{
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  "Package": "BioNet",
  "Type": "Package",
  "Title": "Routines for the functional analysis of biological networks",
  "Version": "1.73.0",
  "Date": "2015-09-11",
  "Author": "Marcus Dittrich and Daniela Beisser",
  "Maintainer": "Marcus Dittrich\n<marcus.dittrich@biozentrum.uni-wuerzburg.de>",
  "Description": "This package provides functions for the integrated\nanalysis of protein-protein interaction networks and the\ndetection of functional modules. Different datasets can be\nintegrated into the network by assigning p-values of\nstatistical tests to the nodes of the network. E.g. p-values\nobtained from the differential expression of the genes from an\nAffymetrix array are assigned to the nodes of the network. By\nfitting a beta-uniform mixture model and calculating scores\nfrom the p-values, overall scores of network regions can be\ncalculated and an integer linear programming algorithm\nidentifies the maximum scoring subnetwork.",
  "License": "GPL (>= 2)",
  "LazyLoad": "yes",
  "URL": "http://bionet.bioapps.biozentrum.uni-wuerzburg.de/",
  "biocViews": "Microarray, DataImport, GraphAndNetwork, Network,\nNetworkEnrichment, GeneExpression, DifferentialExpression",
  "Config/pak/sysreqs": "libglpk-dev libpng-dev libxml2-dev libssl-dev\nzlib1g-dev",
  "Repository": "https://bioc.r-universe.dev",
  "Date/Publication": "2026-04-28 12:34:46 UTC",
  "RemoteUrl": "https://github.com/bioc/BioNet",
  "RemoteRef": "HEAD",
  "RemoteSha": "52d7a61b57fb54e8cefb3d64bed2aeb926a4ad94",
  "NeedsCompilation": "no",
  "Packaged": {
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    "User": "root"
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  "MD5sum": "c117fea654d665b97690aa11c76e302d",
  "_user": "bioc",
  "_type": "src",
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  "_created": "2026-05-29T08:37:52.000Z",
  "_published": "2026-05-29T10:33:37.393Z",
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    "email": "marcus.dittrich@biozentrum.uni-wuerzburg.de"
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    "dataimport",
    "graphandnetwork",
    "network",
    "networkenrichment",
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    "name": "Bioconductor",
    "description": "Software for the analysis and comprehension of high-throughput genomic data"
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  "_cranurl": false,
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    "consensusScores",
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    "fbumLL",
    "fdrThreshold",
    "fitBumModel",
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    "largestScoreComp",
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    "loadNetwork.tab",
    "makeNetwork",
    "mapByVar",
    "permutateNodes",
    "piUpper",
    "plot.bum",
    "plot3dModule",
    "plotLLSurface",
    "plotModule",
    "print.bum",
    "readHeinzGraph",
    "readHeinzTree",
    "resamplingPvalues",
    "rmSelfLoops",
    "runFastHeinz",
    "runHeinz",
    "save3dModule",
    "saveNetwork",
    "scanFDR",
    "scoreFunction",
    "scoreNodes",
    "scoreOffset",
    "sortedEdgeList",
    "subNetwork",
    "summary.bum",
    "writeHeinz",
    "writeHeinzEdges",
    "writeHeinzNodes"
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      "title": "Example p-values for aggregation statistics",
      "object": "pvaluesExample",
      "file": "pvaluesExample.rda",
      "class": [
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        "array"
      ],
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        "p.vals2"
      ],
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      "table": true,
      "tojson": true
    }
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    {
      "page": "BioNet-package",
      "title": "Routines for the functional analysis of biological networks",
      "topics": [
        "BioNet-package",
        "BioNet"
      ]
    },
    {
      "page": "aggrPvals",
      "title": "Aggregate several p-values into one p-value",
      "topics": [
        "aggrPvals"
      ]
    },
    {
      "page": "bumOptim",
      "title": "Fitting a beta-uniform mixture model to p-value distribution",
      "topics": [
        "bumOptim"
      ]
    },
    {
      "page": "compareNetworks",
      "title": "Compare parameters of two networks",
      "topics": [
        "compareNetworks"
      ]
    },
    {
      "page": "consensusScores",
      "title": "Calculation of a consensus score for a network",
      "topics": [
        "consensusScores"
      ]
    },
    {
      "page": "fbum",
      "title": "Compute the density of the bum distribution",
      "topics": [
        "fbum"
      ]
    },
    {
      "page": "fbumLL",
      "title": "Calculate log likelihood of BUM model",
      "topics": [
        "fbumLL"
      ]
    },
    {
      "page": "fdrThreshold",
      "title": "Calculate p-value threshold for given FDR",
      "topics": [
        "fdrThreshold"
      ]
    },
    {
      "page": "fitBumModel",
      "title": "Fit beta-uniform mixture model to a p-value distribution",
      "topics": [
        "fitBumModel"
      ]
    },
    {
      "page": "getCompScores",
      "title": "Partition scores for subgraphs of the network",
      "topics": [
        "getCompScores"
      ]
    },
    {
      "page": "getEdgeList",
      "title": "Get representation of graph as edgelist",
      "topics": [
        "getEdgeList"
      ]
    },
    {
      "page": "hist.bum",
      "title": "Histogram of the p-value distribution with the fitted bum model",
      "topics": [
        "hist.bum"
      ]
    },
    {
      "page": "largestComp",
      "title": "Extract largest component of network",
      "topics": [
        "largestComp"
      ]
    },
    {
      "page": "largestScoreComp",
      "title": "Component with largest score",
      "topics": [
        "largestScoreComp"
      ]
    },
    {
      "page": "loadNetwork.sif",
      "title": "Load network from Cytoscape sif file",
      "topics": [
        "loadNetwork.sif"
      ]
    },
    {
      "page": "loadNetwork.tab",
      "title": "Load network from tabular format",
      "topics": [
        "loadNetwork.tab"
      ]
    },
    {
      "page": "makeNetwork",
      "title": "Create graph from source and target vectors",
      "topics": [
        "makeNetwork"
      ]
    },
    {
      "page": "mapByVar",
      "title": "Select probeset by variance and get PPI ID",
      "topics": [
        "mapByVar"
      ]
    },
    {
      "page": "permutateNodes",
      "title": "Permute node labels",
      "topics": [
        "permutateNodes"
      ]
    },
    {
      "page": "piUpper",
      "title": "Upper bound pi for the fraction of noise",
      "topics": [
        "piUpper"
      ]
    },
    {
      "page": "plot.bum",
      "title": "Quantile-quantile plot for the beta-uniform mixture model",
      "topics": [
        "plot.bum"
      ]
    },
    {
      "page": "plot3dModule",
      "title": "3D plot of the network",
      "topics": [
        "plot3dModule"
      ]
    },
    {
      "page": "plotLLSurface",
      "title": "Log likelihood surface plot",
      "topics": [
        "plotLLSurface"
      ]
    },
    {
      "page": "plotModule",
      "title": "Plot of the network",
      "topics": [
        "plotModule"
      ]
    },
    {
      "page": "print.bum",
      "title": "Print information about bum model",
      "topics": [
        "print.bum"
      ]
    },
    {
      "page": "pvaluesExample",
      "title": "Example p-values for aggregation statistics",
      "topics": [
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      ]
    },
    {
      "page": "readHeinzGraph",
      "title": "Convert HEINZ output to graph",
      "topics": [
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      ]
    },
    {
      "page": "readHeinzTree",
      "title": "Convert HEINZ output to tree",
      "topics": [
        "readHeinzTree"
      ]
    },
    {
      "page": "resamplingPvalues",
      "title": "Resampling of microarray expression values and test for differential expression.",
      "topics": [
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      ]
    },
    {
      "page": "rmSelfLoops",
      "title": "Remove self-loops in a graph",
      "topics": [
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      ]
    },
    {
      "page": "runFastHeinz",
      "title": "Calculate heuristically maximum scoring subnetwork",
      "topics": [
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      ]
    },
    {
      "page": "runHeinz",
      "title": "Start HEINZ",
      "topics": [
        "runHeinz"
      ]
    },
    {
      "page": "save3dModule",
      "title": "Save a 3D plot of the network",
      "topics": [
        "save3dModule"
      ]
    },
    {
      "page": "saveNetwork",
      "title": "Save undirected network in various formats",
      "topics": [
        "saveNetwork"
      ]
    },
    {
      "page": "scanFDR",
      "title": "Dataframe of scores over a given range of FDRs",
      "topics": [
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    },
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      "page": "scoreFunction",
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      "topics": [
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      "topics": [
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