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      FISH Finder: a high-throughput tool for analyzing FISH images.

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          Abstract

          Fluorescence in situ hybridization (FISH) is used to study the organization and the positioning of specific DNA sequences within the cell nucleus. Analyzing the data from FISH images is a tedious process that invokes an element of subjectivity. Automated FISH image analysis offers savings in time as well as gaining the benefit of objective data analysis. While several FISH image analysis software tools have been developed, they often use a threshold-based segmentation algorithm for nucleus segmentation. As fluorescence signal intensities can vary significantly from experiment to experiment, from cell to cell, and within a cell, threshold-based segmentation is inflexible and often insufficient for automatic image analysis, leading to additional manual segmentation and potential subjective bias. To overcome these problems, we developed a graphical software tool called FISH Finder to automatically analyze FISH images that vary significantly. By posing the nucleus segmentation as a classification problem, compound Bayesian classifier is employed so that contextual information is utilized, resulting in reliable classification and boundary extraction. This makes it possible to analyze FISH images efficiently and objectively without adjustment of input parameters. Additionally, FISH Finder was designed to analyze the distances between differentially stained FISH probes.

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          Author and article information

          Journal
          Bioinformatics
          Bioinformatics (Oxford, England)
          Oxford University Press (OUP)
          1367-4811
          1367-4803
          Apr 01 2011
          : 27
          : 7
          Affiliations
          [1 ] Department of Biological Science, Florida State University, Tallahassee, FL 32306, USA.
          Article
          btr053
          10.1093/bioinformatics/btr053
          3065689
          21310746
          c8921c98-b1b5-495e-a2e3-12e6affeb608
          History

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