Assessing uncertainties in x-ray single-particle three-dimensional reconstruction

Jing Liu, Stefan Engblom, and Carl Nettelblad
Phys. Rev. E 98, 013303 – Published 5 July 2018

Abstract

Modern technology for producing extremely bright and coherent x-ray laser pulses provides the possibility to acquire a large number of diffraction patterns from individual biological nanoparticles, including proteins, viruses, and DNA. These two-dimensional diffraction patterns can be practically reconstructed and retrieved down to a resolution of a few angstroms. In principle, a sufficiently large collection of diffraction patterns will contain the required information for a full three-dimensional reconstruction of the biomolecule. The computational methodology for this reconstruction task is still under development and highly resolved reconstructions have not yet been produced. We analyze the expansion-maximization-compression scheme, the current state of the art approach for this very challenging application, by isolating different sources of resolution-limiting factors. Through numerical experiments on synthetic data we evaluate their respective impact. We reach conclusions of relevance for handling actual experimental data, and we also point out certain improvements to the underlying estimation algorithm. We also introduce a practically applicable computational methodology in the form of bootstrap procedures for assessing reconstruction uncertainty in the real data case. We evaluate the sharpness of this approach and argue that this type of procedure will be critical in the near future when handling the increasing amount of data.

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  • Received 18 September 2017
  • Revised 23 February 2018

DOI:https://doi.org/10.1103/PhysRevE.98.013303

©2018 American Physical Society

Physics Subject Headings (PhySH)

Interdisciplinary PhysicsPhysics of Living SystemsAccelerators & Beams

Authors & Affiliations

Jing Liu* and Stefan Engblom

  • Division of Scientific Computing, Department of Information Technology, Uppsala University, SE-751 05 Uppsala, Sweden

Carl Nettelblad

  • Science for Life Laboratory, Division of Scientific Computing, Department of Information Technology, Uppsala University, SE-751 05 Uppsala, Sweden

  • *Jing Liu is also at the Laboratory of Molecular Biophysics, Department of Cell and Molecular Biology, Uppsala University, SE-751 24 Uppsala, Sweden; jing.liu@it.uu.se
  • Corresponding author: stefane@it.uu.se
  • carl.nettelblad@it.uu.se

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Issue

Vol. 98, Iss. 1 — July 2018

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