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Automated classification of multicolored rolling circle products in dual‐channel wide‐field fluorescence microscopy
Author(s) -
Gavrilovic Milan,
Weibrecht Irene,
Conze Tim,
Söderberg Ola,
Wählby Carolina
Publication year - 2011
Publication title -
cytometry part a
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.316
H-Index - 90
eISSN - 1552-4930
pISSN - 1552-4922
DOI - 10.1002/cyto.a.21087
Subject(s) - thresholding , computer science , microscopy , artificial intelligence , fluorescence , rolling circle replication , pattern recognition (psychology) , fluorescence microscope , channel (broadcasting) , computer vision , biological system , optics , image (mathematics) , physics , nuclear magnetic resonance , biology , computer network , polymerase , enzyme
Specific single‐molecule detection opens new possibilities in genomics and proteomics, and automated image analysis is needed for accurate quantification. This work presents image analysis methods for the detection and classification of single molecules and single‐molecule interactions detected using padlock probes or proximity ligation. We use simple, widespread, and cost‐efficient wide‐field microscopy and increase detection multiplexity by labeling detection events with combinations of fluorescence dyes. The mathematical model presented herein can classify the resulting point‐like signals in dual‐channel images by spectral angles without discriminating between low and high intensity. We evaluate the methods on experiments with known signal classes and compare to classical classification algorithms based on intensity thresholding. We also demonstrate how the methods can be used as tools to evaluate biochemical protocols by measuring detection probe quality and accuracy. Finally, the method is used to evaluate single‐molecule detection events in situ . © 2011 International Society for Advancement of Cytometry

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