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Elsevier, Computer Physics Communications

DOI: 10.1016/j.cpc.2015.12.014

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BASDet: Bayesian approach(es) for structure determination from single molecule X-ray diffraction images

Journal article published in 2016 by Michał Walczak, John Ballantyne, Helmut Grubmüller
This paper was not found in any repository, but could be made available legally by the author.
This paper was not found in any repository, but could be made available legally by the author.

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Data provided by SHERPA/RoMEO

Abstract

X-ray free electron lasers (XFEL) are expected to enable molecular structure determination in single molecule diffraction experiments. In this paper, we describe an implementation of two orthogonal Bayesian approaches, previously introduced in Walczak and Grubmüller (2014), capable of extracting structure information from sparse and noisy diffraction images obtained in these experiments. In the ‘Orientational Bayes’ approach, a ‘seed’ model is used to determine for every recorded diffraction image the underlying molecular orientation. The molecular transform of the irradiated molecule is obtained by aligning and averaging those images in three-dimensional reciprocal space. By contrast, in the ‘Structural Bayes’ approach, a real space structure model is optimized to fit best to an entire set of diffraction images. This approach is used in a Monte Carlo structure refinement procedure. Both presented approaches were implemented in C; previous tests (Walczak and Grubmüller, 2014) suggest that the algorithms are robust against low signal to noise ratios and can deliver high resolution structural information.