Our Columbus™ Image Data Storage and Analysis system is an instrument agnostic image analysis and management platform.
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Image storage and analysis for all your high content imaging data.
High Content Screening experiments generate massive amounts of image data that needs to be accessed quickly, analyzed and re-analyzed, shared with colleagues and stored safely. With the trend towards using more complex, physiologically relevant disease models, more sophisticated tools are required to numerically describe cells and their phenotypes comprehensively. The Columbus system is the only image data storage and analysis system that supports a wide range of file formats, allowing visualization of images, regardless of their origin.
A powerful new way to access, store and explore
Image Analysis for Phenotypic Screening
|Version Number||Powerful image analysis capabilities with highly flexible and easy to use building blocks to analyze simple and complex phenotypes of cells.|
This study illustrates the power of high content automated image analysis to quantify complex organelle morphologies, using the Opera system and the texture and STAR features of the Columbus system.
There has been a lot of buzz around artificial intelligence, machine learning and deep learning. Is the reality living up to the hype?
In the world of cellular imaging and its application to drug discovery, there is evidence of real progress against some of the critical challenges facing scientists using these technologies.
In this white paper, you will learn about:
Researchers are increasingly looking to 3D cell cultures, microtissues, and organoids to bridge the gap between 2D cell cultures and in vivo animal models. This whitepaper documents a streamlined procedure for getting the most information, as quickly as possible, using solutions from PerkinElmer.