RANKS (version 1.1)

GBAmax: Guilt By Association (GBA) using the maximum rule

Description

GBAmax implements a Guilt By Association (GBA) method based on the maximum of incident edge weights

Usage

GBAmax(W, ind.positives)

Value

a list with one element:

p

score associated to each node

Arguments

W

numeric matrix representing the adjacency matrix of the graph

ind.positives

indices of the "core" positive examples of the graph. They represent the indices of W corresponding to the positive examples.

Details

GBAmax implements a Guilt By Association (GBA) method for label ranking based on the maximum between the edge weights connecting a node to its positive neighbours

References

Oliver, S., Guilt-by-association goes global, Nature, 403, pp. 601-603, 2000.

See Also

GBAsum

Examples

# Application of GBAmax to the prediction of the DrugBank category Penicillins
# using the Tanimoto chemical structure similarity network 
# between 1253 DrugBank drugs
library(bionetdata);
data(DD.chem.data);
data(DrugBank.Cat);
labels <- DrugBank.Cat[,"Penicillins"];
ind.pos <- which(labels==1);
GBAmax(DD.chem.data, ind.pos);
# Application of GBAmax to the prediction of the DrugBank category "Anti_HIV_Agents"
labels <- DrugBank.Cat[,"Anti_HIV_Agents"];
ind.pos <- which(labels==1);
GBAmax(DD.chem.data, ind.pos);