German Preciat

XomicsToModel integrates multi-omics data with a generic metabolic model to generate context-specific, thermodynamically consistent metabolic models.

The paper infers patient-specific metabolic fluxes in breast cancer using metabolic models and machine learning, showing they reflect molecular subtypes and heterogeneity but not clinical features.

fluxTrAM automates processing of tracer-based metabolomics data and integrates it with genome-scale metabolic models for flux analysis.

This paper introduces a new method for genome-scale metabolic flux inference using conserved moieties, demonstrating its computational efficiency and accuracy with isotopic labeling data.

The paper develops genome-scale metabolic models of human dopaminergic neurons to study metabolic dysfunction in Parkinson's disease using exometabolomic and transcriptomic data.

AGORA2 reconstructs the human microbiome at scale, revealing individual-specific drug metabolism capabilities and correlations with clinical parameters.

The paper simulates alpha-synuclein spread using a connectome model and finds connectivity alone is insufficient to explain observed pathology patterns in rats.

The paper introduces the Virtual Metabolic Human database, which integrates human and gut microbiome metabolism with nutrition and disease data to support biomedical research.