jHoles: a tool for understanding biological complex networks via clique weight rank persistent homology

DOI10.1016/j.entcs.2014.06.011zbMath1337.92073OpenAlexW1972488821WikidataQ113317865 ScholiaQ113317865MaRDI QIDQ281275

Matteo Rucco, Giovanni Petri, Jacopo Binchi, Emanuela Merelli, Francesco Vaccarino

Publication date: 10 May 2016

Full work available at URL: https://doi.org/10.1016/j.entcs.2014.06.011

zbMATH Keywords

Betti numbercomplex networksbiological networkscomputational topologytumor diagnosis

Mathematics Subject Classification ID

Small world graphs, complex networks (graph-theoretic aspects) (05C82) PL-topology (57Q99) Systems biology, networks (92C42)

Related Items (12)

Persistent Homology: A Topological Tool for Higher-Interaction Systems ⋮ Persistent homology and string vacua ⋮ Obey validity limits of data-driven models through topological data analysis and one-class classification ⋮ Catching homologies by geometric entropy ⋮ Aspects of topological approaches for data science ⋮ Multiscale persistent functions for biomolecular structure characterization ⋮ Geometric Metrics for Topological Representations ⋮ Ripser: efficient computation of Vietoris-Rips persistence barcodes ⋮ jHoles ⋮ Simplicial complexes and complex systems ⋮ BPS spectra, barcodes and walls ⋮ Biomolecular topology: modelling and analysis

Uses Software

• Matlab
• JGraphT
• javaPlex
• Holes
• KONECT

Cites Work

• Unnamed Item
• Computing persistent homology
• javaPlex: A Research Software Package for Persistent (Co)Homology
• Dualities in persistent (co)homology
• Topology and data
• A New Algorithm for Generating All the Maximal Independent Sets
• Topology for Computing
• Topology of viral evolution
• On cliques in graphs

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