A Q-analysis package for higher-order interactions analysis in Python and its application in network physiology

The developed package makes Q-analysis accessible to a broad research audience, facilitating the exploration of higher-order interactions in complex systems. The presented applications validate its utility across diverse domains, from social networks to neuroscience. By providing an open-source tool, this work bridges a gap in network science, enabling quantitative analysis of the intricate, multi-node structures that define real-world networks.

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Publication Details

Journal
Frontiers in Network Physiology
Published
2025-10-29
DOI
https://doi.org/10.3389/fnetp.2025.1691159
Primary Topic
Complex Network Analysis Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

A Q-analysis package for higher-order interactions analysis in Python and its application in network physiology

Alexander E. Hramov, Semen Kurkin, Nikita Smirnov
Frontiers in Network Physiology
Complex Network Analysis Techniques
article

A Q-analysis package for higher-order interactions analysis in Python and its application in network physiology

Alexander E. Hramov, Semen Kurkin, Nikita Smirnov
article en

Abstract

The developed package makes Q-analysis accessible to a broad research audience, facilitating the exploration of higher-order interactions in complex systems. The presented applications validate its utility across diverse domains, from social networks to neuroscience. By providing an open-source tool, this work bridges a gap in network science, enabling quantitative analysis of the intricate, multi-node structures that define real-world networks.

Frontiers in Network PhysiologyVol. 5
Plekhanov Russian University of Economics (RU), Immanuel Kant Baltic Federal University (RU)
Russian Science Foundation
Openalex Percentile: Top 72%
Complex Network Analysis Techniques
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