Literature DB >> 23026908

Using Cell-ID 1.4 with R for microscope-based cytometry.

Alan Bush1, Ariel Chernomoretz, Richard Yu, Andrew Gordon, Alejandro Colman-Lerner.   

Abstract

This unit describes a method for quantifying various cellular features (e.g., volume, total and subcellular fluorescence localization) from sets of microscope images of individual cells. It includes procedures for tracking cells over time. One purposely defocused transmission image (sometimes referred to as bright-field or BF) is acquired to segment the image and locate each cell. Fluorescence images (one for each of the color channels to be analyzed) are then acquired by conventional wide-field epifluorescence or confocal microscopy. This method uses the image-processing capabilities of Cell-ID and data analysis by the statistical programming framework R, which is supplemented with a package of routines for analyzing Cell-ID output. Both Cell-ID and the analysis package are open-source. 2012 by John Wiley & Sons, Inc.

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Year:  2012        PMID: 23026908      PMCID: PMC3485637          DOI: 10.1002/0471142727.mb1418s100

Source DB:  PubMed          Journal:  Curr Protoc Mol Biol        ISSN: 1934-3647


  13 in total

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9.  The Open Microscopy Environment (OME) Data Model and XML file: open tools for informatics and quantitative analysis in biological imaging.

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10.  Negative feedback that improves information transmission in yeast signalling.

Authors:  Richard C Yu; C Gustavo Pesce; Alejandro Colman-Lerner; Larry Lok; David Pincus; Eduard Serra; Mark Holl; Kirsten Benjamin; Andrew Gordon; Roger Brent
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  4 in total

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