Unraveling the Thousand Word Picture: An Introduction to Super-Resolution Data Analysis

Antony Lee, Konstantinos Tsekouras, Christopher Calderon, Carlos Bustamante, Steve Presse

Research output: Contribution to journalReview article

23 Citations (Scopus)

Abstract

Super-resolution microscopy provides direct insight into fundamental biological processes occurring at length scales smaller than light's diffraction limit. The analysis of data at such scales has brought statistical and machine learning methods into the mainstream. Here we provide a survey of data analysis methods starting from an overview of basic statistical techniques underlying the analysis of super-resolution and, more broadly, imaging data. We subsequently break down the analysis of super-resolution data into four problems: the localization problem, the counting problem, the linking problem, and what we've termed the interpretation problem.

Original languageEnglish (US)
Pages (from-to)7276-7330
Number of pages55
JournalChemical Reviews
Volume117
Issue number11
DOIs
StatePublished - Jun 14 2017

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Learning systems
Microscopic examination
Diffraction
Imaging techniques

ASJC Scopus subject areas

  • Chemistry(all)

Cite this

Unraveling the Thousand Word Picture : An Introduction to Super-Resolution Data Analysis. / Lee, Antony; Tsekouras, Konstantinos; Calderon, Christopher; Bustamante, Carlos; Presse, Steve.

In: Chemical Reviews, Vol. 117, No. 11, 14.06.2017, p. 7276-7330.

Research output: Contribution to journalReview article

Lee, Antony ; Tsekouras, Konstantinos ; Calderon, Christopher ; Bustamante, Carlos ; Presse, Steve. / Unraveling the Thousand Word Picture : An Introduction to Super-Resolution Data Analysis. In: Chemical Reviews. 2017 ; Vol. 117, No. 11. pp. 7276-7330.
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