The Lawrence Berkeley Lab Indexing Toolbox is intended to be used in the context of X-ray crystallography experiments involving biological macromolecules. Macromolecules such as proteins form 3-dimensional periodic arrays (crystal) which in turn lead to lattice-like diffraction patterns when the crystal sample is irradiated with collimated X-rays from a synchrotron or other X-ray source. Once the diffraction pattern is captured on an imaging device the next step is to deduce the periodic nature of the crystal sample, along with its internal symmetry. this analysis, known as "indexing" is a well-studied problem. However, there are no other implementations designed to operate in an automated setting, in which the human experimentalist is not prosent to manually verify the results of indexing. In particular LABELIT uses three novel algorithms to facilitate automation: a more robust way to verify the position of the incident X-ray beam on the image, a better way to verify that the deduced lattice is consistent with the observed crystal lattice, and new method to deduce the internal symmetry from measurements of the lattice. Moreover, the algorithms are implemented in a Python framework that permits indexing to fail (in rare cases) without crashing the program, thus allowing the software to be incorporated in robotic systems where unattended operation is expected. It will be especially useful for high throughput operations at snychrotron beamlines.
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@misc{osti_1230685,
title = {Lawrence Berkeley Lab Indexing Toolbox, Version 00},
author = {Sauter, Nicholas K.},
abstractNote = {The Lawrence Berkeley Lab Indexing Toolbox is intended to be used in the context of X-ray crystallography experiments involving biological macromolecules. Macromolecules such as proteins form 3-dimensional periodic arrays (crystal) which in turn lead to lattice-like diffraction patterns when the crystal sample is irradiated with collimated X-rays from a synchrotron or other X-ray source. Once the diffraction pattern is captured on an imaging device the next step is to deduce the periodic nature of the crystal sample, along with its internal symmetry. this analysis, known as "indexing" is a well-studied problem. However, there are no other implementations designed to operate in an automated setting, in which the human experimentalist is not prosent to manually verify the results of indexing. In particular LABELIT uses three novel algorithms to facilitate automation: a more robust way to verify the position of the incident X-ray beam on the image, a better way to verify that the deduced lattice is consistent with the observed crystal lattice, and new method to deduce the internal symmetry from measurements of the lattice. Moreover, the algorithms are implemented in a Python framework that permits indexing to fail (in rare cases) without crashing the program, thus allowing the software to be incorporated in robotic systems where unattended operation is expected. It will be especially useful for high throughput operations at snychrotron beamlines.},
doi = {},
url = {https://www.osti.gov/biblio/1230685},
year = {Mon Sep 08 00:00:00 EDT 2003},
month = {Mon Sep 08 00:00:00 EDT 2003},
note =
}
