Cargando…
Inferring a spatial code of cell-cell interactions across a whole animal body
Cell-cell interactions shape cellular function and ultimately organismal phenotype. Interacting cells can sense their mutual distance using combinations of ligand-receptor pairs, suggesting the existence of a spatial code, i.e., signals encoding spatial properties of cellular organization. However,...
Autores principales: | Armingol, Erick, Ghaddar, Abbas, Joshi, Chintan J., Baghdassarian, Hratch, Shamie, Isaac, Chan, Jason, Her, Hsuan-Lin, Berhanu, Samuel, Dar, Anushka, Rodriguez-Armstrong, Fabiola, Yang, Olivia, O’Rourke, Eyleen J., Lewis, Nathan E. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9714814/ https://www.ncbi.nlm.nih.gov/pubmed/36395331 http://dx.doi.org/10.1371/journal.pcbi.1010715 |
Ejemplares similares
-
Combining LIANA and Tensor-cell2cell to decipher cell-cell communication across multiple samples
por: Baghdassarian, Hratch, et al.
Publicado: (2023) -
Whole-body gene expression atlas of an adult metazoan
por: Ghaddar, Abbas, et al.
Publicado: (2023) -
Context-aware deconvolution of cell–cell communication with Tensor-cell2cell
por: Armingol, Erick, et al.
Publicado: (2022) -
StanDep: Capturing transcriptomic variability improves context-specific metabolic models
por: Joshi, Chintan J., et al.
Publicado: (2020) -
Correction: StanDep: Capturing transcriptomic variability improves context-specific metabolic models
por: Joshi, Chintan J., et al.
Publicado: (2022)