The development of effective novel therapeutic agents faces many significant challenges, such as demonstrating that a candidate target plays a critical role in disease progression. RNA interference (RNAi) has proven to be a robust and highly scalable technology, and as such, has become an essential method for studying targets in many disease models. High-content screening (HCS) is a platform for quantitatively measuring cellular features such as transcription factor localization. This is a more powerful method of measuring signal transduction than reporter assays because the image-based data of HCS can eliminate many sources of assay artifacts, and the associated statistical tools are highly effective. While it appears obvious that convergence of technologies is required to establish RNAi screening assays in HCS formats, some challenges arise when combining the approaches. However, combining RNAi and HCS provides significant and unique advantages to a target validation program.
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