Modeling intercellular communication in tissues using spatial graphs of cells
David S. Fischer, Anna C. Schaar, Fabian J. Theis
Abstract
Models of intercellular communication in tissues are based on molecular profiles of dissociated cells, are limited to receptor-ligand signaling and ignore spatial proximity in situ. We present node-centric expression modeling, a method based on graph neural networks that estimates the effects of niche composition on gene expression in an unbiased manner from spatial molecular profiling data. We recover signatures of molecular processes known to underlie cell communication.
Topics & Concepts
BiologyMolecular communicationComputational biologyIntracellularNicheIn situ hybridizationGene regulatory networkGene expression profilingCell biologyGene expressionComputer scienceGeneGeneticsComputer networkEcologyChannel (broadcasting)TransmitterSingle-cell and spatial transcriptomicsGene Regulatory Network AnalysisMolecular Communication and Nanonetworks