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  "Title": "Identification and Classification of the Most Influential Nodes",
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  "Description": "Provides functions for the identification, classification,\nand ranking of influential nodes and candidate features from\nnetwork and omics data. The package implements the Integrated\nValue of Influence (IVI) for integrative network centrality\nanalysis, the SIR-based Influence Ranking (SIRIR) model for\nunsupervised influence ranking, and the Experimental data-based\nIntegrative Ranking (ExIR) model for prioritizing candidate\ndriver, biomarker, and mediator features from experimental\nomics data. Functions are provided for network reconstruction\nfrom adjacency matrices and data frames, topological analysis,\ncentrality calculation, assessment of associations between\ncentrality measures, and conditional probability analysis. ExIR\nsupports bulk and single-cell omics data, including matrices,\nsparse matrices, data frames, tibbles, and Seurat objects.",
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      "page": "sirir",
      "title": "SIR-based Influence Ranking",
      "concept": [
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      "title": "Spreading score",
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  "_vignettes": [
    {
      "source": "Vignettes.Rmd",
      "filename": "Vignettes.html",
      "title": "Introduction to influential",
      "author": "r paste(\"Adrian Salavaty\",strftime(Sys.time(),format=\"%d-%b-%Y\"))",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Overview",
        "Fast correlation analysis",
        "Network reconstruction",
        "From a data frame",
        "From an adjacency matrix",
        "From an incidence matrix",
        "From a SIF file",
        "Calculation of centrality measures",
        "Network vertices",
        "Degree centrality",
        "Betweenness centrality",
        "Neighborhood connectivity",
        "H-index",
        "Local H-index",
        "Collective Influence",
        "ClusterRank",
        "Assessment of the association of centrality measures",
        "Conditional probability of deviation from means",
        "Nature of association (considering dependent and independent)",
        "Nature of association (without considering dependence direction)",
        "Identification of the most influential network nodes",
        "Integrated Value of Influence (IVI) from centrality measures",
        "Integrated Value of Influence (IVI) from a graph",
        "Network visualization",
        "IVI shiny app",
        "Identification of the most important network spreaders",
        "Identification of the most important network hubs",
        "Ranking the influence of nodes on the topology of a network based on the SIRIR model",
        "Experimental data-based classification and ranking of top candidate features",
        "Preparing the differential/regression data",
        "Assembling the Diff_data",
        "Preparing the experimental data (Exptl_data)",
        "Optional pseudo-sampling for large datasets",
        "Conservative feature filtering",
        "Running the ExIR model",
        "Running exir on single-cell RNA-seq data",
        "ExIR visualization",
        "ExIR shiny app",
        "Computational manipulation of cells",
        "References"
      ],
      "created": "2020-01-16 03:58:25",
      "modified": "2026-05-28 05:01:26",
      "commits": 10
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