3DClusterViSu: 3D clustering analysis of super-resolution microscopy data by 3D Voronoi tessellations | Zendy

Leonid Andronov | Zendy; Jonathan Michalon | Zendy; Khalid Ouararhni | Zendy; Igor Orlov | Zendy; Ali Hamiche | Zendy; JeanLuc Vonesch | Zendy; Bruno P. Klaholz | Zendy

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3DClusterViSu: 3D clustering analysis of super-resolution microscopy data by 3D Voronoi tessellations

Author(s) -

Leonid Andronov,

Jonathan Michalon,

Khalid Ouararhni,

Igor Orlov,

Ali Hamiche,

JeanLuc Vonesch,

Bruno P. Klaholz

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/bty200

Subject(s) - voronoi diagram , cluster analysis , microscopy , computer science , resolution (logic) , data mining , artificial intelligence , geometry , mathematics , optics , physics

Single-molecule localization microscopy (SMLM) can play an important role in integrated structural biology approaches to identify, localize and determine the 3D structure of cellular structures. While many tools exist for the 3D analysis and visualization of crystal or cryo-EM structures little exists for 3D SMLM data, which can provide unique insights but are particularly challenging to analyze in three dimensions especially in a dense cellular context.

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