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Recent Computational Approaches in Cryogenic Electron Microscopy: Towards Formalizing a Data-Driven Cycle
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Reporter:
Chenglong Bao, Associate Professor, Tsinghua University
Inviter:
Xin Liu, Professor
Subject:
Recent Computational Approaches in Cryogenic Electron Microscopy: Towards Formalizing a Data-Driven Cycle
Time and place:
11:00-12:00 March 25(Tuesday), N202
Abstract:

Cryogenic Electron Microscopy (cryo-EM) is a powerful imaging technique for determining the high-resolution structures of biological macromolecules. However, it still faces several challenges, including an extremely low signal-to-noise ratio, heterogeneity, and preferred orientation. In this talk, we will present our computational approaches to addressing these challenges, covering the entire cryo-EM data processing pipeline. Specifically, we will discuss methods for data evaluation, processing, post-processing, and model building, combining mathematical models and unsupervised deep learning approaches. We will also present experimental results from biological laboratories to demonstrate the effectiveness of the proposed algorithms.