Work

Informeasure: an R/bioconductor package for quantifying nonlinear dependence between variables in biological networks from an information theory perspective

Year: 2024

Type: article

Abstract: BACKGROUND: Using information measures to infer biological regulatory networks can capture nonlinear relationships between variables. However, it is computationally challenging, and there is a lack of convenient tools. RESULTS: We introduce Informeasure, an R package designed to quantify nonlinear dependencies in biological regulatory networks from an information theory perspective. This package compiles a comprehensive set of information measurements, including mutual information, conditional mutual information, interaction information, partial information decomposition, and part mutual information. Mutual information is used for bivariate network inference, while the other four estimators are dedicated to trivariate network analysis. CONCLUSIONS: Informeasure is a turnkey solution, allowing users to utilize these information measures immediately upon installation. Informeasure is available as an R/Bioconductor package at https://bioconductor.org/packages/Informeasure .

Source: BMC Bioinformatics

DOI: 10.1186/s12859-024-05996-z

Authors: Chu Pan, Yanlin Chen

Institutions: Hunan University, Henan University of Engineering

Language: English

Topic: Gene Regulatory Network Analysis

Subfield: Molecular Biology

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: gold

Estimated APC paid: $2,890

Funder: National Natural Science Foundation of China