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Open Access

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

EURASIP Journal on Advances in Signal Processing20042004:153697

Received: 28 February 2003

Published: 21 January 2004


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.


signal peptidesgenetic programmingbioinformaticsprogrammatic motifartificial neural networkscleavage site

Authors’ Affiliations

Saida Medical AB, Göteborg, Sweden
Department of Physical Resource Theory, Chalmers University of Technology, Göteborg, Sweden


© Lennartsson and Nordin. 2004