CompareNet              Checks if 'di.net.adj.matrix' =
                        'cmi.net.adj.matrix'
ComputEntropy           Compute Entropy matrix from the input data
ComputeCmiPcaCmi        Compute Conditional Mutual Information (CMI)
                        the way it is done in the implementation of the
                        PCA-CMI algo
ConvertDinetToUndinet   Given a directed network, convert it into an
                        undirected network
CountFeedFwdEdgesUndi   Count the number of feed-forward edges in a
                        given undirected network.
GenTrueAdjMatrix        Generates True net adjacency matrix and save as
                        an R object
LearnClr2NetMfi         Learns CLR2 network
LearnClr3NetMfi         Learn CLR3 network
LearnClrNetFromDiscrData
                        Learns CLR network from a given discretized
                        dataset.
LearnClrNetMfi          Learns CLR network
LearnClrNetMfiVer2.1    Learn CLR2.1 network
LearnDbnStructMo1Clr3Ser
                        Learns DBN structure of Markov order 1 where
                        candidate parents are selected using the CLR3
                        algo.
LearnMiNetStructClr     Learns the CLR network Replaces all non-zero
                        edge weights with 1.
LearnMiNetStructRowMedian
                        Learn the mi network structure
LearnMiNetStructZstat   Learn the mi network structure
LearnTgs                Implementing the TGS Algorithm.
Print.common.di.edges   Given two di network adjacency matrices, it
                        prints the common edges in an output file
adjmxToSif              Create a .sif file from given adjacency matrix
calcPerfDiNet           Calculating performance metrics of the directed
                        net 'inferredNet' w.r.t. the directed net
                        'targetNet'.
checkUnrolledDbn        Checks whether the given unrolled DBN follows
                        1st Markov order or not
computeCmi              Compute Conditional Mutual Infortion (CMI)
discretizeData.2L.Tesla
                        Discretize input data into 2 levels.
discretizeData.2L.wt.l
                        Discretizes input data into two levels.
discretizeData.2L.wt.le
                        Discretizes input data into two levels.
discretizeData.3L.wt    Discretizes input data into three levels, given
                        a tolerance.
discretizeData.5L.wt    Discretizes input data into five levels.
eval.wrt.known.gene.ias
                        Accuracy of predicted directed gene reuglatory
                        network adjacency matrix
learnCmiNetStruct       Learns the CMI structure
learnDbnStructLayer3dParDeg1
                        Unrolled DBN structure learning with Markov
                        Order 0 and 1.
learnDbnStructMo1Layer3dParDeg1
                        Goal: Unrolled DBN structure learning with
                        Markov Order 1.
learnDbnStructMo1Layer3dParDeg1_v2
                        Goal: Unrolled DBN structure learning with
                        Markov Order 1.
reachable.nodes         Returns all the nodes reachable from the given
                        node in the directed adjacency matrix
rollDbn                 Convert a given unrolled Dynamic Bayesian
                        Network (DBN) into a rolled DBN using different
                        rolling methods Rolls time-varying networks
                        into a single time-invariant network. This
                        function is compatible with the time-varying
                        networks learnt through
                        learnDbnStruct3dParDeg1.R::learnDbnStructMo1Layer3dParDeg1().
rollDbn_v2              Convert a given unrolled Dynamic Bayesian
                        Network (DBN) into a rolled DBN using different
                        rolling methods Rolls time-varying networks
                        into a single time-invariant network. This
                        function is compatible with the time-varying
                        networks learnt through
                        learnDbnStruct3dParDeg1.R::learnDbnStructMo1Layer3dParDeg1_v2().
