Image-based profiling uses hundreds of measurements of cell morphology from images.
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Samples with similar phenotypes are grouped based on this unbiased, quantitative data.
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Profiling can enrich compound libraries and identify potential drugs and mechanisms.
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Profiling can functionally characterize genes, disease alleles, and disease states.
A dramatic shift has occurred in how biologists use microscopy images. Whether experiments are small-scale or high-throughput, automatically quantifying biological properties in images is now widespread. We see yet another revolution under way: a transition towards using automated image analysis to not only identify phenotypes a biologist specifically seeks to measure (‘screening’) but also as an unbiased and sensitive tool to capture a wide variety of subtle features of cell (or organism) state (‘profiling’). Mapping similarities among samples using image-based (morphological) profiling has tremendous potential to transform drug discovery, functional genomics, and basic biological research. Applications include target identification, lead hopping, library enrichment, functionally annotating genes/alleles, and identifying small molecule modulators of gene activity and disease-specific phenotypes.