期刊
JOURNAL OF BIOMOLECULAR SCREENING
卷 17, 期 2, 页码 266-274出版社
SAGE PUBLICATIONS INC
DOI: 10.1177/1087057111420292
关键词
cell-based assays; high-content screening; image analysis; microscopy
资金
- National Institutes of Health [R01 GM089652, U54 HG005032, RL1 HG004671, RL1 CA133834, RL1 GM084437, UL1 RR024924]
- Direct For Biological Sciences
- Div Of Biological Infrastructure [1119830] Funding Source: National Science Foundation
Automated microscopes have enabled the unprecedented collection of images at a rate that precludes visual inspection. Automated image analysis is required to identify interesting samples and extract quantitative information for high-content screening (HCS). However, researchers are impeded by the lack of metrics and software tools to identify image-based aberrations that pollute data, limiting experiment quality. The authors have developed and validated approaches to identify those image acquisition artifacts that prevent optimal extraction of knowledge from high-content microscopy experiments. They have implemented these as a versatile, open-source toolbox of algorithms and metrics readily usable by biologists to improve data quality in a wide variety of biological experiments.
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