Johanna Galvis

Stage M2 : AI-powered multimodal integration of spatial omics data

Glioblastoma (GB) is an aggressive brain cancer, characterized by extensive infiltration and metabolic adaptations, yet not fully understood. Spatial transcriptomics (ST) and spatial metabolomics (and lipidomics) through Mass Spectrometry Imaging (MSI), are two powerful omics modalities that allow to dissect the tissue organisation of this cancer. Our bioinformatics team, led

Team Member Thesis Defense: Bioinformatics Methods to Study Metabolism in Glioblastoma – Johanna Galvis

On December 11th 2025, the defense of Johanna Galvis’ Thesis, co-supervised by Macha Nikolski and Thomas Daubon, was held at the IBGC conference room, with the presence of the Jury members: Mohamed Elati, Fabien Jourdan, Florence Cavalli, Lucie Brisson and Nicolas Papadakis. Glioblastoma (GB), the most aggressive form of brain

Open-source tool for the differential analysis of metabolomics data and omics integration: DIMet

Labeled Metabolomics data analysis and integration with DIMet

We’re excited to introduce DIMet (https://github.com/cbib/DIMet/wiki), a powerful tool for the differential analysis of isotope-labeled metabolomics data, developed by our team and recently published in Bioinformatics (Galvis J. et al., 2024; https://doi.org/10.1093/bioinformatics/btae282). DIMet is designed specifically for isotope-labeled

Projects

Bioinformatics for the study of metabolism in glioblastoma

Development of omics data integration methods to elucidate the GB invasiveness

Team

About us

Computational Biology and Bioinformatics is an interdisciplinary team at the CNRS institute in Bordeaux focused on multi-omics and imaging data integration. Our two main pillars are 1) Tackling real biological problems and 2) Combining different areas of technical expertise ...