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Journal ArticleDOI

On the treatment of negative intensity observations

Simon French, +1 more
- 01 Jul 1978 - 
- Vol. 34, Iss: 4, pp 517-525
TLDR
In this article, a method is described which produces sensible estimates of structure factor moduli from intensity observations, whether the latter are positive or negative, and preliminary applications of the method to data from the protein phosphorylase b are summarized.
Abstract
A method is described which produces sensible estimates of structure factor moduli from intensity observations, whether the latter are positive or negative. Preliminary applications of the method to data from the protein phosphorylase b are summarized.

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Citations
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Journal ArticleDOI

How good are my data and what is the resolution

TL;DR: The new scaling program AIMLESS is described and tests of refinements at different resolutions are compared with analyses from the scaling step.
Journal ArticleDOI

Model for the structure of bacteriorhodopsin based on high-resolution electron cryo-microscopy.

TL;DR: A complete atomic model for bacteriorhodopsin between amino acid residues 8 and 225 has been built and suggests that pK changes in the Schiff base must act as the means by which light energy is converted into proton pumping pressure in the channel.
Journal ArticleDOI

Comprehensive Functional Maps of the Antigen-binding Site of an Anti-ErbB2 Antibody Obtained with Shotgun Scanning Mutagenesis

TL;DR: The results validate shotgun scanning as a rapid and accurate method for determining the functional contributions of individual side-chains involved in protein-protein interactions.
Journal ArticleDOI

An introduction to data reduction: space-group determination, scaling and intensity statistics.

TL;DR: A summary of how to run the data-reduction programs in the CCP4 suite.
References
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Book

Bayesian inference in statistical analysis

TL;DR: In this article, the effect of non-normality on inference about a population mean with generalizations was investigated. But the authors focused on the effect on the mean with information from more than one source.
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