Description Usage Arguments Details Value Author(s) Examples
View source: R/buildFeederObjectDynamic.R
This function estimates the possible mechanisms of interactions to be added to the PKN from a database of interactions for improving the fitting cost.
1 | buildFeederObjectDynamic(model = model, cnolist = cnolist, indices = indices, database = database, pathLength = 2, DDN = TRUE, k = 2, measErr = c(0.1, 0))
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cnolist |
a cnolist structure, as produced by makeCNOlist |
model |
a model as returned by readSIF. Alternatively, the filename can also be provided |
indices |
a list of indices of poorly fitted measurements as returned from identifyMisfitIndices |
database |
a database of interactions which can be optionally provided as an interaction matrix with 3 or 4 colums (source of interaction, sign of interaction, target of interaction and optionally a weight value from 0 to 1 indicating the significance of that interaction in the database). Default: database=NULL |
pathLength |
a path length parameter for the maximal path length of additional interactions to search for in the database. Default: pathLength = 3 |
DDN |
a parameter indicating whether integrating links inferred from the Data-Driven FEED approach. Default: DDN = TRUE |
k |
a parameter that determine the threshold of significancy of the effect of stimuli and inhibitors, default to 2 |
measErr |
a 2 value vector (err1, err2) defining the error model of the data as sd^2 = err1^2 + (err2*data)^2, default to c(0.1, 0) |
The function identifies and proposes the new links to integrate in the PKN either either by means of the data-driven method from the FEED algorithm or from the provided database of interactions or from both of them.
this function returns a list with fields:
Original PKN |
the original PKN |
Feed mechanisms |
the list of proposed interactions to integrate to the PKN (if both the database and the data-driven method are considered by the user, the last mechanism corresponds to the data-driven approach) |
E.Gjerga
1 2 3 4 5 6 7 8 | data(ToyModel_Gene, package="CNORfeeder")
data(CNOlistToy_Gene, package="CNORfeeder")
data(simData_toy,package="CNORfeeder")
feederObject = buildFeederObjectDynamic(model = model, cnolist = cnolist,
indices = indices, database = database,
DDN = TRUE, pathLength = 2)
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