V2 information functional for vertex-labeled graphs

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Description

This method assigns a probability value to each vertex of the network using the V2 information functional for vertex-labeled graphs. It is based on the same principles as infoTheoreticGCM.

Usage

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infoTheoreticLabeledV2(g, ci=NULL, lambda=1000)

Arguments

g

a graph as a graphNEL object. Each vertex must have an "atom" data attribute specifying its atomic number or chemical symbol.

ci

a list (or named vector) mapping each chemical symbol to a coefficient value. If not specified, 1 will be used for all elements.

lambda

specifies the scaling constant for the distance measures. The default value is 1000.

Details

For details see the vignette.

Value

The returned list consists of the following items:

entropy

contains the calculated entropy measure.

distance

contains the calculated distance measure.

pis

contains the calculated probability distribution.

fvi

contains the calculated values of the functional for each vertex.

Author(s)

Michael Schutte

References

M. Dehmer, N. Barbarini, K. Varmuza, and A. Graber. Novel topological descriptors for analyzing biological networks. BMC Structural Biology, 10:18, 2010.

Examples

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set.seed(987)
g <- randomEGraph(as.character(1:10), 0.3)

nodeDataDefaults(g, "atom") <- "C"
nodeData(g, "2", "atom") <- "O"

infoTheoreticLabeledV2(g, ci=list(`C` = 0.5, `O` = 0.8))

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