Using CellProfiler for Automatic Identification and Measurement of Biological Objects in Images. Issue 1 (5th January 2015)

• Record Type: Journal Article
• Authors: Bray, Mark‐Anthony; Vokes, Martha S.; Carpenter, Anne E.
• Editors: Ausubel, Frederick M.; Brent, Roger; Kingston, Robert E.; Moore, David D.; Seidman, J.G.; Smith, John A.; Struhl, Kevin
• Is Part Of: Current protocols in molecular biology. Volume 109:Issue 1(2015)
• Page Start: 14.17.1
• Page End: 14.17.13
• Publication Date: 2015-01-05
• Subjects: automatic image analysis -- yeast colonies -- open‐source software -- phenotypes -- colony counting; Molecular biology -- Technique -- Periodicals; Molecular biology -- Laboratory manuals; Molecular Biology -- methods; Biologie moléculaire -- Technique; Biologie moléculaire -- Manuels de laboratoire; Molecular biology; Molecular biology -- Technique; Laboratory Manual; Electronic reference sources; Laboratory manuals; 572.8028
• DOI: 10.1002/0471142727.mb1417s109
• Languages: English
• ISSNs: 1934-3639

Abstract

Abstract: Visual analysis is required to perform many biological experiments, from counting colonies to measuring the size or fluorescence intensity of individual cells or organisms. This unit outlines the use of CellProfiler, a free, open‐source image analysis tool that extracts quantitative information from biological images. It includes a step‐by‐step protocol for automated analysis of the number, color, and size of yeast colonies growing on agar plates, but the methods can be adapted to identify and measure many other types of objects in images. The flexibility of the software allows experimenters to create pipelines of adjustable modules to fit different biological experiments and to generate accurate measurements from dozens or even hundreds of thousands of images. © 2015 by John Wiley & Sons, Inc.