Duration: 41:00

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Axel Munk Institute for Mathematical Stochastics, Georg August University Goettingen Session Chair Intro: Imaging in Sciences: The Big Data Challenge Timo Aspelmeier Goettingen University and Max Planck Institute for Biophysical Chemistry Statistical Challenges in Superresolution Microscopy In the past few years, the rapid development of optical fluorescence microscopy methods that are able to break the fundamental physical resolution limit of microscopy has led to many new discoveries in biology, biochemistry and biophysics. As these methods advance, however, they are more and more beginning to probe the discrete quantum nature of matter such that the influences of single molecules and individual photons become relevant. This leads to new statistical issues in the data analysis and interpretation of superresolution microscopy data: The strongly non-Gaussian and discrete nature of fluctuations begins to dominate the data and new tools for extracting images with the highest possible resolution and preferably confidence statements are required. This talk will give an introduction to superresolution fluorescence microscopy, show where and why the statistical and computational challenges arise, give an overview over some existing statistical methods to analyse the data and suggest some important future developments to go beyond the current state of the art. This is joint work with Alexander Egner (Laser Lab Goettingen) and Axel Munk (Goettingen University and Max Planck Institute for Biophysical Chemistry).