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

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This unit describes a method for quantifying various cellular parameters (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 purposefully defocused transmission image (sometimes r...

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Detalles Bibliográficos
Autores principales: Chernomoretz, A., Bush, A., Yu, R., Gordon, A., Colman-Lerner, A.
Formato: JOUR
Materias:
animal
article
cell
computer program
confocal microscopy
cytology
fluorescence microscopy
human
image processing
instrumentation
methodology
statistical analysis
yeast
Animals
Cells
Data Interpretation, Statistical
Humans
Image Processing, Computer-Assisted
Microscopy, Confocal
Microscopy, Fluorescence
Software
Yeasts
Acceso en línea:http://hdl.handle.net/20.500.12110/paper_19343647_vChapter14_n_p_Chernomoretz
Aporte de:
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires
Descripción
Sumario:This unit describes a method for quantifying various cellular parameters (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 purposefully defocused transmission image (sometimes referred to as bright-field or BF) is acquired to locate each cell. Fluorescent 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 (Gordon et al., 2007) and data analysis by the statistical programming framework R (R-Development-Team, 2008), which we have supplemented with a package tailored to analyze Cell-ID output. Both programs are open-source software packages. Copyright 2008 by John Wiley & Sons, Inc.

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