Journal
JOURNAL OF BIOMOLECULAR SCREENING
Volume 12, Issue 4, Pages 490-496Publisher
SAGE PUBLICATIONS INC
DOI: 10.1177/1087057107300707
Keywords
high-content screening; support vector machine; mitosis; cell cycle
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High-content screening studies of mitotic checkpoints are important for identifying cancer targets and developing novel cancer-specific therapies. A crucial step in such a study is to determine the stage of cell cycle. Due to the overwhelming number of cells assayed in a high-content screening experiment and the multiple factors that need to be taken into consideration for accurate determination of mitotic subphases, an automated classifier is necessary. In this article, the authors describe in detail a support vector machine (SVM) classifier that they have implemented to recognize various mitotic subphases. In contrast to previous studies to recognize subcellular patterns, they used only low-resolution cell images and a few parameters that can be calculated inexpensively with off-the-shelf image-processing software. The performance of the SVM was evaluated with a cross-validation method and was shown to be comparable to that of a human expert.
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