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Related Experiment Video

Updated: Jul 11, 2025

3D Scanning Technology Bridging Microcircuits and Macroscale Brain Images in 3D Novel Embedding Overlapping Protocol

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Multilayer network alignment based on topological assessment via embeddings.

Pietro Cinaglia¹, Marianna Milano², Mario Cannataro³

¹Department of Health Sciences, Magna Graecia University, 88100, Catanzaro, Italy. cinaglia@unicz.it.

BMC Bioinformatics

|November 6, 2023

Summary

This summary is machine-generated.

DANTEml is a new software tool for network alignment (NA) of multilayer networks. It significantly outperforms existing methods in aligning both synthetic and real-world networks, offering reliable and statistically validated node mappings.

Keywords:

Embeddings Multilayer networks Network Alignment Network analysis Topological similarity

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Modeling the Functional Network for Spatial Navigation in the Human Brain

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Published on: October 13, 2023

Area of Science:

Computational Biology
Network Science
Data Mining

Background:

Multilayer networks model complex systems with interactions distributed across layers.
Network alignment (NA) maps nodes between networks to preserve topological similarities, enabling knowledge transfer.
Existing NA methods may not fully leverage the rich information within multilayer network structures.

Purpose of the Study:

Introduce DANTEml, a novel software tool for Pairwise Global Network Alignment (PGNA) of multilayer networks.
Evaluate DANTEml's performance and reliability in aligning complex network data.
Provide a user-friendly tool for researchers working with multilayer network analysis.

Main Methods:

DANTEml employs a topological assessment approach using node embeddings from two multilayer networks.
It computes a similarity matrix to identify and map topologically similar nodes.
The software offers a command-line interface with a guided mode for parameter input.

Main Results:

DANTEml significantly outperformed a non-multilayer aware method by up to 1193.62% on synthetic data and 4008.75% on real data.
It also showed substantial improvement over a temporal NA method, by 25.88% and 111.72% respectively.
Statistical assessment confirmed the significance and reliability of the node mappings generated by DANTEml.

Conclusions:

DANTEml is an effective software tool for PGNA of multilayer networks.
It provides statistically validated and reliable node mappings for both synthetic and real-world networks.
The tool demonstrates high performance and reliability in complex network alignment tasks.