October 2022: “BioImageIT: Open-source framework for integration of image data management with analysis” is now published on line in Nature Methods (2022, October): https://www.nature.com/articles/s41592-022-01642-9, BioImageIT software.
- “BioImageIT: integrating image data management with analysis” (France BioImaging NewsLetter)
March 2022: We are opening one PhD position for the segmentation and tracking of 3D+time microscopy images! Please see description and apply here:
- Algorithmes hybrides CNN-Snake pour l’analyse quantitative d’images 3D+temps de cellules vivantes (french)
- Hybrid CNN-Snake algorithms for the quantitative analysis of 3D live cell images (english)
October 2021: “DeepFinder improves macromolecule identification in 3D cellular cryo-electron tomograms” is now published on line in Nature Methods (2021, October): https://www.nature.com/articles/s41592-021-01275-4, DeepFinder software.
- “A new AI-enabled open source algorithm for the detection of molecular structures inside native cells” (HelmHoltz Pionner Campus)
- “Deep learning improves macromolecule identification in 3D cellular cryo-electron tomograms” (France BioImaging NewsLetter)
The main objective of the joint SERPICO Project-Team (INRIA Rennes – Bretagne Atlantique – UMR 144 CNRS Institut Curie (“Subcellular Structure and Cellular Dynamics” Unit) is to decipher the dynamic coordination and organization of molecular complexes at the single cell level. We focus on the cellular and molecular mechanisms of membrane traffic involved in the biogenesis of specialized organelles in epidermal cells with main functions in the immune system and in skin pigmentation and photoprotection. The mathematical theories and algorithms are mainly developed to identify other molecular processes in fundamental biology but they have also a strong potential for applications in biotechnology and medicine: disease diagnosis, detection of genomic instabilities, deterioration of cell cycle, epigenetic mechanisms and cancer prevention. Multidimensional and multimodal light microscopy combined with GFP (Green Fluorescence Protein) tagging has taken a prominent role in life science research due to its ability to study biomolecules within the entire cell and particular cell compartments or domains. We plan to investigate new imaging techniques and processing methods, mathematical models, and algorithms to build an integrated imaging approach that bridges the resolution gaps between the molecule and the whole cell, in space and time. We address the following themes:
- image superresolution/image denoising to preserve cell integrity (photo-toxicity versus exposure time) and image analysis in multidimensional microscopy
- spatio-temporal organization modelling of molecular species and multiscale architectures in light and electron microscopy
- computational simulation, modelling, dynamic comparison and classification of molecules trafficking at different spatial and temporal scales / biophysical model assimilation for dynamic representation in videomicroscopy and prediction in biology
Experiments in vivo for la large class of stimuli (e.g. micro-patterning, SiRNA, drugs) will be conducted to confirm the biological hypotheses and to discern wheter the changes in expression have a role in the mechanisms under study.
The SERPICO team and the UMR144 CNRS Institut Curie Unit / PICT (Cell and Tissue Imaging Facilities) – IBiSA) are partners of France BioImaging the distributed coordinated French infrastructure and electronic cellular BioImaging dedicated to innovation, training and transfer.
- UMR 144 Cell Biology and Cancer, Institut Curie, STED Team, PICT-IBiSA, Paris
- UMR 168 Physico-Chimie Curie Lab – Institut Curie, Paris
- UMR3666/U1143 Cellular and Chemical Biology – Institut Curie, Paris
LMJL Département de Mathématique, Unversité de Nantes
- IRSN – Institut de Radioprotection et Sureté Nucléaire
- Grenoble Insitute Neurosciences
- Helmholtz Zentrum München, Cell Architecture Lab,Neuherberg, Germany