New methods for automated phenotyping of complex cellular behaviors

摘要

Cellular shape change and movement are central to biologic processes that range from normal embryonic development to inflammatory diseases and cancer. Quantitative visual phenotyping of dynamic cellular behaviors creates unique challenges for image capture, analysis and storage. Despite substantial technological advances in molecular biology, biochemistry, genomics and proteomics, investigating cellular processes remains tremendously challenging and labor-intensive. We have developed algorithms and software implementations that allow for fully-automated analysis of experiments designed to investigate a range of cellular and organismal behaviors. By enabling cellular phenotyping, this automated approach creates a unique opportunity for investigators to perform large-scale experiments designed to determine gene function or to screen for small molecule modulators of important cellular behaviors.