SOURCE-LINKED INTELLIGENCE
Graph Deep Learning for detection of INtracellular and SPatial interactions Revealing niches
Graph Deep Learning for detection of INtracellular and SPatial interactions Revealing niches Tissues are multicellular systems organized into niches, highly specialized communities of spatially co-localized cells (spatial neighborhood) that interact with one another (intercellular signaling), shaping their coordinated functions (intracellular states). Advances in single-cell sequencing and spatially resolved technologies now enable the reconstruction of whole-tissue spatial atlases spanning millions of cells and thousands of molecular features (e.g., transcriptomics, epigenomics). However, identifying functional niches from these data remains challenging due to the complexity and multidimensionality of biological processes, as well as the scale of modern datasets. INSPiRe project proposes a novel graph deep learning–based computational framework that integrates single-cell multi-omics with spa
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- recordType
- award
- status
- SIGNED
- region
- EU
- value
- 202125.12
- unit
- EUR
Evidence & attribution
European Commission, CORDIS Horizon Europe project dataset. Metadata adapted.
License: CORDIS reuse policy
First collected: 2026-09-20T05:31:32.981Z. This is not the publication date.