Work

Exploring Network Curvature Differences in Gene Expression Networks

Year: 2024

Type: conference-paper

Abstract: Networks and their properties have been used to study complex biological systems. Recently, network curvature measures have demonstrated the ability to capture relevant network properties. This study employs network curvature measures to analyse gene expression correlations in various human tissues for identifying unique topological features that differentiate these groups. Preliminary findings suggest that curvature measures offer novel insights that could enhance our understanding of the biological systems.

Source: IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

DOI: 10.1109/bibm62325.2024.10822230

Authors: Pietro Hiram Guzzi, Marianna Milano

Institution: Magna Graecia University

Language: English

Topic: Bioinformatics and Genomic Networks

Subfield: Molecular Biology

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: green

Funder: European Commission

Awards: G1909101453, G4508289328