influential

Overview

The goal of influential is to help identification of the most influential nodes in a network as well as the classification and ranking of top candidate features. This package contains functions for the classification and ranking of features, reconstruction of networks from adjacency matrices and data frames, analysis of the topology of the network and calculation of centrality measures as well as a novel and powerful influential node ranking. The Experimental data-based Integrative Ranking (ExIR) is a sophisticated model for classification and ranking of the top candidate features based on only the experimental data. The first integrative method, namely the Integrated Value of Influence (IVI), that captures all topological dimensions of the network for the identification of network most influential nodes is also provided as a function. Also, neighborhood connectivity, H-index, local H-index, and collective influence (CI), all of which required centrality measures for the calculation of IVI, are for the first time provided in a python package. Additionally, 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.

Check out our paper for a more complete description of the IVI formula and all of its underpinning methods and analyses.

Also, read our preprint on the ExIR model and its validations.

Author

The influential package was written by Adrian Salavaty

Advisors

Mirana Ramialison and Peter D. Currie

How to Install

You can install the official PyPI of the influential with the following code:

pip install influential

Or the development version from GitHub:

pip install git+https://github.com/asalavaty/python-influential.git#egg=influential

Note: If you are using Python 3 you may need to use pip3 instead of pip, as follows.

pip3 install influential
pip3 install git+https://github.com/asalavaty/python-influential.git#egg=influential

Shiny apps

• Influential Software Package web portal

• IVI Shiny App: A shiny app for the calculation of the Integrated Value of Influence (IVI) of network nodes as well as IVI-based visualization of the network.

• ExIR Shiny App: A shiny app for running the Experimental-data-based Integrative Ranking (ExIR) model as well as visualization of its results.

How to cite influential

To cite influential, please cite its associated paper:

• Integrated Value of Influence: An Integrative Method for the Identification of the Most Influential Nodes within Networks. Adrian Salavaty, Mirana Ramialison, Peter D Currie. Patterns. 2020.08.14 (Read online).

How to contribute

Please don’t hesitate to report any bugs/issues and request for enhancement or any other contributions. To submit a bug report or enhancement request, please use the python-influential GitHub issues tracker.