Isabelle Fournier

SpacePath improves spatial metabolomics analysis by handling molecular ambiguity and identifying novel lipid families in spatial datasets.

The paper integrates SpiderMass mass spectrometry with clinical and microbiome data to improve intraoperative margin delineation and prognosis in esophageal-gastric cancers.

The paper expands and refines a reference catalog of human non-canonical open reading frames (ncORFs) by incorporating more datasets and introducing a translation signature score framework to prioritize high-quality ncORFs.

The paper develops a machine-learning pipeline using mass spectrometry imaging to create molecular digital twins for real-time oncological surgery, enabling precise tumor margin delineation and bacterial strain prediction.

The paper predicts proteins and pathways from lipid analyses using MALDI MSI and dry proteomics in glioblastoma, showing lipid-protein associations linked to patient prognosis.

Proximity-dependent biotinylation (BioID) of 28 SARS-CoV-2 proteins in human cells maps 5,415 proximal interactions with 2,128 host targets across basal and poly(I:C) conditions.

The paper develops a cumulative learning approach for classifying small mass spectrometry datasets using 1D-CNNs, achieving high accuracy across diverse biological contexts.