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Examples of applying a multivariate Wilson prior to comparative crystallography data

Authors: Hekstra, Doeke; Wang, Harrison K.; Dalton, Kevin M.;

Examples of applying a multivariate Wilson prior to comparative crystallography data

Abstract

This folder contains four examples of merging crystallographic intensities with a bivariate prior: time-resolved Laue crystallography of the photoactive yellow protein (pyp.zip) anomalous diffraction from serial XFEL crystallography of thermolysin (thermolysin_xfel.zip) anomalous diffraction from Laue crystallography of NaI-soaked lysozyme (lysozyme.zip) fragment screening monochromatic data of Nsp3 Mac1 (dfs.zip) Additionally, we provide several auxilliary examples: For PYP, an example where we set aside a test fraction to semi-independently optimize the double-Wilson r (pyp_test_fraction.zip) for lysozyme, two examples, one where we use Laue-DIALS instead of precognition (lysozyme-laue-dials.zip), and another where we set aside the first 90 images to semi-independently optimize the double-Wilson r (lysozyme_test_fraction.zip) For thermolysin, an example where we use a bivariate versus a univariate prior as the number of scaled images grows (thermolysin_xfel_frames_sweep.zip), and another where we set aside the first 395 images to semi-independently optimize the double-Wilson r (thermolysin_xfel_test_fraction.zip) Finally, we provide zip files containing Careless repositories (careless_041.zip, careless_053.zip) and the dw repository containing Jupyter notebooks outlining the theory of the double-Wilson model (dw.zip). Every example includes scripts to run Careless as well as to analyze the outputs in order to reproduce the figures in the double-Wilson manuscript. For every example, there is a `README.md` that describes the contents of each example folder.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average