Florian Tran

Interferon-independent STING enforces epithelial genome-integrity checkpoint to restrain tumor evolution

This study shows that STING acts as a genome-integrity checkpoint in epithelial cells, independent of interferon, and its loss leads to chromosomal instability and tumor development.

Long-Term Intestinal Epithelial Remodeling Induced by Acute Protein-Energy Malnutrition

This study investigates long-term intestinal epithelial changes after acute protein-energy malnutrition using multi-omics approaches and identifies microbial lipid metabolites and epigenetic factors as key drivers of persistent Paneth cell dysfunction.

Simultaneous Profiling of the Blood and Gut T and B Cell Repertoires in Crohn's Disease and Symptomatic Controls Illustrates Tissue-specific Alterations in the Immune Repertoire of Crohn's Disease Patients

Quantifying The Impact of Bulk TCR-Seq Methodological Choices on The Profiled T Cell Repertoire

This study evaluates how methodological choices in bulk TCR-Seq affect T cell repertoire profiling, finding that RNA/DNA quality significantly impacts results and that low quantities can be partially compensated by increasing PCR cycles.

Metabolic modeling reveals a multi-level deregulation of host-microbiome metabolic networks in IBD

This study uses metabolic modeling to uncover host-microbiome metabolic dysregulation in IBD, identifying key pathways and potential therapeutic interventions.

Association of ulcerative colitis with atopic dermatitis: identification of shared and unique mechanisms by construction and computational analysis of disease maps

This paper constructs and compares computational disease maps of ulcerative colitis and atopic dermatitis to identify shared and unique molecular mechanisms and potential therapeutic targets.

FixNCut: Single-cell genomics through reversible tissue fixation and dissociation

FixNCut is a reversible fixation and dissociation method that preserves RNA integrity and cellular composition in human and mouse tissues, enabling robust single-cell and spatial analyses.

Swarm Learning as a privacy-preserving machine learning approach for disease classification

This paper introduces Swarm Learning, a decentralized machine learning approach for disease classification using transcriptomic data, demonstrating its effectiveness in developing classifiers for COVID-19, tuberculosis, and leukemias while preserving privacy.