In:
Acta Crystallographica Section D Biological Crystallography, International Union of Crystallography (IUCr), Vol. 58, No. 11 ( 2002-11-01), p. 1915-1923
Abstract:
A system for the automatic categorization of the results of crystallization experiments generated by robotic screening is presented. Images from robotically generated crystallization screens are taken at preset time intervals and analyzed by the computer program Crystal Experiment Evaluation Program ( CEEP ). This program attempts to automatically categorize the individual crystal experiments into a number of simple classes ranging from clear drop to mountable crystal. The algorithm first selects features from the images via edge detection and texture analysis. Classification is achieved via a self-organizing neural net generated from a set of hand-classified images used as a training set. New images are then classified according to this neural net. It is demonstrated that incorporation of time-series information may enhance the accuracy of classification. Preliminary results from the screening of the proteome of Thermotoga maritima are presented showing the utility of the system.
Type of Medium:
Online Resource
ISSN:
0907-4449
DOI:
10.1107/S0907444902016840
Language:
Unknown
Publisher:
International Union of Crystallography (IUCr)
Publication Date:
2002
detail.hit.zdb_id:
2968623-4
SSG:
12
SSG:
13
