Modeling intercellular communication in tissues using spatial graphs of cells

Fischer DS, Schaar AC, Theis FJ (2022)

Publication Type: Journal article

Publication year: 2022

Journal

Nature Biotechnology Nature Publishing Group

DOI: 10.1038/s41587-022-01467-z

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.

Involved external institutions

Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt (HMGU) / Helmholtz Munich DE Germany (DE)

How to cite

APA:

Fischer, D.S., Schaar, A.C., & Theis, F.J. (2022). Modeling intercellular communication in tissues using spatial graphs of cells. Nature Biotechnology. https://doi.org/10.1038/s41587-022-01467-z

MLA:

Fischer, David S., Anna C. Schaar, and Fabian J. Theis. "Modeling intercellular communication in tissues using spatial graphs of cells." Nature Biotechnology (2022).

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