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  • Title: Automatic analysis of agarose gel images.
    Author: Adiga PS, Bhomra A, Turri MG, Nicod A, Datta SR, Jeavons P, Mott R, Flint J.
    Journal: Bioinformatics; 2001 Nov; 17(11):1084-9. PubMed ID: 11724740.
    Abstract:
    MOTIVATION: Automatic tools to speed up routine biological processes are very much sought after in bio-medical research. Much repetitive work in molecular biology, such as allele calling in genetic analysis, can be made semi-automatic or task specific automatic by using existing techniques from computer science and signal processing. Computerized analysis is reproducible and avoids various forms of human error. Semi-automatic techniques with an interactive check on the results speed up the analysis and reduce the error. RESULTS: We have successfully implemented an image processing software package to automatically analyze agarose gel images of polymorphic DNA markers. We have obtained up to 90% accuracy for the classification of alleles in good quality images and up to 70% accuracy in average quality images. These results are obtained within a few seconds. Even after subsequent interactive checking to increase the accuracy of allele classification to 100%, the overall speed with which the data can be processed is greatly increased, compared to manual allele classification. AVAILABILITY: The IDL source code of the software is available on request from jonathan.flint@well.ox.ac.uk
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