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Identification of heavy‐atom derivatives by normal probability methods
Author(s) -
Howell P. L.,
Smith G. D.
Publication year - 1992
Publication title -
journal of applied crystallography
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.429
H-Index - 162
ISSN - 1600-5767
DOI - 10.1107/s0021889891010385
Subject(s) - atom (system on chip) , resolution (logic) , set (abstract data type) , identification (biology) , data set , derivative (finance) , measure (data warehouse) , experimental data , computer science , function (biology) , biological system , algorithm , chemistry , data mining , statistics , mathematics , artificial intelligence , biology , botany , evolutionary biology , financial economics , embedded system , economics , programming language
Normal and half‐normal probability plots have been used extensively in the analysis of data and parameters in small‐molecule crystallography. A procedure and computer program is described to apply this method to macromolecular data. The utility of this procedure is that a subset of data from a putative heavy‐atom derivative can be analyzed and compared with a native set of data providing a quantitative indicator of individual and overall changes in intensity. A qualitative measure of the scattering contribution as a function of resolution can be obtained from comparisons of different resolution ranges. The results from comparisons of (i) native data collected by different techniques and (ii) native and heavy‐atom‐derivative data suggest a set of guidelines which can be used as an aid in the selection of data with a significant heavy‐atom contribution.