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A Genetic Programming Method for the Identification of Signal Peptides and Prediction of Their Cleavage Sites

Abstract

A novel approach to signal peptide identification is presented. We use an evolutionary algorithm for automatic evolution of classification programs, so-called programmatic motifs. The variant of evolutionary algorithm used is called genetic programming where a population of solution candidates in the form of full computer programs is evolved, based on training examples consisting of signal peptide sequences. The method is compared with a previous work using artificial neural network (ANN) approaches. Some advantages compared to ANNs are noted. The programmatic motif can perform computational tasks beyond that of feed-forward neural networks and has also other advantages such as readability. The best motif evolved was analyzed and shown to detect the h-region of the signal peptide. A powerful parallel computer cluster was used for the experiment.

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Correspondence to David Lennartsson.

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Lennartsson, D., Nordin, P. A Genetic Programming Method for the Identification of Signal Peptides and Prediction of Their Cleavage Sites. EURASIP J. Adv. Signal Process. 2004, 153697 (2004). https://doi.org/10.1155/S1110865704309108

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Keywords

  • signal peptides
  • genetic programming
  • bioinformatics
  • programmatic motif
  • artificial neural networks
  • cleavage site
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