Local statistics allow quantification of cell-to-cell variability from high-throughput microscope images
Quantifying variability in protein expression is a major goal of systems biology and cell-to-cell variability in subcellular localization pattern has not been systematically quantified. We define a local measure to quantify cell-to-cell variability in high-throughput microscope images and show that...
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Veröffentlicht in: | Bioinformatics 2015-03, Vol.31 (6), p.940-947 |
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Hauptverfasser: | , , , |
Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Quantifying variability in protein expression is a major goal of systems biology and cell-to-cell variability in subcellular localization pattern has not been systematically quantified.
We define a local measure to quantify cell-to-cell variability in high-throughput microscope images and show that it allows comparable measures of variability for proteins with diverse subcellular localizations. We systematically estimate cell-to-cell variability in the yeast GFP collection and identify examples of proteins that show cell-to-cell variability in their subcellular localization.
Automated image analysis methods can be used to quantify cell-to-cell variability in microscope images. |
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ISSN: | 1367-4803 1367-4811 1460-2059 |
DOI: | 10.1093/bioinformatics/btu759 |