Solving the 3-D Puzzle of Rotation Assignment in Single Particle Cryo-Electron Microscopy

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Single particle cryo-electron microscopy (EM) recently joined X-ray crystallography and nuclear magnetic resonance spectroscopy as a high-resolution structural method for biological macromolecules. In single particle cryo-EM, the 3-D structure needs to be determined from many noisy 2-D projection images of individual, ideally identical frozen-hydrated macromolecules whose orientations and positions are random and unknown.

This lecture will explore algorithms for estimating the unknown pose parameters. The main focus will be on algorithms that are based on semidefinite programming relaxations that can be viewed as extensions to existing approximation algorithms to max-cut and unique games, two fundamental problems in theoretical computer science.

 

About the Speaker

Amit Singer is a professor of mathematics and a member of the executive committee of the Program in Applied and Computational Mathematics (PACM) at Princeton University. He joined Princeton as an assistant professor in 2008. From 2005 to 2008 he was a Gibbs Assistant Professor in Applied Mathematics at the Department of Mathematics, Yale University.

Singer received his B.Sc. degree in Physics and Mathematics and his Ph.D. degree in applied mathematics from Tel Aviv University, Israel, in 1997 and 2005, respectively. He was awarded the Moore Investigator in Data-Driven Discovery Award (2014), the Simons Investigator Award (2012), the Presidential Early Career Award for Scientists and Engineers (2010), the Alfred P. Sloan Research Fellowship (2010) and the Haim Nessyahu Prize in Mathematics (2007). His current research in applied mathematics focuses on theoretical and computational aspects of data science, and on developing computational methods for structural biology.

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