Automatic Identification of DNA Markers based on Features Reduction.
This paper has implemented a feature reduction based on Independent Components Analysis (ICA) and Principal Component Analysis (PCA) for an automatic supervised identification system of Pejibaye palm DNA markers, using an Artificial Neural Network (ANN) as classifier; obtaining 100% for the classes' identification. The biochemical parameterization proposed, based on 89 RAPD primer markers applied on haplotypes of Pejibaye races, has correctly been proved for its reduction. The computational times have been studied, obtaining results in real time for test mode. Finally the interesting combination of these techniques (biochemical and computational), gives rise to a formulation of an inexpensive and handy method of origin denomination plant certification.
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