Article

jHoles: A Tool for Understanding Biological Complex Networks via Clique Weight Rank Persistent Homology

2014-07-01

Abstract excerpt

Complex networks equipped with topological data analysis are one of the promising tools in the study of biological systems (e.g. evolution dynamics, brain correlation, breast cancer diagnosis, etc…). In this paper, we propose jHoles, a new version of Holes, an algorithms based on persistent homology for studying the connectivity features of complex networks. jHoles fills the lack of an efficient implementation of...

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Literature Corpus work: c26fd98c-2d23-551e-abb4-8ac3d62b9f56
DOI: 10.1016/j.entcs.2014.06.011

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