Identification and Classification of the Most Influential Nodes
Vertex betweenness centrality
Centrality-based network visualization
ClusterRank (CR)
Collective Influence (CI)
Computational manipulation of cells
Conditional probability of deviation from means
Assembling the differential/regression data
Assessment of innate features and associations of two network centrali...
Assessment of innate features and associations of two network centrali...
Experimental data-based Integrated Ranking
Visualization of ExIR results
Fast correlation and mutual rank analysis
H-index
Hubness score
Influential package
Integrated Value of Influence (IVI)
Integrated Value of Influence (IVI)
local H-index (LH-index)
Neighborhood connectivity
Objects exported from other packages
Run shiny app
SIF to igraph
SIR-based Influence Ranking
Spreading score
Contains functions for the classification and ranking of top candidate features, reconstruction of networks from adjacency matrices and data frames, analysis of the topology of the network and calculation of centrality measures, and identification of the most influential nodes. Also, a function is provided for running SIRIR model, which is the combination of leave-one-out cross validation technique and the conventional SIR model, on a network to unsupervisedly rank the true influence of vertices. Additionally, some functions have been provided for the assessment of dependence and correlation of two network centrality measures as well as the conditional probability of deviation from their corresponding means in opposite direction. Fred Viole and David Nawrocki (2013, ISBN:1490523995). Csardi G, Nepusz T (2006). "The igraph software package for complex network research." InterJournal, Complex Systems, 1695. Adopted algorithms and sources are referenced in function document.
Useful links