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CellCognition: time-resolved phenotype annotation in high-throughput live cell imaging


Held, M; Schmitz, M H A; Fischer, B; Walter, T; Neumann, B; Olma, M H; Peter, M; Ellenberg, J; Gerlich, D W (2010). CellCognition: time-resolved phenotype annotation in high-throughput live cell imaging. Nature Methods, 7(9):747-754.

Abstract

Fluorescence time-lapse imaging has become a powerful tool to investigate complex dynamic processes such as cell division or intracellular trafficking. Automated microscopes generate time-resolved imaging data at high throughput, yet tools for quantification of large-scale movie data are largely missing. Here we present CellCognition, a computational framework to annotate complex cellular dynamics. We developed a machine-learning method that combines state-of-the-art classification with hidden Markov modeling for annotation of the progression through morphologically distinct biological states. Incorporation of time information into the annotation scheme was essential to suppress classification noise at state transitions and confusion between different functional states with similar morphology. We demonstrate generic applicability in different assays and perturbation conditions, including a candidate-based RNA interference screen for regulators of mitotic exit in human cells. CellCognition is published as open source software, enabling live-cell imaging-based screening with assays that directly score cellular dynamics.

Abstract

Fluorescence time-lapse imaging has become a powerful tool to investigate complex dynamic processes such as cell division or intracellular trafficking. Automated microscopes generate time-resolved imaging data at high throughput, yet tools for quantification of large-scale movie data are largely missing. Here we present CellCognition, a computational framework to annotate complex cellular dynamics. We developed a machine-learning method that combines state-of-the-art classification with hidden Markov modeling for annotation of the progression through morphologically distinct biological states. Incorporation of time information into the annotation scheme was essential to suppress classification noise at state transitions and confusion between different functional states with similar morphology. We demonstrate generic applicability in different assays and perturbation conditions, including a candidate-based RNA interference screen for regulators of mitotic exit in human cells. CellCognition is published as open source software, enabling live-cell imaging-based screening with assays that directly score cellular dynamics.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > Institute for Regenerative Medicine (IREM)
Dewey Decimal Classification:610 Medicine & health
Language:English
Date:2010
Deposited On:17 Jan 2011 18:37
Last Modified:16 Aug 2016 10:13
Publisher:Nature Publishing Group
ISSN:1548-7091
Publisher DOI:https://doi.org/10.1038/nmeth.1486
PubMed ID:20693996

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