Understanding the Signal Sequence
Protein translocation, the transport of newly synthesized proteins out of the cell, is a fundamental mechanism of life. In spite of tremendous variations in primary structure, signal sequences are very often functionally conserved across species. We are interested in understanding how cells recognize the proteins that are to be exported and how the necessary information is encoded in the so called signal Sequences.
We address these problems by building a physico-chemical model of signal sequence recognition, using experimental data. The models are built using decision trees and the attributes are generated with genetic algorithms techniques, according to experimentally localised proteins and the physico-chemical properties of amino-acids. The genetic algorithms are optimised by the evolutionary computing framework n-genes.