Title: Signal representation and processing of nucleotide sequences

Authors: Paul Cristea, Rodica Tuduce, Iulian Nastac, Jan Cornelis, Rudi Deklerck, Marius Andrei

Addresses: Bio-Medical Engineering Center, University 'Politehnica' of Bucharest, Spl. Independentei 313, sect. 6, 060042, Bucharest, Romania. ' Bio-Medical Engineering Center, University 'Politehnica' of Bucharest, Spl. Independentei 313, sect. 6, 060042, Bucharest, Romania. ' Bio-Medical Engineering Center, University 'Politehnica' of Bucharest, Spl. Independentei 313, sect. 6, 060042, Bucharest, Romania. ' ETRO Department, Vrije Universiteit Brussel, Pleinlaan 2, B-1050 Brussels, Belgium. ' ETRO Department, Vrije Universiteit Brussel, Pleinlaan 2 B-1050 Brussel, Belgium. ' Google Inc., 1600 Amphitheater Pkwy, 94040 Mountain View, CA, USA

Abstract: Sets of related signals can be represented by separating their joint variation and showing the individual signal offsets with respect to this reference. An example is the Genomic Signal Analysis (GSA) of pathogen variability. The conversion of symbolic nucleotide sequences to genomic signals allows to use signal processing methods to analyse genomic data. This approach reveals striking regularities in the distribution of nucleotides and pair of nucleotides along the sequences, in both prokaryotes and eukaryotes. Genomic signals can also be used for sequence prediction, similarly to time series prediction. The methodology is also adequate for studying the development of pathogen multiple resistance to drugs.

Keywords: nucleotide genomic signals; pathogen variability; multiple drug resistance; signal representation; signal processing; nucleotide sequences; genomic signal analysis; GSA; prokaryotes; eukaryotes; sequence prediction.

DOI: 10.1504/IJFIPM.2008.021390

International Journal of Functional Informatics and Personalised Medicine, 2008 Vol.1 No.3, pp.253 - 268

Published online: 22 Nov 2008 *

Full-text access for editors Access for subscribers Purchase this article Comment on this article