ABSTRACT
Structural crystallography aims to provide a three-dimensional representation of macromolecules. Many parts of the multistep process to produce the three-dimensional structural model have been automated, especially through various structural genomics projects. A key step is the production of crystals for diffraction. The target macromolecule is combined with a large and chemically diverse set of cocktails with some leading ideally, but infrequently, to crystallization. A variety of outcomes will be observed during these screening experiments that typically require human interpretation for classification. Human interpretation is neither scalable nor objective, highlighting the need to develop an automatic computer-based image classification. As a first step towards automated image classification, 147,456 images representing crystallization experiments from 96 different macromolecular samples were manually classified. Each image was classified by three experts into seven predefined categories or their combinations. The resulting data where all three observers are in agreement provides one component of a truth set for the development and rigorous testing of automated image-classification systems and provides information about the chemical cocktails used for crystallization. In this paper, the details of this study are presented.
Subject(s)
Crystallography, X-Ray/methods , Image Processing, Computer-Assisted/methods , Macromolecular Substances/chemistry , Teaching/methods , Algorithms , Computer Graphics , Crystallization , Crystallography, X-Ray/classification , Electronic Data Processing , Humans , Image Processing, Computer-Assisted/classification , Models, Molecular , Teaching/trendsABSTRACT
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.
