Feedforward Neural Networks for the Classification of Two-dimensional Polyacrylamide Gel Electrophoresis Images

  • Ariel Cary
  • Davor Pavisic
  • Reynaldo Vargas
Palabras clave: Neural networks, proteomics, 2D-PAGE


This article describes a method, using neural networks, for classifying twodimensional polyacrylamide gel electrophoretograms, complex biomedical images
that contain proteins separated from a biological sample. The classification aims
at grouping images and identifying their most significant features. The gel image
processing part is first summarized. The details on how the classification is accomplished using neural networks axe then presented. After that, an experiment
using real gels of rat cells is carried out, showing the successful implementation
and application of this method. Finally, experimental results show that this neural
network based method is more than 90% effective.

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