The use of connected masks for reconstructing the single particle image from X-ray diffraction data. III. Maximum-likelihood based strategies to select solution of the phase problem
Matematičeskaâ biologiâ i bioinformatika, Tome 13 (2018), pp. t70-t83.

Voir la notice de l'article provenant de la source Math-Net.Ru

The main experimental limitation of biological crystallography is associated with the need to prepare the object under study in the form of a single crystal. New powerful X-ray sources, namely free-electron X-ray lasers, makes it possible to raise the question of the determination of the structure of isolated biological macromolecules and their complexes in practice. An additional advantage of working with isolated particles is the possibility to obtain information about scattering in all directions, and not only in those limited by the Laue-Bragg diffraction conditions. This significantly facilitates the solution of the phase problem of X-ray diffraction analysis. This paper is devoted to two lines of development of the method for solving the phase problem, proposed earlier by the authors, which is based on the random scanning of the configuration space of potential solutions of the phase problem. The paper suggests a new criterion for the selection of "candidates" for solving the phase problem in the process of scanning. It involves the maximization of statistical likelihood, and its effectiveness is shown in test calculations. The second line concerns the choice of the optimal scanning strategy. It is shown that the gradual expansion of the set of experimental data used in the work allows obtaining solutions of a higher quality than those obtained with all available data included into the work simultaneously from the beginning.
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N. L. Lunina; T. E. Petrova; A. G. Urzhumtsev; V. Y. Lunin. The use of connected masks for reconstructing the single particle image from X-ray diffraction data. III. Maximum-likelihood based strategies to select solution of the phase problem. Matematičeskaâ biologiâ i bioinformatika, Tome 13 (2018), pp. t70-t83. http://geodesic.mathdoc.fr/item/MBB_2018_13_a5/

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