien Dejean

BFWalk is a network propagation algorithm that avoids bias toward highly connected proteins, outperforming existing methods in identifying phenotype-associated genes across four human diseases.

The paper compares optimal transport and machine learning methods for recoding categorical variables in merged clinical datasets with missing data, finding OTrecod more accurate in challenging scenarios.

This meta-analysis of fecal microbiota in lactating Holstein cows identifies a core microbiota and three profiles, highlighting methodological challenges and the need for standardization.

This paper predicts short-term performance in Rugby Union using player tracking data, showing improved prediction ability with multivariate player positions.

The paper generates a spatial RNA profile of catshark habenulae, identifies novel markers, and reveals asymmetry and organizational patterns, providing a reference for studying habenula evolution in jawed vertebrates.

This study integrates genomics, epigenomics, and metabolomics data to identify ADHD biomarkers and explore omics-level connections, finding associations between PGSs, CpGs, and metabolites.

The paper introduces a framework for analyzing heterogeneous omics data using mixOmics, demonstrating its application to Arabidopsis thaliana under sub-optimal temperature conditions.