Rapid Reconstruction of Time-Varying Gene Regulatory Networks

adjmxToSif | Create a .sif file from given adjacency matrix |

calcPerfDiNet | Calculating performance metrics of the directed net... |

checkUnrolledDbn | Checks whether the given unrolled DBN follows 1st Markov... |

CompareNet | Checks if 'di.net.adj.matrix' = 'cmi.net.adj.matrix' |

computeCmi | Compute Conditional Mutual Infortion (CMI) |

ComputeCmiPcaCmi | Compute Conditional Mutual Information (CMI) the way it is... |

ComputEntropy | Compute Entropy matrix from the input data |

ConvertDinetToUndinet | Given a directed network, convert it into an undirected... |

CountFeedFwdEdgesUndi | Count the number of feed-forward edges in a given undirected... |

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... |

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 |

learnCmiNetStruct | Learns the CMI structure |

learnDbnStructLayer3dParDeg1 | Unrolled DBN structure learning with Markov Order 0 and 1. |

LearnDbnStructMo1Clr3Ser | Learns DBN structure of Markov order 1 where candidate... |

learnDbnStructMo1Layer3dParDeg1 | Goal: Unrolled DBN structure learning with Markov Order 1. |

learnDbnStructMo1Layer3dParDeg1_v2 | Goal: Unrolled DBN structure learning with Markov Order 1. |

LearnMiNetStructClr | Learns the CLR network Replaces all non-zero edge weights... |

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... |

reachable.nodes | Returns all the nodes reachable from the given node in the... |

rollDbn | Convert a given unrolled Dynamic Bayesian Network (DBN) into... |

rollDbn_v2 | Convert a given unrolled Dynamic Bayesian Network (DBN) into... |

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.