@article{AgaroseGelImage,
  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.",
  author = "P. S. Umesh Adiga, A. Bhomra, M. G. Turri, A. Nicod, S. R. Datta, Peter Jeavons, Richard Mott, Jonathan Flint",
  journal = "Bioinformatics",
  number = "11",
  pages = "1084-1089",
  title = "Automatic analysis of agarose gel images",
  url = "http://bioinformatics.oxfordjournals.org/cgi/content/abstract/17/11/1084",
  volume = "17",
  year = "2001",
}