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Average degree of neighbors within the neighborhood subgraph. Measures how interconnected a node's neighbors are. Proposed by Li et al. (2011) for identifying essential proteins in PPI networks.

Usage

centrality_lac(x, mode = "all", ...)

Arguments

x

Network input (matrix, igraph, network, cograph_network, tna object).

mode

For directed networks: "all" (default), "in", or "out".

...

Additional arguments passed to centrality (e.g., normalized, weighted, directed).

Value

Named numeric vector of LAC values.

References

Li, M., Wang, J., Chen, X., Wang, H., & Pan, Y. (2011). A local average connectivity-based method for identifying essential proteins from the network level. Computational Biology and Chemistry, 35(3), 143-150.

See also

centrality for computing multiple measures at once, centrality_dmnc for another neighborhood density measure.

Examples

adj <- matrix(c(0, 1, 1, 1, 0, 1, 1, 1, 0), 3, 3)
rownames(adj) <- colnames(adj) <- c("A", "B", "C")
centrality_lac(adj)
#> A B C 
#> 1 1 1