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Visualisation of 100-dimensional Image Data

Spreker: Peter Serocka

A new challenge to data visualization has arisen from a recent laboratory technique that is capable of imaging the expressions of upto 100 biomedical relevant molecule types in a single tissue probe, termed the Toponome. Aiming at deciphering the biochemical interactions of the molecules, and thus their biological functions as well their roles in diseases, one finds that current methods of image analysis are not fully suited for this new quality of high-dimensional image data. We present and demonstrate a novel framework for interactive real-time visualization, making use of standard graphics acceleration hardware. It is based on quickly computing and visualizing similarities in the 100-dimensional space of molecule expression. We discuss how navigating through highdimensional data spaces by interactively mapping levels of similarity can evolve into a perceptually demanding, yet useful paradigm for aproaching Toponome data.

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