ArticleScientific reports2021
Homological scaffold via minimal homology bases.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Chordless cycle filtrations for dimensionality detection in complex networks via topological data analysis.Nature communications · 2026Article
- Node persistence from topological data analysis reveals changes in brain functional connectivity.Patterns (New York, N.Y.) · 2026Article
- Interaction of Functional Brain Networks Is Associated With k-Clique Percolation in the Human Structural Connectome.Human brain mapping · 2025Article
- Article
- Simple topological task-based functional connectivity features predict longitudinal behavioral change of fluid reasoning in the RANN cohort.NeuroImage · 2023Article
- Tight basis cycle representatives for persistent homology of large biological data sets.PLoS computational biology · 2023Article
- Simplicial and topological descriptions of human brain dynamics.Network neuroscience (Cambridge, Mass.) · 2021Article
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The homological scaffold leverages persistent homology to construct a topologically sound summary of a weighted network. However, its crucial dependency on the choice of representative cycles hinders the ability to trace back global features onto individual network components, unless one provides a principled way to make such a choice. In this paper, we apply recent advances in the computation of minimal homology bases to introduce a quasi-canonical version of the scaffold, called minimal, and employ it to analyze data both real and in silico. At the same time, we verify that, statistically, the standard scaffold is a good proxy of the minimal one for sufficiently complex networks.
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Registered trials
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