Maud Fagny

The paper identifies genomic and transcriptomic factors determining gene dispensability in maize by analyzing a pan-gene set and transcriptomic profiles across multiple tissues.

This study shows NM1 regulates adipose tissue remodeling, metabolic inflammation, and obesity in mice by controlling chromatin accessibility and gene expression during adipogenesis.

The paper analyzes SNP heritability across eQTL networks to show heritability clusters in tissue-specific modules and local hubs, which influence complex trait evolution.

The paper develops an epigenetic age predictor that accounts for DNA sequence variation in African populations, finding that genetic variants can influence epigenetic age and longevity.

The paper integrates genomic, epigenomic, and transcriptomic data to model enhancer-driven gene regulatory networks in maize tissues, identifying tissue-specific transcription factor families and transposable element contributions.

PUMA integrates miRNA target predictions with gene expression data to identify tissue-specific miRNA regulatory interactions and their disease relevance.

The paper assesses the reproducibility and functional importance of eQTL network nodes by analyzing degree centrality across 21 GTEx tissues.

The paper identifies ancestry-related DNA methylation differences and their causal impact on immune gene regulation using monocytes and Bayesian analysis.

The paper identifies genomic variants associated with immune cell infiltration using histopathological image QTL analysis.

The paper develops a preprocessing and normalization pipeline for large-scale RNA-Seq data, addressing batch and tissue effects in heterogeneous datasets.

This study analyzes gene regulation across 38 tissues to show that transcription factor-target connections are more tissue-specific than genes, and that tissue-specific genes are not highly targeted in their networks but occupy bottleneck positions.

The paper compares gene expression and regulatory patterns between cell lines and their source tissues, finding reduced expression levels and altered transcription factor regulation in cell lines.

The paper uses a network-based approach to analyze eQTLs across 13 tissues, identifying cis- and trans-eQTLs and linking SNPs to biological processes and disease associations.

The paper identifies sexual dimorphism in gene expression and regulatory networks across 31 human tissues using GTEx data, showing that many genes and networks are sex-specific.

The paper identifies age-related DNA methylation patterns in African hunter-gatherer populations and shows that genetic variation at meQTLs influences these associations.