The Rényi divergence enables accurate and precise cluster analysis for localization microscopy | Zendy

Adela Staszowska | Zendy; Patrick FoxRoberts | Zendy; L Hirvonen | Zendy; Christopher J. Peddie | Zendy; Lucy Collinson | Zendy; Gareth E. Jones | Zendy; Susan Cox | Zendy

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The Rényi divergence enables accurate and precise cluster analysis for localization microscopy

Author(s) -

Adela Staszowska,

Patrick FoxRoberts,

L Hirvonen,

Christopher J. Peddie,

Lucy Collinson,

Gareth E. Jones,

Susan Cox

Publication year - 2018

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/bty403

Subject(s) - cluster (spacecraft) , divergence (linguistics) , computer science , microscopy , artificial intelligence , computational biology , biology , physics , optics , programming language , philosophy , linguistics

Clustering analysis is a key technique for quantitatively characterizing structures in localization microscopy images. To build up accurate information about biological structures, it is critical that the quantification is both accurate (close to the ground truth) and precise (has small scatter and is reproducible).

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