Binference {CNORfeeder} | R Documentation

## Bayesian network inference

### Description

This function uses data (CNOlist) to infer a Bayesian network using the catnet package.

### Usage

    Binference(CNOlist, mode="AIC", tempCheckOrders=10,
                maxIter=100, filename="BAYESIAN")

### Arguments

`CNOlist` | a CNOlist structure, as produced by makeCNOlist
`mode` | a character, optimization network selection criterion such as "AIC" and "BIC", to be used in cnSearchSA
`tempCheckOrders` | an integer, the number of iteration, orders to be searched, with constant temperature, to be used in cnSearchSA
`maxIter` | an integer, the total number of iterations, thus orders, to be processed, to be used in cnSearchSA
`filename` | name of the sif file saved, default BAYESIAN

### Details

This function transforms the data in a format compatible with catnet package, infers the network using the Stochastic Network Search as implemented in catnet (see cnSearchSA), computes the consensus model of the models returned by cnSearchSA considering only links that have a frequency of appearence greater than 0.1 and returns the model in the sif format.

### Value

`sif` | the inferred data-driven network in sif format

### Author(s)

F.Eduati

### See Also

mapDDN2model

### Examples

    data(CNOlistDREAM,package="CellNOptR")
    DDN<-Binference(CNOlistDREAM, tempCheckOrders=10, maxIter=100,
                    filename="BAYESIAN")

[Package CNORfeeder version 1.30.0 Index]