Quantification of fibrous spatial point patterns from single-molecule localization microscopy (SMLM) data | Zendy

Ruby Peters | Zendy; Marta Benthem Muñiz | Zendy; Juliette Griffié | Zendy; David J. Williamson | Zendy; George W. Ashdown | Zendy; Christian D. Lorenz | Zendy; Dylan M. Owen | Zendy

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Quantification of fibrous spatial point patterns from single-molecule localization microscopy (SMLM) data

Author(s) -

Ruby Peters,

Marta Benthem Muñiz,

Juliette Griffié,

David J. Williamson,

George W. Ashdown,

Christian D. Lorenz,

Dylan M. Owen

Publication year - 2017

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/btx026

Subject(s) - computer science , context (archaeology) , cluster analysis , point (geometry) , artificial intelligence , matlab , microscopy , pattern recognition (psychology) , data mining , physics , optics , mathematics , geometry , biology , paleontology , operating system

Unlike conventional microscopy which produces pixelated images, SMLM produces data in the form of a list of localization coordinates-a spatial point pattern (SPP). Often, such SPPs are analyzed using cluster analysis algorithms to quantify molecular clustering within, for example, the plasma membrane. While SMLM cluster analysis is now well developed, techniques for analyzing fibrous structures remain poorly explored.

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