Toward automated denoising of single molecular Förster resonance energy transfer data

Hao Chih Lee, Bo Lin Lin, Wei Hau Chang, I. Ping Tu

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

A wide-field two-channel fluorescence microscope is a powerful tool as it allows for the study of conformation dynamics of hundreds to thousands of immobilized single molecules by Förster resonance energy transfer (FRET) signals. To date, the data reduction from a movie to a final set containing meaningful single-molecule FRET (smFRET) traces involves human inspection and intervention at several critical steps, greatly hampering the efficiency at the post-imaging stage. To facilitate the data reduction from smFRET movies to smFRET traces and to address the noise-limited issues, we developed a statistical denoising system toward fully automated processing. This data reduction system has embedded several novel approaches. First, as to background subtraction, high-order singular value decomposition (HOSVD) method is employed to extract spatial and temporal features. Second, to register and map the two color channels, the spots representing bleeding through the donor channel to the acceptor channel are used. Finally, correlation analysis and likelihood ratio statistic for the change point detection (CPD) are developed to study the two channels simultaneously, resolve FRET states, and report the dwelling time of each state. The performance of our method has been checked using both simulation and real data.

Original languageEnglish
Article number011007
JournalJournal of Biomedical Optics
Volume17
Issue number1
DOIs
StatePublished - Jan 2012
Externally publishedYes

Keywords

  • Change point detection
  • Denoising
  • Dimension reduction
  • Fluorescence resonance energy transfer
  • Molecular imaging
  • Total internal reflection

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