期刊
BIOTECHNIQUES
卷 42, 期 1, 页码 71-75出版社
EATON PUBLISHING CO
DOI: 10.2144/000112257
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资金
- NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCES [R01GM072555] Funding Source: NIH RePORTER
- NIGMS NIH HHS [R01 GM072555-01, R01 GM072555] Funding Source: Medline
Careful visual examination of biological samples is quite powerful, but man), visual analysis tasks done in the laboratory are repetitive, tedious, and subjective. Here we describe the use of the open-source software, CellProfiler (TM), to automatically identify and measure a variety of biological objects in images. The applications demonstrated here include yeast colony counting and classifying, cell microarray annotation, yeast patch assays, mouse tumor quantification, wound healing assays, and tissue topology measurement. The software automatically identifies objects in digital images, counts them, and records a full spectrum of measurements for each object, including location within the image, size, shape, color intensity, degree of correlation between colors, texture (smoothness), and number of neighbors. Small numbers of images can be processed automatically on a personal computer and hundreds of thousands can be analyzed using a computing cluster. This free, easy-to-use software enables biologists to comprehensively and quantitatively address many questions that previously would have required custom programming, thereby facilitating discovery in a variety of biological fields of study
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