Panagiotis Mandros

This paper introduces Giraffe, a matrix factorization method for gene regulatory network inference that estimates signed regulatory effects, showing improved accuracy in distinguishing activating and inhibitory interactions across multiple biological contexts.

The paper develops a Nextflow workflow for reproducibly inferring regulatory networks from TCGA data, showing its application to colon cancer subtypes.

This study investigates how loss of the Y chromosome in lung adenocarcinoma affects the tumor immune environment and response to immunotherapy.

BONOBO infers sample-specific co-expression networks to capture individual heterogeneity in gene regulation, outperforming existing methods in yeast, breast cancer, and thyroid tissue analyses.

This paper introduces node2vec2rank, a method for graph differential analysis that identifies biologically relevant differences between weighted networks in cancer subtypes and single-cell dynamics.