Description Usage Arguments Details Value Author(s) References Examples

View source: R/infoTheoreticLabeled.R

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.

1 | ```
infoTheoreticLabeledV2(g, ci=NULL, lambda=1000)
``` |

`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. |

For details see the vignette.

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. |

Michael Schutte

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

1 2 3 4 5 6 7 | ```
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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