Tight basis cycle representatives for persistent homology of large biological data sets.

ABSTRACT: Persistent homology (PH) is a popular tool for topological data analysis that has found applications across diverse areas of research. It provides a rigorous method to compute robust topological features in discrete experimental observations that often contain various sources of uncertainties. Although powerful in theory, PH suffers from high computation cost that precludes its application to large data sets. Additionally, most analyses using PH are limited to computing the existence of nontrivial features. Precise localization of these features is not generally attempted because, by definition, localized representations are not unique and because of even higher computation cost. Such a precise location is a sine qua non for determining functional significance, especially in biological app

SUBMITTER: Aggarwal M 

PROVIDER: S-EPMC10275456 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature