Skopi: a simulation package for diffractive imaging of noncrystalline biomolecules

Abstract

X-ray free-electron lasers (XFELs) have the ability to produce ultra-bright femtosecond X-ray pulses for coherent diffraction imaging of biomolecules. While the development of methods and algorithms for macromolecular crystallography is now mature, XFEL experiments involving aerosolized or solvated biomolecular samples offer new challenges in terms of both experimental design and data processing. Skopi is a simulation package that can generate single-hit diffraction images for reconstruction algorithms, multi-hit diffraction images of aggregated particles for training machine learning classifiers using labeled data, diffraction images of randomly distributed particles for fluctuation X-ray scattering algorithms, and diffraction images of reference and target particles for holographic reconstruction algorithms. Skopi is a resource to aid feasibility studies and advance the development of algorithms for noncrystalline experiments at XFEL facilities.

Single particle imaging of biological specimens

“…A successful reconstruction of SPI from noisy and incomplete experimental diffraction patterns [44][45] need a series of complex methods of data processing and hence extremely depends on highly synthetic interdisciplinary expertise. To achieve atomic resolution and femtosecond temporal resolution, the current computational requirements of SPI have led researchers to explore the use of modern data analytical techniques to solve problems in image reconstruction [46][47][48][49][50] . Machine Learning methods and in particular deep learning models can provide promising tools for tackling diverse challenges of SPI, such as hit-finding, phase retrieval, orientation recovery and image reconstruction.…”

SpeckleNN: a unified embedding for real-time speckle pattern classification in X-ray single-particle imaging with limited labeled examples

“…The beam profile employed in the simulation has a radius of 0.5 mm and a photon energy of 1.66 keV, and contains 10 12 photons per pulse. We simulated all speckle patterns using skopi (Peck et al, 2022) on a square detector with the dimensions 172 Â 172 pixels. To replicate the conditions similar to real experiments, we first applied a 6 Â 8 pixel binary mask mimicking a beam stop at the center and another 172 Â 4 pixel binary mask resembling a gap dividing a detector in middle.…”

SpeckleNN: A unified embedding for real-time speckle pattern classification in X-ray single-particle imaging with limited labeled examples

“…The beam profile employed in the simulation has a radius of 0.5 µm and a photon energy of 1.66 keV , and contains 10 12 photons per pulse. We simulated all speckle patterns using skopi [Peck et al, 2022] on a square detector with a dimension of 172 × 172 pixels. To replicate the conditions similar to real experiments, we firstly applied a 6 × 8 pixel binary mask mimicking a beam stop at the center and another 172 × 4 pixel binary mask resembling a gap dividing a detector in the middle.…”