findFBLs: Identifies feedback loops in a network or in a set of...

In csclab/RMut: RMut: a collective framework for mutations analysis in network dynamics

Description

Searches and counts feedback loops for all nodes/edges in a network or in a set of networks.

Usage

findFBLs(networks, maxLength = 2L)

Arguments

networks	A network or a set of networks used for FBLs search
maxLength	The maximal length of FBLs, default is 2

Details

This function searches feedback loops (FBLs) in a specific network or in a set of networks. For each network, the returned results are stored in two corresponding data frames of node/edge attributes. Each data frame has one column for node/edge identifiers, and three columns contain corresponding number of involved FBLs and number of involved positive/negative FBLs. Another data frame of the network object, "network" data frame, contains total number of FBLs and total number of positive/negative FBLs in the network.

Value

The updated network objects including number of FBLs for each node/edge.

See Also

findFFLs, calCentrality, calSensitivity

Examples

data(amrn)
amrn <- findFBLs(amrn, maxLength = 10)
print(amrn$nodes)
print(amrn$edges)
print(amrn$network)

csclab/RMut documentation built on May 14, 2019, 12:07 p.m.