Open AccessEstablishing a training set through the visual analysis of crystallization trials. Part II: crystal examples
Author(s) -
Snell Edward H.,
Lauricella Angela M.,
Potter Stephen A.,
Luft Joseph R.,
Gulde Stacey M.,
Collins Robert J.,
Franks Geoff,
Malkowski Michael G.,
Cumbaa Christian,
Jurisica Igor,
DeTitta George T.
Publication year - 2008
Publication title -
acta crystallographica section d
Language(s) - English
Resource type - Journals
ISSN - 1399-0047
DOI - 10.1107/s0907444908028059
Subject(s) - crystallization , set (abstract data type) , crystal (programming language) , complement (music) , data set , genomics , training set , computer science , artificial intelligence , crystallography , biology , chemistry , genome , engineering , gene , biochemistry , chemical engineering , complementation , phenotype , programming language
In the automated image analysis of crystallization experiments, representative examples of outcomes can be obtained rapidly. However, while the outcomes appear to be diverse, the number of crystalline outcomes can be small. To complement a training set from the visual observation of 147 456 crystallization outcomes, a set of crystal images was produced from 106 and 163 macromolecules under study for the North East Structural Genomics Consortium (NESG) and Structural Genomics of Pathogenic Protozoa (SGPP) groups, respectively. These crystal images have been combined with the initial training set. A description of the crystal‐enriched data set and a preliminary analysis of outcomes from the data are described.