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Fig. 2 | BMC Biology

Fig. 2

From: Griottes: a generalist tool for network generation from segmented tissue images

Fig. 2

a Confocal dorsal view of the zebrafish adult pallium. Glial fibrillary acidic protein (GFAP) in green, Proliferating cell nuclear antigen (PCNA) in magenta and Zonula occludens-1 (ZO1) in white or blue. ZO1 is highlighting the apical domain of the cells allowing the identification of their apical area. Inset: spotlight on a limited tissue area, the ZO1 membrane staining allows for the exact localization of cell membranes. Scale bar is 100 μm. Griottes incorporates different network construction methods. The contact-based method connects cells sharing a common membrane, the Delaunay and Geometric graphs are commonly used graph-generation methods. c The graphs generated from a same set of nodes with different construction rules have different properties. For instance, the degree distribution of a Geometric graph is broader than that of the Contact and Delaunay graph. d Mean PCNA signal within the cells in the example tissue. Cells with an average intensity above 6500 (red line) are considered PCNA+, the other cells are PCNA−. e Thresholding intensity signals converts a network populated with continuous fluorescence signals to a network populated with categorical cell types. f. Representation of the example network (panel b) where node colors represent cell type. Left: the network is projected on the ZO1 signal. Right: the network is projected on the PCNA signal. This method reliably incorporates cell type information into the network representation of the tissue. g Left: connected cells can have widely varying contact surfaces. Right: this information can be encoded into the network by weighting the links between cells. Two differing cell-cell interfaces (pink lines) have different link weights in the network representation of the tissue (pink arrows). h The connection between cells can be quantified at scale: the histogram of link weights in the tissue shown in panel a

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