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Next: Introduction

SPEP: a Signal Peptide Predictor Based on Neural Network Systems

Piero Fariselli - Giacomo Finocchiaro - Rita Casadio

Department of Biology/CIRB University of Bologna,
via Irnerio 42, 40126 Bologna, Italy

{Piero.Fariselli, Rita.Casadio}


A Neural-Network-based system is trained and tested on a set of well annotated proteins to tackle the problem of predicting the signal peptide in protein sequences. The method trained on a set of experimentally derived signal peptides from Eukaryotes and Prokaryotes, identifies the presence of the sorting signal and predicts their cleavage sites. The accuracy in cross-validation is comparable with previously presented programs reaching the 97%, 97% and 95% for Gram negative, Gram positive and Eukaryotes, respectively.

(Click here for the cross-validation sets )