Analysis of High-Dimensional Data from Cell Imaging
Genedata is actively pursuing research and development of new methods to leverage the rich information contained in high content screens. High Content Screening (HCS) has made tremendous advances through improvements in key elements, such as reliable and more affordable high content readers, improved cell and liquid handling, automation of data acquisition, and improved image analysis. HCS is becoming routine in cell-based screening, especially where hardly tractable targets or assessment based on phenotypic response patterns are important, in siRNA screening for fundamental research into cellular pathways or target validation, in compound profiling against primary cell lines, and in predictive toxicology. With its broader application, HCS is also being scaled up to higher throughput levels.
The current challenge is the systematic analysis of the resulting high-dimensional and large-scale data sets to a biologically relevant purpose. Researchers desire a system that can scale to smoothly process tens to hundreds of millions of data points while leveraging the complex information contained in HCS data. A scalable, flexible software solution designed for all of these application areas now holds the key to realizing the full potential for HCS across an enterprise
Genedata is working on applying multivariate statistical algorithms adapted to HCS data, presenting results in visualizers dedicated to the scientific questions in HCS, and incorporating them both into the proven scalable data management solution Genedata Screener®. This will enable HCS scientists to benefit from an enterprise framework for efficient data analysis and scalable management of their HCS experiments.
Please check back for the latest developments in HCS at Genedata or contact us to receive more information.