  The application of single-cell molecular profiling coupled with spatial
technologies has enabled charting cellular heterogeneity in reference tissues
and in disease. This new wave of molecular data has highlighted the expected
diversity of single-cell dynamics upon shared external queues and spatial
organizations. However, little is known about the relationship between single
cell heterogeneity and the emergence and maintenance of robust multicellular
processes in developed tissues and its role in (patho)physiology. Here, we
present emerging computational modeling strategies that use increasingly
available large-scale cross-condition single cell and spatial datasets, to
study multicellular organization in tissues and complement cell taxonomies.
This perspective should enable us to better understand how cells within tissues
collectively process information and adapt synchronized responses in disease
contexts and to bridge the gap between structural changes and functions in
tissues.
