ArticleScientific reports2019
Comparing methods for comparing networks.
Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 71 papers.
What it found
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Who cites it
71 citing papers in PubMed.
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- Environmental and host- and parasite-associated drivers of the flea-mammal interaction network structure differ between biogeographic realms.Parasitology research · 2025Article
- Combinative Protein Expression of Immediate Early Genes c-Fos, Arc, and Npas4 Along Aversive and Appetitive Experience-Related Neural Networks.Hippocampus · 2025Article
- tna: An R Package for Transition Network Analysis.Applied psychological measurement · 2025Article
- From network biology to immunity: potential longitudinal biomarkers for targeting the network topology of the HIV reservoir.Journal of translational medicine · 2025Review
- An egonet based approach to effective weighted network comparison.Scientific reports · 2025Article
- Analyzing the accessibility of Rome's healthcare services via public transportation: a complex network approach.Scientific reports · 2025Article
- Computational memory capacity predicts aging and cognitive decline.Nature communications · 2025Article
- How Are TBI Symptoms Interconnected? A Network Analysis Approach.Brain and behavior · 2025Article
- The interplay of sex and genotype in disease associations: a comprehensive network analysis in the UK Biobank.Human genomics · 2025Article
- A Selective Review of Network Analysis Methods for Gene Expression Data.Methods in molecular biology (Clifton, N.J.) · 2025Review
- Graph Laplacian Learning with Exponential Family Noise.IEEE transactions on signal and information processing over networks · 2025Article
- Publication-driven consistency in food web structures: Implications for comparative ecology.Ecology · 2025Article
11 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
With the impressive growth of available data and the flexibility of network modelling, the problem of devising effective quantitative methods for the comparison of networks arises. Plenty of such methods have been designed to accomplish this task: most of them deal with undirected and unweighted networks only, but a few are capable of handling directed and/or weighted networks too, thus properly exploiting richer information. In this work, we contribute to the effort of comparing the different methods for comparing networks and providing a guide for the selection of an appropriate one. First, we review and classify a collection of network comparison methods, highlighting the criteria they are based on and their advantages and drawbacks. The set includes methods requiring known node-correspondence, such as DeltaCon and Cut Distance, as well as methods not requiring a priori known node-correspondence, such as alignment-based, graphlet-based, and spectral methods, and the recently proposed Portrait Divergence and NetLSD. We test the above methods on synthetic networks and we assess their usability and the meaningfulness of the results they provide. Finally, we apply the methods to two real-world datasets, the European Air Transportation Network and the FAO Trade Network, in order to discuss the results that can be drawn from this type of analysis.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.